Статті в журналах з теми "Goodness metric"
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1
Adebolu, Ibukun O., Hirokazu Masui, and Mengu Cho. "Quantitative Evaluation of SRS Similarity for Aerospace Testing Applications." Shock and Vibration 2021 (February 8, 2021): 1–10. http://dx.doi.org/10.1155/2021/6655878.
Повний текст джерелаАнотація:
The similarity between a shock response spectrum (SRS) and a target shock specification is essential in evaluating the success of a qualification test of a space component. Qualification testing facilities often utilize shock response databases for rapid testing. Traditionally, the comparison of two shocks (SRS) depends on visual evaluation, which is, at best, subjective. This paper compares five different quantitative methods for evaluating shock response similarity. This work aims to find the most suitable metric for retrieving an SRS from a pyroshock database. The five methods are the SRS difference, mean acceleration difference, average SRS ratio, dimensionless SRS coefficients, and mean square goodness-of-fit method. None of the similarity metrics account for the sign of the deviation between the target SRS and database SRS, making it challenging to satisfy the criteria for a good shock test. We propose a metric (the weighted distance) for retrieving the most similar SRS to a target SRS specification from a shock database in this work. The weighted distance outperforms the mean square goodness-of-fit and other metrics in database SRS retrieval for rapid qualification testing.
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Franco, Manuel, Juana María Vivo, Manuel Quesada-Martínez, Astrid Duque-Ramos, and Jesualdo Tomás Fernández-Breis. "Evaluation of ontology structural metrics based on public repository data." Briefings in Bioinformatics 21, no. 2 (February 4, 2019): 473–85. http://dx.doi.org/10.1093/bib/bbz009.
Повний текст джерелаАнотація:
Abstract The development and application of biological ontologies have increased significantly in recent years. These ontologies can be retrieved from different repositories, which do not provide much information about quality aspects of the ontologies. In the past years, some ontology structural metrics have been proposed, but their validity as measurement instrument has not been sufficiently studied to date. In this work, we evaluate a set of reproducible and objective ontology structural metrics. Given the lack of standard methods for this purpose, we have applied an evaluation method based on the stability and goodness of the classifications of ontologies produced by each metric on an ontology corpus. The evaluation has been done using ontology repositories as corpora. More concretely, we have used 119 ontologies from the OBO Foundry repository and 78 ontologies from AgroPortal. First, we study the correlations between the metrics. Second, we study whether the clusters for a given metric are stable and have a good structure. The results show that the existing correlations are not biasing the evaluation, there are no metrics generating unstable clusterings and all the metrics evaluated provide at least reasonable clustering structure. Furthermore, our work permits to review and suggest the most reliable ontology structural metrics in terms of stability and goodness of their classifications. Availability: http://sele.inf.um.es/ontology-metrics
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CHAN, VICTOR K. Y., W. ERIC WONG, and T. F. XIE. "A STATISTICAL METHODOLOGY TO SIMPLIFY SOFTWARE METRIC MODELS CONSTRUCTED USING INCOMPLETE DATA SAMPLES." International Journal of Software Engineering and Knowledge Engineering 17, no. 06 (December 2007): 689–707. http://dx.doi.org/10.1142/s0218194007003495.
Повний текст джерелаАнотація:
Software metric models predict the target software metric(s), e.g., the development work effort or defect rates, for any future software project based on the project's predictor software metric(s), e.g., the project team size. Obviously, the construction of such a software metric model makes use of a data sample of such metrics from analogous past projects. However, incomplete data often appear in such data samples. Moreover, the decision on whether a particular predictor metric should be included is most likely based on an intuitive or experience-based assumption that the predictor metric has an impact on the target metric with a statistical significance. However, this assumption is usually not verifiable "retrospectively" after the model is constructed, leading to redundant predictor metric(s) and/or unnecessary predictor metric complexity. To solve all these problems, we derived a methodology consisting of the k-nearest neighbors (k-NN) imputation method, statistical hypothesis testing, and a "goodness-of-fit" criterion. This methodology was tested on software effort metric models and software quality metric models, the latter usually suffers from far more serious incomplete data. This paper documents this methodology and the tests on these two types of software metric models.
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Kang, Tae-Ho, Ashish Sharma, and Lucy Marshall. "Assessing Goodness of Fit for Verifying Probabilistic Forecasts." Forecasting 3, no. 4 (October 27, 2021): 763–73. http://dx.doi.org/10.3390/forecast3040047.
Повний текст джерелаАнотація:
The verification of probabilistic forecasts in hydro-climatology is integral to their development, use, and adoption. We propose here a means of utilizing goodness of fit measures for verifying the reliability of probabilistic forecasts. The difficulty in measuring the goodness of fit for a probabilistic prediction or forecast is that predicted probability distributions for a target variable are not stationary in time, meaning one observation alone exists to quantify goodness of fit for each prediction issued. Therefore, we suggest an additional dissociation that can dissociate target information from the other time variant part—the target to be verified in this study is the alignment of observations to the predicted probability distribution. For this dissociation, the probability integral transformation is used. To measure the goodness of fit for the predicted probability distributions, this study uses the root mean squared deviation metric. If the observations after the dissociation can be assumed to be independent, the mean square deviation metric becomes a chi-square test statistic, which enables statistically testing the hypothesis regarding whether the observations are from the same population as the predicted probability distributions. An illustration of our proposed rationale is provided using the multi-model ensemble prediction for El Niño–Southern Oscillation.
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Nadir, Zeeshan, Kristin M. Rice, Michael S. Brown, and Charles A. Bouman. "Testing the Goodness of Model Fit in Tunable Diode Laser Absorption Tomography." Electronic Imaging 2021, no. 15 (January 18, 2021): 291–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.15.coimg-291.
Повний текст джерелаАнотація:
Tunable diode laser absorption tomography (TDLAT) has emerged as a popular nonintrusive technique for simultaneous sensing of gas concentration and temperature by making light absorbance measurements. Major challenge of TDLAT imaging is that the measurement data is very sparse. Therefore, precise models are required to describe the measurement process (forward model) and the behavior of the gas flow properites (prior model) to get accurate reconstructions. The sparsity of the measurement data makes TDLAT very sensitive to the accuracy of the models and makes it prone to overfitting. Both the forward and prior models can have systematic errors due to several reasons. So far, substantial amount of work has been done by researchers on developing reconstruction methods and formulating models, forward and prior. Yet, there has not been significant research work done on constructing a metric for goodness of the model fit that can indicate when there is an inaccuracy in the forward or the prior model. In this paper, we present a metric for goodness of model fit that can be used to indicate if the models used in the reconstruction are inaccurate. Results show that our metric can reliably quantify the goodness of model fit for sparese data reconstruction problems such as TDLAT.
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Chechile, Richard A. "A vector-based goodness-of-fit metric for interval-scaled data." Communications in Statistics - Theory and Methods 28, no. 2 (January 1999): 277–96. http://dx.doi.org/10.1080/03610929908832298.
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Babić, Sladana, Christophe Ley, Lorenzo Ricci, and David Veredas. "TailCoR: A new and simple metric for tail correlations that disentangles the linear and nonlinear dependencies that cause extreme co-movements." PLOS ONE 18, no. 1 (January 3, 2023): e0278599. http://dx.doi.org/10.1371/journal.pone.0278599.
