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Journal articles on the topic 'Spatial autoregressions, Hypothesis testing'

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1

Robinson, Peter M., and Francesca Rossi. "REFINED TESTS FOR SPATIAL CORRELATION." Econometric Theory 31, no. 6 (November 4, 2014): 1249–80. http://dx.doi.org/10.1017/s0266466614000498.

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We consider testing the null hypothesis of no spatial correlation against the alternative of pure first order spatial autoregression. A test statistic based on the least squares estimate has good first-order asymptotic properties, but these may not be relevant in small- or moderate-sized samples, especially as (depending on properties of the spatial weight matrix) the usual parametric rate of convergence may not be attained. We thus develop tests with more accurate size properties, by means of Edgeworth expansions and the bootstrap. Although the least squares estimate is inconsistent for the correlation parameter, we show that under quite general conditions its probability limit has the correct sign, and that least squares testing is consistent; we also establish asymptotic local power properties. The finite-sample performance of our tests is compared with others in Monte Carlo simulations.
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Cavaliere, Giuseppe, and Iliyan Georgiev. "EXPLOITING INFINITE VARIANCE THROUGH DUMMY VARIABLES IN NONSTATIONARY AUTOREGRESSIONS." Econometric Theory 29, no. 6 (August 13, 2013): 1162–95. http://dx.doi.org/10.1017/s0266466613000030.

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We consider estimation and testing in finite-order autoregressive models with a (near) unit root and infinite-variance innovations. We study the asymptotic properties of estimators obtained by dummying out “large” innovations, i.e., those exceeding a given threshold. These estimators reflect the common practice of dealing with large residuals by including impulse dummies in the estimated regression. Iterative versions of the dummy-variable estimator are also discussed. We provide conditions on the preliminary parameter estimator and on the threshold that ensure that (i) the dummy-based estimator is consistent at higher rates than the ordinary least squares estimator, (ii) an asymptotically normal test statistic for the unit root hypothesis can be derived, and (iii) order of magnitude gains of local power are obtained.
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Shen, Xiaotong, Hsin-Cheng Huang, and Noel Cressie. "Nonparametric Hypothesis Testing for a Spatial Signal." Journal of the American Statistical Association 97, no. 460 (December 2002): 1122–40. http://dx.doi.org/10.1198/016214502388618933.

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4

Schneider, Darryl W. "Alertness and cognitive control: Testing the spatial grouping hypothesis." Attention, Perception, & Psychophysics 81, no. 6 (May 23, 2019): 1913–25. http://dx.doi.org/10.3758/s13414-019-01764-x.

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5

Mur, Jesús, Fernando López, and Ana Angulo. "Testing the hypothesis of stability in spatial econometric models." Papers in Regional Science 88, no. 2 (June 2009): 409–44. http://dx.doi.org/10.1111/j.1435-5957.2009.00224.x.

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6

Nedimović, Predrag, and Sučica Zdravković. "Lightness contrast & assimilation: testing the hypotheses." Primenjena psihologija 14, no. 3 (November 17, 2021): 253–75. http://dx.doi.org/10.19090/pp.2021.3.253-275.

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Lightness contrast alters lightness of a target decreasing its similarity with neighbouring surfaces (inducers), while lightness assimilation has an opposite effect, similarity is increased. Previous studies emphasized some aspects of stimulation that favour occurrence of one or both of these two phenomena: spatial frequency of the inducers, magnitude and direction of the reflectance difference between the target and the inducers. More importantly, based on previous studies three precise hypotheses can be formulated that predict occurrence of the two phenomena: spatial frequency, differential stimulation and assimilation asymmetry. We manipulated target and inducers’ reflectance, and inducers’ spatial frequency. This enabled us not only to test the importance of these factors, but to predict lightness for each stimulus, according to all three hypotheses. Our results confirmed the importance of tested factors for both lightness contrast and assimilation. Unfortunately, the proposed hypotheses were poor in predicting the obtained data. Differential stimulation hypothesis correctly predicted obtained effect in less than half situations, since small reflectance differences produced contrast, and large differences produced assimilation. Spatial frequency hypothesis did not correctly predict the strength of obtained effects, and we obtained largest assimilation effects with low spatial frequency inducers. Finally, assimilation asymmetry hypothesis did not predict a single obtained effect. Contrary to this hypothesis predictions, we obtained contrast with decrement, and assimilation with increment inducers.
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7