Повний текст джерелаАнотація:
Economic and financial crises are characterised by unusually large events. These tail events co-move because of linear and/or nonlinear dependencies. We introduce TailCoR, a metric that combines (and disentangles) these linear and non-linear dependencies. TailCoR between two variables is based on the tail inter quantile range of a simple projection. It is dimension-free, and, unlike competing metrics, it performs well in small samples and no optimisations are needed. Indeed, TailCoR requires a few lines of coding and it is very fast. A Monte Carlo analysis confirms the goodness of the metric, which is illustrated on a sample of 21 daily financial market indexes across the globe and for 20 years. The estimated TailCoRs are in line with the financial and economic events, such as the 2008 great financial crisis and the 2020 pandemic.
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Farhang-Mehr, Ali, and Shapour Azarm. "An Information-Theoretic Entropy Metric for Assessing Multi-Objective Optimization Solution Set Quality." Journal of Mechanical Design 125, no. 4 (December 1, 2003): 655–63. http://dx.doi.org/10.1115/1.1623186.
Повний текст джерелаАнотація:
An entropy-based metric is presented that can be used for assessing the quality of a solution set as obtained from multi-objective optimization techniques. This metric quantifies the “goodness” of a set of solutions in terms of distribution quality over the Pareto frontier. The metric can be used to compare the performance of different multi-objective optimization techniques. In particular, the metric can be used in analysis of multi-objective evolutionary algorithms, wherein the capabilities of such techniques to produce and maintain diversity among different solution points are desired to be compared on a quantitative basis. An engineering test example, the multi-objective design optimization of a speed-reducer, is provided to demonstrate an application of the proposed entropy metric.
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Graffelman, Jan. "Goodness-of-fit filtering in classical metric multidimensional scaling with large datasets." Journal of Applied Statistics 47, no. 11 (December 17, 2019): 2011–24. http://dx.doi.org/10.1080/02664763.2019.1702929.
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Arnastauskaitė, Jurgita, Tomas Ruzgas, and Mindaugas Bražėnas. "An Exhaustive Power Comparison of Normality Tests." Mathematics 9, no. 7 (April 6, 2021): 788. http://dx.doi.org/10.3390/math9070788.
Повний текст джерелаАнотація:
A goodness-of-fit test is a frequently used modern statistics tool. However, it is still unclear what the most reliable approach is to check assumptions about data set normality. A particular data set (especially with a small number of observations) only partly describes the process, which leaves many options for the interpretation of its true distribution. As a consequence, many goodness-of-fit statistical tests have been developed, the power of which depends on particular circumstances (i.e., sample size, outlets, etc.). With the aim of developing a more universal goodness-of-fit test, we propose an approach based on an N-metric with our chosen kernel function. To compare the power of 40 normality tests, the goodness-of-fit hypothesis was tested for 15 data distributions with 6 different sample sizes. Based on exhaustive comparative research results, we recommend the use of our test for samples of size n≥118.
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Horak, Danijela, Simiao Yu, and Gholamreza Salimi-Khorshidi. "Topology Distance: A Topology-Based Approach for Evaluating Generative Adversarial Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7721–28. http://dx.doi.org/10.1609/aaai.v35i9.16943.
Повний текст джерелаАнотація:
Automatic evaluation of the goodness of Generative Adversarial Networks (GANs) has been a challenge for the field of machine learning. In this work, we propose a distance complementary to existing measures: Topology Distance (TD), the main idea behind which is to compare the geometric and topological features of the latent manifold of real data with those of generated data. More specifically, we build Vietoris-Rips complex on image features, and define TD based on the differences in persistent-homology groups of the two manifolds. We compare TD with the most commonly-used and relevant measures in the field, including Inception Score (IS), Fr\'echet Inception Distance (FID), Kernel Inception Distance (KID) and Geometry Score (GS), in a range of experiments on various datasets. We demonstrate the unique advantage and superiority of our proposed approach over the aforementioned metrics. A combination of our empirical results and the theoretical argument we propose in favour of TD, strongly supports the claim that TD is a powerful candidate metric that researchers can employ when aiming to automatically evaluate the goodness of GANs’ learning.
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Sampson, Geoffrey. "A Proposal for Improving the Measurement of Parse Accuracy." International Journal of Corpus Linguistics 5, no. 1 (July 28, 2000): 53–68. http://dx.doi.org/10.1075/ijcl.5.1.04sam.
Повний текст джерелаАнотація:
Widespread dissatisfaction has been expressed with the measure of parse accuracy used in the Parseval programme, based on the location of constituent boundaries. Scores on the Parseval metric are perceived as poorly correlated with intuitive judgments of goodness of parse; the metric applies only to a restricted range of grammar formalisms; and it is seen as divorced from applications of NLP technology. The present paper defines an alternative metric, which measures the accuracy with which successive words are fitted into parsetrees. (The original statement of this metric is believed to have been the earliest published proposal about quantifying parse accuracy.) The metric defined here gives overall scores that quantify intuitive concepts of good and bad parsing relatively directly, and it gives scores for individual words which enable the location of parsing errors to be pinpointed. It applies to a wider range of grammar formalisms, and is tunable for specific parsing applications.
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Külske, Christof, and Alex Opoku. "The Posterior metric and the Goodness of Gibbsianness for transforms of Gibbs measures." Electronic Journal of Probability 13 (2008): 1307–44. http://dx.doi.org/10.1214/ejp.v13-560.
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Vriens, Marco, Michel Wedel, and Tom Wilms. "Metric Conjoint Segmentation Methods: A Monte Carlo Comparison." Journal of Marketing Research 33, no. 1 (February 1996): 73–85. http://dx.doi.org/10.1177/002224379603300107.
Повний текст джерелаАнотація:
The authors compare nine metric conjoint segmentation methods. Four methods concern two-stage procedures in which the estimation of conjoint models and the partitioning of the sample are performed separately; in five, the estimation and segmentation stages are integrated. The methods are compared conceptually and empirically in a Monte Carlo study. The empirical comparison pertains to measures that assess parameter recovery, goodness-of-fit, and predictive accuracy. Most of the integrated conjoint segmentation methods outperform the two-stage clustering procedures under the conditions specified, in which a latent class procedure performs best. However, differences in predictive accuracy were small. The effects of degrees of freedom for error and the number of respondents were considerably smaller than those of number of segments, error variance, and within-segment heterogeneity.
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Short, Jeffrey. "Oil Identification Based on a Goodness-of-Fit Metric Applied to Hydrocarbon Analysis Results." Environmental Forensics 3, no. 3 (January 1, 2002): 349–55. http://dx.doi.org/10.1080/713848379.
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Short, J. "Oil Identification Based on a Goodness-of-Fit Metric Applied to Hydrocarbon Analysis Results." Environmental Forensics 3, no. 3-4 (September 2002): 349–55. http://dx.doi.org/10.1006/enfo.2002.0105.
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Carlson, Clinton P., and Dimitrios Zekkos. "A Metric to Screen Acceptable Velocity and Displacement Time Histories of Modified Ground Motions." Earthquake Spectra 33, no. 4 (November 2017): 1495–512. http://dx.doi.org/10.1193/011117eqs012m.
Повний текст джерелаАнотація:
Ground motion modification is extensively used in practice to modify a seed acceleration time history in intensity and frequency content until its acceleration response spectrum matches a target spectrum. However, the decision to accept or reject a modified motion commonly relies on a subjective process where the time histories of the modified motion are visually compared to those of the seed motion. Various metrics were used to quantify the similarity between the modified time histories and their scaled counterparts for hundreds of modified ground motions from three different earthquake scenarios. Of the metrics considered, the inverse modified RMSE metric for time histories ( imRMSE t) was found most appropriate as it resulted in the least amount of dispersion in the goodness-of-fit values with respect to spectral mismatch. The imRMSE t was then found to be correlated to qualitative rankings assigned to the modified time histories through a visual assessment. The correlation between the quantitative imRMSE t values and qualitative rankings is used to establish threshold values to screen modified velocity and displacement time histories that are likely acceptable or likely unacceptable.
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Onyutha, Charles. "A hydrological model skill score and revised R-squared." Hydrology Research 53, no. 1 (November 18, 2021): 51–64. http://dx.doi.org/10.2166/nh.2021.071.
Повний текст джерелаАнотація:
Abstract Despite the advances in methods of statistical and mathematical modeling, there is considerable lack of focus on improving how to judge models’ quality. Coefficient of determination (R2) is arguably the most widely applied ‘goodness-of-fit’ metric in modelling and prediction of environmental systems. However, known issues of R2 are that it: (i) can be low and high for an accurate and imperfect model, respectively; (ii) yields the same value when we regress observed on modelled series and vice versa; and (iii) does not quantify a model's bias. A new model skill score E and revised R-squared (RRS) are presented to combine correlation, bias measure and capacity to capture variability. Differences between E and RRS lie in the forms of correlation and variability measure used for each metric. Acceptability of E and RRS was demonstrated through comparison of results from a large number of hydrological simulations. By applying E and RRS, the modeller can diagnostically identify and expose systematic issues behind model optimizations based on other ‘goodness-of-fits’ such as Nash–Sutcliffe efficiency (NSE) and mean squared error. Unlike NSE, which varies from −∞ to 1, E and RRS occur over the range 0–1. MATLAB codes for computing E and RRS are provided.
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Fisher, Franklin M. "A metric for assessing the “goodness” of income distributions and the effect of price changes." Journal of Economic Theory 109, no. 2 (April 2003): 324–32. http://dx.doi.org/10.1016/s0022-0531(03)00015-2.
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Muddu, Shashank Venkat, and Rohit Ramachandran. "A Population Balance Methodology Incorporating Semi-Mechanistic Residence Time Metrics for Twin Screw Granulation." Processes 10, no. 2 (January 31, 2022): 292. http://dx.doi.org/10.3390/pr10020292.
Повний текст джерелаАнотація:
This work is concerned with the incorporation of semi-mechanistic residence time metrics into population balance equations for twin screw granulation processes to predict key properties. From the historical residence time and particle size data sourced, process parameters and equipment configuration information were fed into the system of equations where the input flow rates and model compartmentalization varied upon the parameters. Semi-mechanistic relations for the residence time metrics were employed to predict the particle velocities and dispersion coefficients in the axial flow direction of the twin screw granulation. The developed model was then calibrated for several experimental run points in each data-set. The predictions were evaluated quantitatively through the parity plots. The root mean square error (RMSE) was used as a metric to compare the degree of goodness of fit for different data-sets using the developed semi-mechanistic relations. In summary, this paper presents a more mechanistic but simplified approach of feeding residence time metrics into the population balance equations for twin screw granulation processes.
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Barrett, Bradford S., and Sultan Hameed. "Seasonal Variability in Precipitation in Central and Southern Chile: Modulation by the South Pacific High." Journal of Climate 30, no. 1 (January 2017): 55–69. http://dx.doi.org/10.1175/jcli-d-16-0019.1.
Повний текст джерелаАнотація:
Monthly precipitation in Chile (30°–55°S) was found to vary by intensity, latitude, and longitude of the South Pacific high (SPH). In austral winter, precipitation was higher when the SPH was weaker and when it was centered farther west. In austral spring, precipitation was higher when the SPH was weaker, similar to winter. However, spring precipitation was not found to be related to SPH longitude, and higher precipitation was found when the SPH was centered farther north. In austral summer, no relationship was found between precipitation and either SPH intensity or longitude, but positive correlations were found between precipitation and latitude of the SPH. In austral autumn, correlation patterns between precipitation and all three SPH metrics more closely resembled those seen in winter. The results of a multiple linear regression confirmed the importance of two SPH metrics (intensity and longitude) and the unimportance of a third SPH metric (latitude) in understanding variability in winter, summer, and autumn precipitation in central and southern Chile. In spring, regression results confirmed a relationship between precipitation and SPH intensity and latitude. Furthermore, the SPH intensity and longitude in winter combined to hindcast monthly precipitation with a better goodness of fit than five El Niño–Southern Oscillation metrics traditionally related to Chilean precipitation. Anomalies of lower-tropospheric circulation and vertical velocities were found to support the observed relationships between SPH and precipitation. Based on these results, a physical mechanism is proposed that employs the SPH as a metric to aid in understanding variability in precipitation in central and south-central Chile in all seasons.
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Campidelli, M., A. G. Razaqpur, and S. Foo. "Reliability-based load factors for blast design." Canadian Journal of Civil Engineering 40, no. 5 (May 2013): 461–74. http://dx.doi.org/10.1139/cjce-2011-0411.
Повний текст джерелаАнотація:
In this study the concepts of reliability are used to derive blast load factors. First, some objective criteria are proposed for the proper interpretation of pressure data gathered in arena tests. These criteria are applied to the pressure–time histories recorded during field tests involving live explosive detonated in contact with the ground. Three major shock wavefront parameters, including peak pressure, impulse, and positive phase duration are calculated. Next, statistical analysis is performed on these metrics to estimate their probability density functions and goodness-of-fit tests are carried out to gauge the appropriateness of each estimate. Using the best-fitting distribution for each wavefront metric, load factors are derived on the basis of two approaches. The first approach employs the percentiles of the three load metrics, each estimated using the pertinent probability distribution. The second approach uses concepts of reliability and presents load factors for low, medium, and high level of protection. The two sets of load factors are compared and the limitations of each approach are discussed.
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Adrangi, Bahram, and Kambiz Raffiee. "Optimization Analysis of the U.S. Aggregate Consumption: A Goodness-of-Fit Approach." American Economist 41, no. 2 (October 1997): 62–69. http://dx.doi.org/10.1177/056943459704100208.
Повний текст джерелаАнотація:
This paper examines the hypothesis of optimizing behavior of the U.S. consumers using quarterly and seasonally adjusted series on real consumer expenditures on eight commodity groups: clothing, durable goods, energy, food, housing, medical care, transportation, and others for the period of 1947:I through 1993:I. Following the Weak Axiom of Revealed Preference (WARP), a money-metric utility function is derived to calculate an efficiency index to determine the percentage difference between the observed cost of consumption and the optimum cost of consumption in each period of the sample. The empirical results provide evidence that the allocative efficiency in the U.S. has improved only slightly due to the wave of deregulations in the early 1980s. Our results are consistent with the predictions of the general theory of second best in showing that gains in the allocative efficiency may be minimal as long as many sectors of the economy remain partially or totally regulated.