Weidner, R., N. J. Shah, and G. R. Fink. "The Neural Basis of Perceptual Hypothesis Generation and Testing." Journal of Cognitive Neuroscience 18, no. 2 (February 1, 2006): 258–66. http://dx.doi.org/10.1162/jocn.2006.18.2.258.

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Four-dot masking is a new form of visual masking that does not involve local contour interactions or spatial superimposition of the target stimulus and the mask (as, e.g., in pattern or metacontrast masking). Rather, the effective masking mechanism is based on object substitution. Object substitution masking occurs when low-level visual information representations are altered before target identification through iterative interaction with high-level visual processing stages has been completed. Interestingly, object substitution interacts with attention processes: Strong masking effects are observed when attentional orientation toward the target location is delayed. In contrast, no masking occurs when attention can be rapidly shifted to and engaged onto the target location. We investigated the neural basis of object substitution masking by studying the interaction of spatial attention and masking processes using functional magnetic resonance imaging. Behavioral data indicated a two-way interaction between the factors Spatial Attention (valid vs. invalid cueing) and Masking (four-dot vs. pattern masking). As expected, spatial attention improved performance more strongly during object substitution masking. Functional correlates of this interaction were found in the primary visual cortex, higher visual areas, and left intraparietal sulcus. A region-of-interest analysis in these areas revealed that the largest blood oxygenation level-dependent signal changes occurred during effective four-dot masking. In contrast, the weakest signal changes in these areas were observed when target visibility was highest. The data suggest that these areas represent an object substitution network dedicated to the generation and testing of a perceptual hypotheses as described by the object substitution theory of masking of Di-Lollo et al. [Competition for consciousness among visual events: The psychophysics of reentrant visual processes. Journal of Experimental Psychology: General, 129, 481–507, 2000].
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8

Meilán-Vila, Andrea, Jean Opsomer, Mario Francisco-Fernández, and Rosa Crujeiras. "Testing Goodness-of-Fit of Parametric Spatial Trends." Proceedings 2, no. 18 (September 17, 2018): 1185. http://dx.doi.org/10.3390/proceedings2181185.

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The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametric trend surface, that is, a regression model with spatially correlated errors. The asymptotic behavior under the null hypothesis, as well as the asymptotic power of the test under local alternatives will be analyzed. Finite sample performance of the test is addressed by simulation, introducing a bootstrap calibration procedure.
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9

Muelenz, Cornelius, Matthias Gamer, and Heiko Hecht. "Testing the Egocentric Mirror-Rotation Hypothesis." Seeing and Perceiving 23, no. 5 (2010): 373–83. http://dx.doi.org/10.1163/187847510x540000.

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AbstractAlthough observers know about the law of reflection, their intuitive understanding of spatial locations in mirrors is often erroneous. Hecht et al. (2005) proposed a two-stage mirror-rotation hypothesis to explain these misconceptions. The hypothesis involves an egocentric bias to the effect that observers behave as if the mirror surface were rotated by about 2° to be more orthogonal than is the case. We test four variants of the hypothesis, which differ depending on whether the virtual world, the mirror, or both are taken to be rotated. We devised an experimental setup that allowed us to distinguish between these variants. Our results confirm that the virtual world — and only the virtual world — is being rotated. Observers had to perform a localization task, using a mirror that was either fronto-parallel or rotated opposite the direction of the predicted effect. We were thus able to compensate for the effect. The positions of objects in mirrors were perceived in accordance with the erroneous conception that the virtual world behind the mirror is slightly rotated and that the reconstruction is based on the non-rotated fronto-parallel mirror. A covert rotation of the mirror by about 2° against the predicted effect was able to compensate for the placement error.
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10

Guarte, Jacqueline, and Erniel Barrios. "Nonparametric Hypothesis Testing in a Spatial-Temporal Model: A Simulation Study." Communications in Statistics - Simulation and Computation 42, no. 1 (January 2013): 153–70. http://dx.doi.org/10.1080/03610918.2011.633725.