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Muddu, Shashank Venkat, Lalith Kotamarthy, and Rohit Ramachandran. "A Semi-Mechanistic Prediction of Residence Time Metrics in Twin Screw Granulation." Pharmaceutics 13, no. 3 (March 16, 2021): 393. http://dx.doi.org/10.3390/pharmaceutics13030393.
Повний текст джерелаАнотація:
This work is concerned with the semi-mechanistic prediction of residence time metrics using historical data from mono-component twin screw wet granulation processes. From the data, several key parameters such as powder throughput rate, shafts rotation speed, liquid binder feed ratio, number of kneading elements in the shafts and the stagger angle between the kneading elements were identified and physical factors were developed to translate those varying parameters into expressions affecting the key intermediate phenomena in the equipment, holdup, flow and mixing. The developed relations were then tested across datasets to evaluate the performance of the model, applying a k-fold optimization technique. The semi-mechanistic predictions were evaluated both qualitatively through the main effects plots and quantitatively through the parity plots and correlations between the tuning constants across datasets. The root mean square error (RMSE) was used as a metric to compare the degree of goodness of fit for different datasets using the developed semi-mechanistic relations. In summary this paper presents a new approach at estimating both the residence time metrics in twin screw wet granulation, mean residence time (MRT) and variance through semi-mechanistic relations, the validity of which have been tested for different datasets.
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Novotný, Jan Sebastian, Lucie Váchová, and Jana Kvintová. "Validation of the Factor Structure and Gender-Related Measurement Invariance of the Inventory of Socially Supportive Behaviors (Short Form): Proposing an Alternative Design." Social Sciences 11, no. 11 (November 18, 2022): 528. http://dx.doi.org/10.3390/socsci11110528.
Повний текст джерелаАнотація:
The aim of this paper was to validate the factor structure and gender-related measurement invariance of the short form of the Inventory of Socially Supportive Behaviors (ISSB). The study sample consisted of 710 undergraduate students aged 19–55 years. A confirmatory factor analysis of the original design confirmed a three-factor structure with an acceptable goodness of fit (CFI = 0.910, TLI = 0.894, RMSEA = 0.066) and validity; however, some indices hinted at potential weak points. Therefore, we proposed an alternative model with the identical three-factor structure but fewer items. This model showed a better goodness of fit (CFI = 0.953, TLI = 0.936, RMSEA = 0.064) and was superior to the original design (p < 0.001). Convergent and discriminant validity and reliability were also good. Finally, a gender-related measurement invariance analysis demonstrated invariance in the ISSB structure for both models, while revealing partial metric and scalar invariance. In conclusion, the findings suggest that the ISSB-SF is a reliable, efficient and rapid tool for measuring received social support, with the proposed alternative design possibly being advantageous if validated on other populations.
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Livadiotis, George. "General Fitting Methods Based on Lq Norms and their Optimization." Stats 3, no. 1 (January 6, 2020): 16–31. http://dx.doi.org/10.3390/stats3010002.
Повний текст джерелаАнотація:
The widely used fitting method of least squares is neither unique nor does it provide the most accurate results. Other fitting methods exist which differ on the metric norm can be used for expressing the total deviations between the given data and the fitted statistical model. The least square method is based on the Euclidean norm L2, while the alternative least absolute deviations method is based on the Taxicab norm, L1. In general, there is an infinite number of fitting methods based on metric spaces induced by Lq norms. The most accurate, and thus optimal method, is the one with the (i) highest sensitivity, given by the curvature at the minimum of total deviations, (ii) the smallest errors of the fitting parameters, (iii) best goodness of fitting. The first two cases concern fitting methods where the given curve functions or datasets do not have any errors, while the third case deals with fitting methods where the given data are assigned with errors.
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Wen, Ming, Zhi Ye, Danhua Lin, and Weidong Wang. "Preliminary development of a multidimensional positive youth development scale for young rural and urban adolescents in China." PLOS ONE 17, no. 7 (July 28, 2022): e0270974. http://dx.doi.org/10.1371/journal.pone.0270974.
Повний текст джерелаАнотація:
This study examined the dimensionality, reliability, and validity of a Chinese version of the 5-C Model of positive youth development (PYD), originally developed in the U.S., with a sample of rural and urban young adolescents in China. The Cs represent five youth strengths: competence, confidence, character, caring, and connection. The results of the exploratory factor analyses showed a reasonable data fit with the 5-C Model. The total and subscale scores evinced good internal reliability (α = .7 to .9) and the confirmatory factor analyses confirmed the convergence of the five Cs on a second-order latent factor of PYD, showing adequate goodness of fit (CFI = 0.94; TLI = 0.93; RMSEA = 0.04). Metric and scalar invariance were found across gender. Metric and partial scalar invariance were found for rural-urban groups. Supportive evidence on convergent and discriminatory validity was also found. We conclude that the Chinese version of the 5-C PYD Scale is a reliable and valid instrument, with good construct validity for Chinese young adolescents.
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Rezapour, Mahdi, and Khaled Ksaibati. "Accounting for Attribute Non-Attendance and Common-Metric Aggregation in the Choice of Seat Belt Use, a Latent Class Model with Preference Heterogeneity." Algorithms 14, no. 3 (March 6, 2021): 84. http://dx.doi.org/10.3390/a14030084.
Повний текст джерелаАнотація:
A choice to use a seat belt is largely dependent on the psychology of the vehicles’ occupants, and thus those decisions are expected to be characterized by preference heterogeneity. Despite the importance of seat belt use on the safety of the roadways, the majority of existing studies ignored the heterogeneity in the data and used a very standard statistical or descriptive method to identify the factors of using a seatbelt. Application of the right statistical method is of crucial importance to unlock the underlying factors of the choice being made by vehicles’ occupants. Thus, this study was conducted to identify the contributory factors to the front-seat passengers’ choice of seat belt usage, while accounting for the choice preference heterogeneity. The latent class model has been offered to replace the mixed logit model by replacing a continuous distribution with a discrete one. However, one of the shortcomings of the latent class model is that the homogeneity is assumed across a same class. A further extension is to relax the assumption of homogeneity by allowing some parameters to vary across the same group. The model could still be extended to overlay some attributes by considering attributes non-attendance (ANA), and aggregation of common-metric attributes (ACMA). Thus, this study was conducted to make a comparison across goodness of fit of the discussed models. Beside a comparison based on goodness of fit, the share of individuals in each class was used to see how it changes based on various model specifications. In summary, the results indicated that adding another layer to account for the heterogeneity within the same class of the latent class (LC) model, and accounting for ANA and ACMA would improve the model fit. It has been discussed in the content of the manuscript that accounting for ANA, ACMA and an extra layer of heterogeneity does not just improve the model goodness of fit, but largely impacts the share of class allocation of the models.
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Jayadevan, Vijai, Tadamasa Sawada, Edward Delp, and Zygmunt Pizlo. "Perception of 3D Symmetrical and Nearly Symmetrical Shapes." Symmetry 10, no. 8 (August 16, 2018): 344. http://dx.doi.org/10.3390/sym10080344.
Повний текст джерелаАнотація:
The human visual system uses priors to convert an ill-posed inverse problem of 3D shape recovery into a well-posed one. In previous studies, we have demonstrated the use of priors like symmetry, compactness and minimal surface in the perception of 3D symmetric shapes. We also showed that binocular perception of symmetric shapes can be well modeled by the above-mentioned priors and binocular depth order information. In this study, which used a shape-matching task, we show that these priors can also be used to model perception of near-symmetrical shapes. Our near-symmetrical shapes are asymmetrical shapes obtained from affine distortions of symmetrical shapes. We found that the perception of symmetrical shapes is closer to veridical than the perception of asymmetrical shapes is. We introduce a metric to measure asymmetry of abstract polyhedral shapes, and a similar metric to measure shape dissimilarity between two polyhedral shapes. We report some key observations obtained by analyzing the data from the experiment. A website was developed with all the shapes used in the experiment, along with the shapes recovered by the subject and the shapes recovered by the model. This website provides a qualitative analysis of the effectiveness of the model and also helps demonstrate the goodness of the shape metric.
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Manda, Rajasekhar, and Dr P. Rajesh Kumar. "Merit factor analysis of polyphaser sequences using cyclic algorithm new with good correlation properties." International Journal of Engineering & Technology 7, no. 3.29 (August 24, 2018): 203. http://dx.doi.org/10.14419/ijet.v7i3.29.18796.
Повний текст джерелаАнотація:
Polyphase sequences such as Pn (n=1, 2, 3, 4, x), Golomb, Frank, and the Chu are with good correlation properties, lower sidelobe levels and large merit factor values are helpful in applications like radar, sonar and channel estimation and communications. The goodness of a sequence obtained from merit factor. The transmitted and received signal may not be the same due to noise. The correlation function of given sequence is expressed by ISL (Integrated Sidelobe Level) by minimizing the ISL metrics the performance parameter merit factor is improved. To make this possible the ISL metric is expressed in the frequency domain and minimized to its most recent values and fixing at their most recent value until the predefined threshold satisfied. Because of FFT operations, the Cyclic Algorithm New applied to very long length sequences say N~106. In this paper, the Merit factor and correlation levels compared with standard, and cyclic algorithm new initialized with Polyphase sequences for lengths 102~104. Moreover, the observations made for four consecutive even and odd integer lengths say 162, 172, 182, and 192. CAN (P3, Golomb) exhibits merit factor improvement of 3.77%. These sequences of sidelobe levels reduced.
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Dookie, Isa, Sean Rocke, Arvind Singh, and Craig J. Ramlal. "Evaluating wind speed probability distribution models with a novel goodness of fit metric: a Trinidad and Tobago case study." International Journal of Energy and Environmental Engineering 9, no. 3 (May 17, 2018): 323–39. http://dx.doi.org/10.1007/s40095-018-0271-y.
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Dawson, C. W., N. J. Mount, R. J. Abrahart, and J. Louis. "Sensitivity analysis for comparison, validation and physical legitimacy of neural network-based hydrological models." Journal of Hydroinformatics 16, no. 2 (July 16, 2013): 407–24. http://dx.doi.org/10.2166/hydro.2013.222.
Повний текст джерелаАнотація:
This paper addresses the difficult question of how to perform meaningful comparisons between neural network-based hydrological models and alternative modelling approaches. Standard, goodness-of-fit metric approaches are limited since they only assess numerical performance and not physical legitimacy of the means by which output is achieved. Consequently, the potential for general application or catchment transfer of such models is seldom understood. This paper presents a partial derivative, relative sensitivity analysis method as a consistent means by which the physical legitimacy of models can be evaluated. It is used to compare the behaviour and physical rationality of a generalised linear model and two neural network models for predicting median flood magnitude in rural catchments. The different models perform similarly in terms of goodness-of-fit statistics, but behave quite distinctly when the relative sensitivities of their inputs are evaluated. The neural solutions are seen to offer an encouraging degree of physical legitimacy in their behaviour, over that of a generalised linear modelling counterpart, particularly when overfitting is constrained. This indicates that neural models offer preferable solutions for transfer into ungauged catchments. Thus, the importance of understanding both model performance and physical legitimacy when comparing neural models with alternative modelling approaches is demonstrated.
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Vangipuram, Gautam, Aaron Y. Lee, Kasra A. Rezaei, Lisa C. Olmos De Koo, Yewlin E. Chee, Jennifer R. Chao, Catherine Egan, and Cecilia S. Lee. "CAPTCHA as a Visual Performance Metric in Active Macular Disease." Journal of Ophthalmology 2019 (June 9, 2019): 1–6. http://dx.doi.org/10.1155/2019/6710754.
Повний текст джерелаАнотація:
Purpose. CAPTCHA (completely automated public turing test to tell computers and humans apart) was designed as a spam prevention test. In patients with visual impairment, completion of this task has been assumed to be difficult; but to date, no study has proven this to be true. As visual function is not well measured by Snellen visual acuity (VA) alone, we theorized that CAPTCHA performance may provide additional information on macular disease-related visual dysfunction. Methods. This was designed as a pilot study. Active disease was defined as the presence of either intraretinal fluid (IRF) or subretinal fluid (SRF) on spectral-domain optical coherence tomography. CAPTCHA performance was tested using 10 prompts. In addition, near and distance VA, contrast sensitivity, and reading speed were measured. Visual acuity matched pseudophakic patients were used as controls. Primary outcome measures were average edit distance and percent of correct responses. Results. 70 patients were recruited: 33 with active macular disease and 37 control subjects. Contrast sensitivity was found to be significantly different in both the IRF (p<0.01) and SRF groups (p<0.01). No significant difference was found comparing the odds ratio of average edit distance of active disease (IRF, SRF) vs. control (OR 1.09 (0.62, 1.90), 1.10 (0.58, 2.05), p=0.77, 0.77) or percent correct responses of active disease vs. control (OR 0.98 (0.96, 1.01), 1.09 (0.58, 2.05), p=0.22,0.51) in CAPTCHA testing. The goodness of fit using logistic regression analysis for the dependent variables of either IRF or SRF did not improve accounting for average edit distance (p=0.49, p=0.27) or percent correct (p=0.89, p=0.61). Conclusions. Distance VA and contrast sensitivity are positively correlated with the presence of IRF and SRF in active macular disease. CAPTCHA performance did not appear to be a significant predictor of either IRF or SRF in our pilot study.
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Fahad, Muhammad, Arsalan Shahid, Ravi Reddy Manumachu, and Alexey Lastovetsky. "A Novel Statistical Learning-Based Methodology for Measuring the Goodness of Energy Profiles of Applications Executing on Multicore Computing Platforms." Energies 13, no. 15 (August 1, 2020): 3944. http://dx.doi.org/10.3390/en13153944.