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11

Vesno, Yen, Ahmad Soleh, and Sri Handayani. "The Effect of Remuneration and Job Satisfaction on Employee Performance in Public Works and Spatial Planning Agency (PUPR) of Seluma Regency." Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan 2, no. 4 (October 16, 2021): 389–96. http://dx.doi.org/10.53697/emak.v2i4.183.

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The aim of this study is to determine the effect of remuneration and job satisfaction on employee performance at Public Works and Spatial Planning Agency (PUPR) of Seluma Regency.The sample in this study were all employees at the Public Works and Spatial Planning Agency (PUPR) of Seluma Regency who had become State Civil Servants (ASN) as many as 52 people. The sampling method is by means of a census. The data collectiontechnique by means of a questionnaire. The analytical method used is multiple regression analysis, hypothesis testing t and hypothesis testing f.The regression equation results are Y = 6.045 + 0.419X1 + 0.458 X2 with a positive regression direction, meaning that if there is an increase in remuneration and job satisfaction, the performance will also increase. Remuneration has a significant effect on employee performance at Public Works and Spatial Planning Agency (PUPR) of Seluma Regency. This is evidenced by the results of partial hypothesis testing (t test) that the significant value of 0.000 is smaller than 0.05. This means that if the remuneration increases, the employee performance will also increase. Job satisfaction has a significant effect on employee performance at Public Works and Spatial Planning Agency (PUPR) of Seluma Regency. This is evidenced by the results of partial hypothesis testing (t test) that the significant value of 0.000 is smaller than 0.05. This means that if organizational commitment increases, employee performance will also increase. Remuneration and job satisfaction have a significant effect together on the employees performance at Public Works and Spatial Planning Agency (PUPR) of Seluma Regency. This is evidenced by the results of simultaneous hypothesis testing (f test) that the significant value is 0.000 less than 0.05.
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12

Weinberg, Bruce A. "Testing the spatial mismatch hypothesis using inter-city variations in industrial composition." Regional Science and Urban Economics 34, no. 5 (September 2004): 505–32. http://dx.doi.org/10.1016/s0166-0462(03)00072-3.

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13

Chan, Kwun Chuen Gary, Jinhui Han, Adrian Patrick Kennedy, and Sheung Chi Phillip Yam. "Testing network autocorrelation without replicates." PLOS ONE 17, no. 11 (November 3, 2022): e0275532. http://dx.doi.org/10.1371/journal.pone.0275532.

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In this paper, we propose a portmanteau test for whether a graph-structured network dataset without replicates exhibits autocorrelation across units connected by edges. Specifically, the well known Ljung-Box test for serial autocorrelation of time series data is generalized to the network setting using a specially derived central limit theorem for a weakly stationary random field. The asymptotic distribution of the test statistic under the null hypothesis of no autocorrelation is shown to be chi-squared, yielding a simple and easy-to-implement procedure for testing graph-structured autocorrelation, including spatial and spatial-temporal autocorrelation as special cases. Numerical simulations are carried out to demonstrate and confirm the derived asymptotic results. Convergence is found to occur quickly depending on the number of lags included in the test statistic, and a significant increase in statistical power is also observed relative to some recently proposed permutation tests. An example application is presented by fitting spatial autoregressive models to the distribution of COVID-19 cases across counties in New York state.
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14

Makeienko, Maryna. "Symbolic Analysis Applied to the Specification of Spatial Trends and Spatial Dependence." Entropy 22, no. 4 (April 20, 2020): 466. http://dx.doi.org/10.3390/e22040466.