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Accurate energy profiles are essential to the optimization of parallel applications for energy through workload distribution. Since there are many model-based methods available for efficient construction of energy profiles, we need an approach to measure the goodness of the profiles compared with the ground-truth profile, which is usually built by a time-consuming but reliable method. Correlation coefficient and relative error are two such popular statistical approaches, but they assume that profiles be linear or at least very smooth functions of workload size. This assumption does not hold true in the multicore era. Due to the complex shapes of energy profiles of applications on modern multicore platforms, the statistical methods can often rank inaccurate energy profiles higher than more accurate ones and employing such profiles in the energy optimization loop of an application leads to significant energy losses (up to 54% in our case). In this work, we present the first method specifically designed for goodness measurement of energy profiles. First, it analyses the underlying energy consumption trend of each energy profile and removes the profiles that exhibit a trend different from that of the ground truth. Then, it ranks the remaining energy profiles using the Euclidean distances as a metric. We demonstrate that the proposed method is more accurate than the statistical approaches and can save a significant amount of energy.
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Prince, Jon B. "The Integration of Stimulus Dimensions in the Perception of Music." Quarterly Journal of Experimental Psychology 64, no. 11 (November 2011): 2125–52. http://dx.doi.org/10.1080/17470218.2011.573080.
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A central aim of cognitive psychology is to explain how we integrate stimulus dimensions into a unified percept, but how the dimensions of pitch and time combine in the perception of music remains a largely unresolved issue. The goal of this study was to test the effect of varying the degree of conformity to dimensional structure in pitch and time (specifically, tonality and metre) on goodness ratings and classifications of melodies. The pitches and durations of melodies were either presented in their original order, as a reordered sequence, or replaced with random elements. Musically trained and untrained participants (24 each) rated melodic goodness, attending selectively to the dimensions of pitch, time, or both. Also, 24 trained participants classified whether or not the melodies were tonal, metric, or both. Pitch and temporal manipulations always influenced responses, but participants successfully emphasized either dimension in accordance with instructions. Effects of pitch and time were mostly independent for selective attention conditions, but more interactive when evaluating both dimensions. When interactions occurred, the effect of either dimension increased as the other dimension conformed more to its original structure. Relative main effect sizes (| pitch η2 – time η2 |) predicted the strength of pitch–time interactions (pitch × time η2); interactions were stronger when main effect sizes were more evenly matched. These results have implications for dimensional integration in several domains. Relative main effect size could serve as an indicator of dimensional salience, such that interactions are more likely when dimensions are equally salient.
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Morales, Jose, Johannes Flacke, and Jaap Zevenbergen. "Modelling residential land values using geographic and geometric accessibility in Guatemala City." Environment and Planning B: Urban Analytics and City Science 46, no. 4 (August 25, 2017): 751–76. http://dx.doi.org/10.1177/2399808317726332.
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Location and accessibility are core concepts for land-value research. However, the perspective is still limited in their conceptual and methodological application to cities from the Global South. The objective of this research is to bridge concepts and definitions to comprehensively operationalize accessibility indicators and uncover its relation with residential land-values in Guatemala City. We developed a multivariate regression model using the following access metrics: (1) geographic-access indices that were computed using time-based analyses per transport mode; (2) geometric-access metrics estimated via Space Syntax at various spatial scales; (3) a proposed geometric via geographic-access metric computed as potential access to network centrality. A variable selection process allowed to assess the information contribution of each variable in building a parsimonious model. We assessed the model in the context of model variations that represent common approaches used in existing literature. Geographic access to the core business district has the highest impact on the land-values, followed by proximity to urban areas with high geometric-access, measured as geometric via geographic access. Geometric accessibility at neighbourhood and city-wide scales add spatialized information that contributes to a parsimonious model and reduces spatial dependence. The model yielded the highest goodness of fit and prediction accuracy compared with the model variations. We concluded that Guatemala City land-values follow a predominant monocentric structure. Additionally, potential access to vital urban areas as identified via Space Syntax denotes the presence of economic activities, or potential for such, which were not explicitly addressed through the geographic-access metrics. The results have limitations but pose methodological possibilities relevant for research and practice in similar Latin American cities.
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Młyński, Dariusz, Andrzej Wałęga, Andrea Petroselli, Flavia Tauro, and Marta Cebulska. "Estimating Maximum Daily Precipitation in the Upper Vistula Basin, Poland." Atmosphere 10, no. 2 (January 23, 2019): 43. http://dx.doi.org/10.3390/atmos10020043.
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The aim of this study was to determine the best probability distributions for calculating the maximum annual daily precipitation with the specific probability of exceedance (Pmaxp%). The novelty of this study lies in using the peak-weighted root mean square error (PWRMSE), the root mean square error (RMSE), and the coefficient of determination (R2) for assessing the fit of empirical and theoretical distributions. The input data included maximum daily precipitation records collected in the years 1971–2014 at 51 rainfall stations from the Upper Vistula Basin, Southern Poland. The value of Pmaxp% was determined based on the following probability distributions of random variables: Pearson’s type III (PIII), Weibull’s (W), log-normal, generalized extreme value (GEV), and Gumbel’s (G). Our outcomes showed a lack of significant trends in the observation series of the investigated random variables for a majority of the rainfall stations in the Upper Vistula Basin. We found that the peak-weighted root mean square error (PWRMSE) method, a commonly used metric for quality assessment of rainfall-runoff models, is useful for identifying the statistical distributions of the best fit. In fact, our findings demonstrated the consistency of this approach with the RMSE goodness-of-fit metrics. We also identified the GEV distribution as recommended for calculating the maximum daily precipitation with the specific probability of exceedance in the catchments of the Upper Vistula Basin.
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Cheng, Shi, Yuhui Shi, and Quande Qin. "Population Diversity of Particle Swarm Optimizer Solving Single and Multi-Objective Problems." International Journal of Swarm Intelligence Research 3, no. 4 (October 2012): 23–60. http://dx.doi.org/10.4018/jsir.2012100102.
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Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities: exploration of new possibilities and exploitation of old certainties. The exploration ability means that an algorithm can explore more search place to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals’ information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained. Another issue in multiobjective is the solution metric. Pareto domination is utilized to compare between two solutions, however, solutions are almost Pareto non-dominated for multi-objective problems with more than ten objectives. In this paper, the authors analyze the population diversity of particle swarm optimizer for solving both single objective and multiobjective problems. The population diversity of solutions is used to measure the goodness of a set of solutions. This metric may guide the search in problems with numerous objectives. Adaptive optimization algorithms can be designed through controlling the balance between exploration and exploitation.
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Babier, Aaron, Timothy C. Y. Chan, Taewoo Lee, Rafid Mahmood, and Daria Terekhov. "An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization." INFORMS Journal on Optimization 3, no. 2 (January 2021): 119–38. http://dx.doi.org/10.1287/ijoo.2019.0045.
Повний текст джерелаАнотація:
We develop a generalized inverse optimization framework for fitting the cost vector of a single linear optimization problem given multiple observed decisions. This setting is motivated by ensemble learning, where building consensus from base learners can yield better predictions. We unify several models in the inverse optimization literature under a single framework and derive assumption-free and exact solution methods for each one. We extend a goodness-of-fit metric previously introduced for the problem with a single observed decision to this new setting and demonstrate several important properties. Finally, we demonstrate our framework in a novel inverse optimization-driven procedure for automated radiation therapy treatment planning. Here, the inverse optimization model leverages an ensemble of dose predictions from different machine learning models to construct a consensus treatment plan that outperforms baseline methods. The consensus plan yields better trade-offs between the competing clinical criteria used for plan evaluation.