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This article provides symbolic analysis tools for specifying spatial econometric models. It firstly considers testing spatial dependence in the presence of potential leading deterministic spatial components (similar to time-series tests for unit roots in the presence of temporal drift and/or time-trend) and secondly considers how to econometrically model spatial economic relations that might contain unobserved spatial structure of unknown form. Hypothesis testing is conducted with a symbolic-entropy based non-parametric statistical procedure, recently proposed by Garcia-Cordoba, Matilla-Garcia, and Ruiz (2019), which does not rely on prior weight matrices assumptions. It is shown that the use of geographically restricted semiparametric spatial models is a promising modeling strategy for cross-sectional datasets that are compatible with some types of spatial dependence. The results state that models that merely incorporate space coordinates might be sufficient to capture space dependence. Hedonic models for Baltimore, Boston, and Toledo housing prices datasets are revisited, studied (with the new proposed procedures), and compared with standard spatial econometric methodologies.
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15

Sifriyani, Sifriyani. "Simultaneous Hypothesis Testing of Multivariable Nonparametric Spline Regression in the GWR Model." International Journal of Statistics and Probability 8, no. 4 (June 25, 2019): 32. http://dx.doi.org/10.5539/ijsp.v8n4p32.

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In this research, studied multivariable nonparametric geographically weighted regression use truncated spline approach. The model is an expansion of nonparametric truncated spline regression that takes into account geographical or spatial factors. The purpose of this study was to find statistics test and distribution for the simultaneous hypothesis test. This study obtains the statistic test used the maximum likelihood ratio test (MLRT) method. Results of the research obtained statistics test based on the ratio between the maximum of the likelihood function under the set of H_0  and the maximum of the set likelihood function below the population with each have a spatial factor. Distribution of statistical tests has been proven to have a distribution of F. The modeling application used the percentage of the death of Dengue Hemorrhagic Fever (DHF) in 38 districts/cities in East Java Province. The modeling resulted in the determination coefficient of 80.7% and SSE value that is 0.0043.
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16

Wasani, Desy, Purhadi, and Sutikno. "Parameter estimation and hypothesis testing of geographically and temporally weighted bivariate Gamma regression model." IOP Conference Series: Earth and Environmental Science 880, no. 1 (October 1, 2021): 012044. http://dx.doi.org/10.1088/1755-1315/880/1/012044.

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Abstract Geographically Weighted Regression (GWR) study potential relationships in regression models that distinguish geographic spaces using non-stationary parameters to overcome spatial effects. The use of gamma regression, namely regression with the dependent variable with a gamma distribution, can be an alternative if the data do not follow a normal distribution. Gamma distribution is a continuous set of non-negative values, generally skewed to the right or positive skewness. Gamma regression is developed to be Bivariate Gamma Regression (BGR) when there are two dependent variables with gamma distribution. If the observation units are location points, spatial effects may occur. The Geographically Weighted Bivariate Gamma Regression (GWBGR) model can be a solution for spatial heterogeneity. However, during its development, many cases require information from panel data. Using panel data can provide complete information because it covers several periods, but it allows for temporal effects. This study developed a Geographically and Temporally Weighted Bivariate Gamma Regression (GTWBGR) model to handle spatial and temporal heterogeneity simultaneously. The estimation of the GTWBGR model parameters uses the Maximum Likelihood Estimation (MLE) method that followed by the numerical iteration of Berndt Hall Hall Hausman (BHHH). The simultaneous testing uses the Maximum Likelihood Ratio Test (MLRT) method to get a test statistic. With a large sample size, the distribution of the test statistic approaches chi-square. Meanwhile, partial testing uses the Z test statistic.
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17

Loomis, Jack M., Roberta L. Klatzky, Brendan McHugh, and Nicholas A. Giudice. "Spatial working memory for locations specified by vision and audition: Testing the amodality hypothesis." Attention, Perception, & Psychophysics 74, no. 6 (May 3, 2012): 1260–67. http://dx.doi.org/10.3758/s13414-012-0311-2.

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18

Simpson, Mark R., and Stephen J. Walsh. "Changes in the spatial structure of Grand Bank yellowtail flounder: testing MacCall's basin hypothesis." Journal of Sea Research 51, no. 3-4 (May 2004): 199–210. http://dx.doi.org/10.1016/j.seares.2003.08.007.

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19

Li, Zhengzhou, Lei Qi, Wenyan Li, Gang Jin, and Ming Wei. "Track Initiation for Dim Small Moving Infrared Target Based on Spatial-Temporal Hypothesis Testing." Journal of Infrared, Millimeter, and Terahertz Waves 30, no. 5 (February 13, 2009): 513–25. http://dx.doi.org/10.1007/s10762-008-9459-1.

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20

Fan, Yong, Guangming Yu, and Zongyi He. "Origin, spatial pattern, and evolution of urban system: Testing a hypothesis of “urban tree”." Habitat International 59 (January 2017): 60–70. http://dx.doi.org/10.1016/j.habitatint.2016.11.012.

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21

Caldeira, Ana Maria, and Elisabeth Kastenholz. "Tourists’ spatial behaviour in urban destinations." Journal of Vacation Marketing 24, no. 3 (May 22, 2017): 247–60. http://dx.doi.org/10.1177/1356766717706102.

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Tourism implies movement. This study tests the effect of past experience on tourists’ spatiotemporal behaviour in the context of urban multi-attraction visitation. Differences between first-time and repeat visitors are examined using global positioning systems technology and a post-visit survey of tourists staying at 10 different hotels in Lisbon. The impact of prior destination experience is assessed regarding intra-destination movements as well as multi-attraction visitation patterns, within a systematic framework in order to assess tourists’ intra-destination spatiotemporal behaviour. Hypothesis testing confirmed destination familiarity as an influential factor of urban tourists’ behaviour in space and time.
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Alba-Fernández, M., and Francisco Ariza-López. "A Homogeneity Test for Comparing Gridded-Spatial-Point Patterns of Human Caused Fires." Forests 9, no. 8 (July 27, 2018): 454. http://dx.doi.org/10.3390/f9080454.

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The statistical evaluation of the spatial similarity of human caused fire patterns is an important issue for wildland fire analysis. This paper proposes a method based on observed data and on a statistical tool (homogeneity test) that is based on non-explicit spatial distribution hypothesis for the human caused fire events. If a tessellation coming from a space filling curve is superimposed on the spatial point patterns, and a linearization mechanism applied, the statistical problem of testing the similarity between the spatial point patterns is equivalent to the one of testing the homogeneity between the two multinomial distributions obtained by modeling the proportions of cases on each cell of the tessellation. This way of comparing spatial point patterns is free of any hypothesis on any spatial point process. Because data are spatially over-dispersed, the existence of many cells of the grid without any count is a problem for classical statistical homogeneity tests. Our work overcomes this problem by applying specific test statistics based on the square Hellinger distance. Simulations and actual data are used in order to tune the process and to demonstrate the capabilities of the proposal. Results indicate that a new and robust method for comparing spatial point patterns of human caused fires is available.
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23

Purwanti, Setyorini Indah, Sutikno, and Purhadi. "Parameter estimation and hypothesis testing of geographically and temporally weighted bivariate generalized Poisson regression." IOP Conference Series: Earth and Environmental Science 880, no. 1 (October 1, 2021): 012043. http://dx.doi.org/10.1088/1755-1315/880/1/012043.