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Kafarov, Telman Emiralievich, and Rizvan Telmanovich Kafarov. "The religious factor in the response to the pandemic: the pros and cons." KANT 39, no. 2 (June 15, 2021): 185–91. http://dx.doi.org/10.24923/2222-243x.2021-39.33.
Повний текст джерелаАнотація:
The purpose of the study is to analyze some significant in the strategy and tactics of religious activity in the context of the pandemic. The positive aspects and some shortcomings of the work of religious communities to counteract the epidemic are revealed. It is shown that we are talking about a change in the social role of religion in modern conditions, when its organizations are moving away from narrow confessional activities in the space of churches, mosques and synagogues and are actively involved in public spheres of activity. The scientific novelty lies in the analysis of how the pandemic significantly changed the metric of action of many religious canons, including the postulates about the omnipotence, all-goodness and humanity of God. The article reveals some positions in the theory and practice of the religious life of Islam and Christianity, which are unjustified in the context of the coronavirus.
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Luis-Ruiz, Julio Manuel de, Javier Sedano-Cibrián, Raúl Pereda-García, Rubén Pérez-Álvarez, and Beatriz Malagón-Picón. "Optimization of Photogrammetric Flights with UAVs for the Metric Virtualization of Archaeological Sites. Application to Juliobriga (Cantabria, Spain)." Applied Sciences 11, no. 3 (January 28, 2021): 1204. http://dx.doi.org/10.3390/app11031204.
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Three-dimensional models are required to virtualize heritage sites. In recent years, different techniques that ease their generation have been consolidated, such as photogrammetry with Unmanned Aerial Vehicles (UAVs). Nonmetric cameras allow relatively inexpensive data collections. Traditional aerial photogrammetry has established methodologies, but there are not commonly used recommendations for the selection of parameters when working with UAV platforms. This research applies the Taguchi Design of Experiments Method, with four parameters (height of flight, forward and lateral overlaps, and inclination angle of the sensor) and three levels (L9 matrix and nine flights), to determine the set that offers the best metric goodness and, therefore, the most faithful model. The Roman civitas of Juliobriga (Cantabria, North of Spain) was selected for this experiment. The optimal flight results of the average signal-to-noise ratio analysis were height of 15 m, forward and lateral overlaps of 80%, and inclination of 0° (nadiral). This research also highlights the noticeable contribution of the inclination in the accuracy of the model with respect to the others, which is 16.4 times higher than that of the less relevant one (height of flight). This leads to propose avoiding inclination angle as a variable, and the sole development of nadiral flights to obtain accurate models.
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Wei, Jie. "On Markov Earth Mover's Distance." International Journal of Image and Graphics 14, no. 04 (October 2014): 1450016. http://dx.doi.org/10.1142/s0219467814500168.
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In statistics, pattern recognition and signal processing, it is of utmost importance to have an effective and efficient distance to measure the similarity between two distributions and sequences. In statistics this is referred to as goodness-of-fit problem. Two leading goodness of fit methods are chi-square and Kolmogorov–Smirnov distances. The strictly localized nature of these two measures hinders their practical utilities in patterns and signals where the sample size is usually small. In view of this problem Rubner and colleagues developed the earth mover's distance (EMD) to allow for cross-bin moves in evaluating the distance between two patterns, which find a broad spectrum of applications. EMD-L1 was later proposed to reduce the time complexity of EMD from super-cubic by one order of magnitude by exploiting the special L1 metric. EMD-hat was developed to turn the global EMD to a localized one by discarding long-distance earth movements. In this work, we introduce a Markov EMD (MEMD) by treating the source and destination nodes absolutely symmetrically. In MEMD, like hat-EMD, the earth is only moved locally as dictated by the degree d of neighborhood system. Nodes that cannot be matched locally is handled by dummy source and destination nodes. By use of this localized network structure, a greedy algorithm that is linear to the degree d and number of nodes is then developed to evaluate the MEMD. Empirical studies on the use of MEMD on deterministic and statistical synthetic sequences and SIFT-based image retrieval suggested encouraging performances.
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Anand, Adarsh, Ompal Singh, Richie Aggarwal, and Deepti Aggrawal. "Diffusion Modeling Based on Customer's Review and Product Satisfaction." International Journal of Technology Diffusion 7, no. 1 (January 2016): 20–31. http://dx.doi.org/10.4018/ijtd.2016010102.
Повний текст джерелаАнотація:
The purpose of this paper is to determine the internal/external factors that lead to fluctuation in marketplace. Before introducing new products in the market, organization needs proper understanding of the market which can be realized through sound mathematical modeling and scientific decision making tools. The objective is as follows: market size is determined by the number of customers a product is flanked by; therefore, it becomes critical to understand satisfaction of demanders as one of the metric for measuring performance of the product. In this paper, the authors have discussed how the adoption takes place in accordance with the market fluctuation. For this purpose, they have developed four different methodical frameworks to help the management to estimate sales due to varying behaviour of market (as per reviews about the product). Analysis and validation has been done on two different real life datasets. Weighted Criteria Value Approach (WCVA) has been applied to rank the models by using several goodness of fit collectively.
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Albertus, Mickael. "Raking-ratio empirical process with auxiliary information learning." ESAIM: Probability and Statistics 24 (2020): 435–53. http://dx.doi.org/10.1051/ps/2020017.
Повний текст джерелаАнотація:
The raking-ratio method is a statistical and computational method which adjusts the empirical measure to match the true probability of sets of a finite partition. The asymptotic behavior of the raking-ratio empirical process indexed by a class of functions is studied when the auxiliary information is given by estimates. These estimates are supposed to result from the learning of the probability of sets of partitions from another sample larger than the sample of the statistician, as in the case of two-stage sampling surveys. Under some metric entropy hypothesis and conditions on the size of the information source sample, the strong approximation of this process and in particular the weak convergence are established. Under these conditions, the asymptotic behavior of the new process is the same as the classical raking-ratio empirical process. Some possible statistical applications of these results are also given, like the strengthening of the Z-test and the chi-square goodness of fit test.
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Boker, Steven M. "A Measurement of the Adaptation of Color Vision to the Spectral Environment." Psychological Science 8, no. 2 (March 1997): 130–34. http://dx.doi.org/10.1111/j.1467-9280.1997.tb00695.x.
Повний текст джерелаАнотація:
An exploratory factor analysis of the reflectance spectral distributions of a sample of natural and man-made objects yields a factor pattern remarkably similar to psychophysical color-matching curves. The goodness-of-fit indices from a maximum likelihood confirmatory factor model with fixed factor loadings specified by empirical trichromatic color-matching data indicate that the human visual system performs near to an optimum value for an ideal trichromatic system composed of three linear components. An unconstrained four-factor maximum likelihood model fits significantly better than a three-factor unconstrained model, suggesting that a color metric is better represented in four dimensions than in a three-dimensional space. This fourth factor can be calculated as a nonlinear interaction term between the first three factors: thus, a trichromatic input is sufficient to compute a color space of four dimensions. The visual system may exploit this nonlinear dependency in the spectral environment in order to obtain a four-dimensional color space without the biological cost of a fourth color receptor.