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Abstract Poisson regression is used to model the data with the response variable in the form of count data. This modeling must meet the equidispersion assumption. That is, the average value is the same as the variance. However, this assumption is often violated. Violation of the equidispersion assumption in Poisson regression modeling will result in invalid conclusions. These violations are an overdispersion and an underdispersion of the response variable. Generalized Poisson Regression (GPR) is an alternative if there is a violation of the equidispersion assumption. If there are two correlated response variables, modeling will use the Bivariate Generalized Poisson Regression (BGPR). However, in the panel data with the observation unit in the form of an area, BGPR is not quite right because there is spatial and temporal heterogeneity in the data. Geographically and Temporally Weighted Bivariate Generalized Poisson Regression (GTWBGPR) is a method for modeling spatial and temporal heterogeneity data. GTWBGPR is a development of GWBGPR. In GTWBGPR, besides accommodating spatial effects, it also accommodates temporal effects. This research will discuss the parameter estimation and test statistics for the GTWBGPR model. Parameter estimation uses Maximum Likelihood Estimation (MLE), but the result is not closed-form, so it is solved by numerical iteration. The numerical iteration used is Newton-Raphson. The test statistic for simultaneous testing uses the Maximum Likelihood Ratio Test (MLRT). With large samples, then this test statistic has a chi-square distribution approximation. So the test statistic for the partial test uses the Z test statistic.
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Doran, Justin, and Bernard Fingleton. "US Metropolitan Area Resilience: Insights from dynamic spatial panel estimation." Environment and Planning A: Economy and Space 50, no. 1 (October 12, 2017): 111–32. http://dx.doi.org/10.1177/0308518x17736067.

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In this paper, we show that the economic crisis commencing in 2007 had different impacts across US Metropolitan Statistical Areas, and seek to understand why differences occurred. The hypothesis of interest is that differences in industrial structure are a cause of variations in response to the crisis. Our approach uses a state-of-the art dynamic spatial panel model to obtain counterfactual predictions of Metropolitan Statistical Area employment levels from 2008 to 2014. The counterfactual employment series are compared with actual employment paths in order to obtain Metropolitan Statistical Area-specific measures of crisis impact, which then are analysed with a view to testing the hypothesis that resilience to the crisis was dependent on Metropolitan Statistical Area industrial structure.
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Corinaldesi, C., E. Crevatin, P. Del Negro, M. Marini, A. Russo, S. Fonda-Umani, and R. Danovaro. "Large-Scale Spatial Distribution of Virioplankton in the Adriatic Sea: Testing the Trophic State Control Hypothesis." Applied and Environmental Microbiology 69, no. 5 (May 2003): 2664–73. http://dx.doi.org/10.1128/aem.69.5.2664-2673.2003.

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ABSTRACT Little is known concerning environmental factors that may control the distribution of virioplankton on large spatial scales. In previous studies workers reported high viral levels in eutrophic systems and suggested that the trophic state is a possible driving force controlling the spatial distribution of viruses. In order to test this hypothesis, we determined the distribution of viral abundance and bacterial abundance and the virus-to-bacterium ratio in a wide area covering the entire Adriatic basin (Mediterranean Sea). To gather additional information on factors controlling viral distribution on a large scale, functional microbial parameters (exoenzymatic activities, bacterial production and turnover) were related to trophic gradients. At large spatial scales, viral distribution was independent of autotrophic biomass and all other environmental parameters. We concluded that in contrast to what was previously hypothesized, changing trophic conditions do not directly affect virioplankton distribution. Since virus distribution was coupled with bacterial turnover times, our results suggest that viral abundance depends on bacterial activity and on host cell abundance.
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Marcon, Eric, Stéphane Traissac, and Gabriel Lang. "A Statistical Test for Ripley’s K Function Rejection of Poisson Null Hypothesis." ISRN Ecology 2013 (April 14, 2013): 1–9. http://dx.doi.org/10.1155/2013/753475.