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Chen, W., and C. Yuan. "A Probabilistic-Based Design Model for Achieving Flexibility in Design." Journal of Mechanical Design 121, no. 1 (March 1, 1999): 77–83. http://dx.doi.org/10.1115/1.2829433.
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In this paper we propose the use of a probabilistic-based design model as a basis for providing the flexibility in a design process that allows designs to be readily adapted to changing conditions. Our proposed approach can be used to develop a range of solutions that meet a ranged set of design requirements. Meanwhile, designers are allowed to specify the varying degree of desirability of a ranged set of design performance based on their preferences. The Design Preference Index (DPI) is introduced as a design metric to measure the goodness of flexible designs. Providing the foundation to our work are the probabilistic representations of design performance, the application of the robust design concept, and the utilization of the compromise Decision Support Problem (DSP) as a multiobjective decision model. A two-bar structural design is used as an example to demonstrate our approach. Our focus in this paper is on introducing the probabilistic-based design model and not on the results of the example problem, per se.
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Truong, W., V. Trinh, and TQ Khanh. "Circadian stimulus – A computation model with photometric and colorimetric quantities." Lighting Research & Technology 52, no. 6 (November 14, 2019): 751–62. http://dx.doi.org/10.1177/1477153519887423.
Повний текст джерелаАнотація:
The circadian stimulus is an important, validated and updated metric that describes the invisible influences of light on the human circadian system explicitly and scientifically. However, an absolute spectral power distribution must be supplied for its computation, which is only measurable by an expensive and complicated spectrometer. This paper proposes an alternative circadian stimulus computation model that is identified as the function CS(z, Ev) for white light sources based on the most common and simplest parameters of illuminance Ev in lux and the chromaticity coordinate z. These parameters are well known and widely used in both colour science and lighting technology. In order to prove the accuracy and availability of the model, an internal validation was performed with the adapted method repeating split data to check the goodness of the model fit. The fitted model achieved a maximum residual of 0.058 in the circadian stimulus quantity (R2 = 0.998). An external validation with the maximum residual of 0.030 (R2 = 0.999) provided stronger evidence for the usability of the model in applications.
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Fonseca-Pedrero, Eduardo, Serafín Lemos-Giráldez, Mercedes Paino, Marta Santarén-Rosell, Susana Sierra-Baigrie, and José Muñiz. "Reliability and Sources of Validity Evidence of the Oviedo Schizotypy Assessment Questionnaire-Abbreviated (ESQUIZO-Q-A)." Spanish journal of psychology 15, no. 2 (July 2012): 840–49. http://dx.doi.org/10.5209/rev_sjop.2012.v15.n2.38895.
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The main goal of this research was to examine the reliability and different sources of validity evidence of the Oviedo Schizotypy Assessment Questionnaire-Abbreviated (ESQUIZO-Q-A) in nonclinical adolescents. The final sample was made up of 1,455 participants, 705 males (48.5%), with a mean age of 15.92 years (SD = 1.18). The internal consistency of the subscales ranged from .62 to .75. The analysis of its internal structure yielded a three-dimensional solution based on the dimensions: Reality Distortion, Anhedonia, and Interpersonal Disorganization. Likewise, the goodness-of-fit indices derived from the Confirmatory Factor Analysis for the hypothesized three-factor model were adequate. The three dimensions of the ESQUIZO-Q-A were significantly correlated with the subscales of the Strengths and Difficulties Questionnaire. The ESQUIZO-Q is a brief and simple self-report with adequate psychometric properties for the assessment of schizotypal traits in nonclinical adolescent populations. Future research should continue to explore the metric quality of the ESQUIZO-Q-A (e.g., sensitivity and specificity) and incorporate the new advances in psychological and educational assessment such as Computerized Adaptive Testing.
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Kitali, Angela E., Emmanuel Kidando, Thobias Sando, Ren Moses, and Eren Erman Ozguven. "Evaluating Aging Pedestrian Crash Severity with Bayesian Complementary Log–Log Model for Improved Prediction Accuracy." Transportation Research Record: Journal of the Transportation Research Board 2659, no. 1 (January 2017): 155–63. http://dx.doi.org/10.3141/2659-17.
Повний текст джерелаАнотація:
Reliable prediction accuracy is an essential attribute for crash prediction models. Generally, more severe injury outcomes, such as fatalities, are rarer than less severe crashes, such as property damage only or minor injury crashes. The complementary log–log (cloglog) model, commonly used in epidemiological research, is known for its accuracy in predicting rare events. This study implemented the cloglog model in analyzing pedestrian injury severity and compared its performance with the two conventional models used in injury severity research: the probit and logit models. The three models were developed with data from 1,397 crashes involving aging pedestrians that occurred in Florida from 2009 through 2013. The response variable, injury severity level, was binary and categorized as either fatal or severe injury or minor or no injury. The study used three accuracy metrics (deviance information criteria, prediction accuracy, and receiver operating characteristics curves) to compare the performance of the models. The cloglog model outperformed the probit and logit models in overall goodness of fit and prediction accuracy. More important, the cloglog model outperformed the other two models considerably for predicting fatal and severe crashes according to the recall metric (72% accuracy versus 43% and 41% for probit and logit models, respectively). However, the other two models outperformed the cloglog model in predicting crashes with no or minor injuries. Of predictor variables included in the model, six were found to significantly influence fatal or severe injuries for aging pedestrians at 95% Bayesian credible interval. These variables included pedestrian age, alcohol involvement, first harmful event, vehicle movement, shoulder type, and posted speed.
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Villarini, Gabriele, and Gabriel A. Vecchi. "North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE): Statistical Modeling and Sensitivity to Sea Surface Temperature Changes." Journal of Climate 25, no. 2 (January 15, 2012): 625–37. http://dx.doi.org/10.1175/jcli-d-11-00146.1.
Повний текст джерелаАнотація:
Abstract This study focuses on the statistical modeling of the power dissipation index (PDI) and accumulated cyclone energy (ACE) for the North Atlantic basin over the period 1949–2008, which are metrics routinely used to assess tropical storm activity, and their sensitivity to sea surface temperature (SST) changes. To describe the variability exhibited by the data, four different statistical distributions are considered (gamma, Gumbel, lognormal, and Weibull), and tropical Atlantic and tropical mean SSTs are used as predictors. Model selection, both in terms of significant covariates and their functional relation to the parameters of the statistical distribution, is performed using two penalty criteria. Two different SST datasets are considered [the Met Office’s Global Sea Ice and Sea Surface Temperature dataset (HadISSTv1) and NOAA’s extended reconstructed SST dataset (ERSSTv3b)] to examine the sensitivity of the results to the input data. The statistical models presented in this study are able to well describe the variability in the observations according to several goodness-of-fit diagnostics. Both tropical Atlantic and tropical mean SSTs are significant predictors, independently of the SST input data, penalty criterion, and tropical storm activity metric. The application of these models to centennial reconstructions and seasonal forecasting is illustrated. The sensitivity of North Atlantic tropical cyclone frequency, duration, and intensity is examined for both uniform and nonuniform SST changes. Under uniform SST warming, these results indicate that there is a modest sensitivity of intensity, and a decrease in tropical storm and hurricane frequencies. On the other hand, increases in tropical Atlantic SST relative to the tropical mean SST suggest an increase in the intensity and frequency of North Atlantic tropical storms and hurricanes.