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Ripley’s K function is the classical tool to characterize the spatial structure of point patterns. It is widely used in vegetation studies. Testing its values against a null hypothesis usually relies on Monte-Carlo simulations since little is known about its distribution. We introduce a statistical test against complete spatial randomness (CSR). The test returns the P value to reject the null hypothesis of independence between point locations. It is more rigorous and faster than classical Monte-Carlo simulations. We show how to apply it to a tropical forest plot. The necessary R code is provided.
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Huse, Geir. "A spatial approach to understanding herring population dynamics." Canadian Journal of Fisheries and Aquatic Sciences 73, no. 2 (February 2016): 177–88. http://dx.doi.org/10.1139/cjfas-2015-0095.

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Johan Hjort’s so-called second recruitment hypothesis addressed the fate of offspring that drift out of areas suitable for their survival. This hypothesis has forged the concept of a population as a closed life cycle, making countercurrent adult spawning migration a necessary mechanism in balancing larval drift. The Norwegian spring-spawning (NSS) herring stock (Clupea harengus), the object of much of Hjort’s work, is spread over large areas in the Northeast Atlantic, with spawning along the Norwegian coast, nursery areas in the Barents Sea, feeding areas in the Norwegian Sea, and overwintering areas outside northern Norway. Understanding the spatial dynamics of highly migratory fish stocks such as the NSS herring, therefore, is critical to understanding their population dynamics. Here I review hypotheses on the spatial dynamics of fish focusing on NSS herring and discuss consequences for population dynamics and interactions with other ecosystem components. The results illustrate the key role that strong herring cohorts play both as predators in the Barents and Norwegian seas and as prey on the overwintering and spawning grounds along the Norwegian coast. It is advocated that spatial full life cycle models should be developed for key fish stocks as a meeting place for model assumptions and observations and as a test bed for a multiple hypothesis testing approach.
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Cellmer, Radosław. "USE OF SPATIAL AUTOCORRELATION TO BUILD REGRESSION MODELS OF TRANSACTION PRICES." Real Estate Management and Valuation 21, no. 4 (December 1, 2013): 65–74. http://dx.doi.org/10.2478/remav-2013-0038.

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Abstract This paper presents the principles of studying global spatial autocorrelation in the land property market, as well as the possibilities of using these regularities for the construction of spatial regression models. Research work consisted primarily of testing the structure of the spatial weights matrix using different criteria and conducting diagnostic tests of two types of models: the spatial error model and the spatial lag model. The paper formulates the hypothesis that the application of spatial regression models greatly increases the accuracy of transaction price prediction while forming the basis for the creation of cartographic documents including, among others, maps of land value.
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van Anders, Sari M., and Elizabeth Hampson. "Testing the prenatal androgen hypothesis: measuring digit ratios, sexual orientation, and spatial abilities in adults." Hormones and Behavior 47, no. 1 (January 2005): 92–98. http://dx.doi.org/10.1016/j.yhbeh.2004.09.003.

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Wang, Hong, Eulogio Pardo-Igúzquiza, Peter A. Dowd, and Yongguo Yang. "Comparison of statistical methods for testing the hypothesis of constant global mean in spatial statistics." Spatial Statistics 23 (March 2018): 143–59. http://dx.doi.org/10.1016/j.spasta.2018.01.001.

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HA, NGUYEN MINH, BUI HOANG NGOC, and MICHAEL MCALEER. "FINANCIAL INTEGRATION, ENERGY CONSUMPTION AND ECONOMIC GROWTH IN VIETNAM." Annals of Financial Economics 15, no. 03 (September 2020): 2050010. http://dx.doi.org/10.1142/s2010495220500104.

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The paper investigates the impact of financial integration and energy consumption on economic growth in Vietnam during the period 1986–2017. By applying the Autoregressive Distributed Lag ARDL) approach proposed by Pesaran et al. [Pesaran, MH, Y Shin and RJ Smith (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326.] and the bounds cointegration test, the empirical results show the existence of long-term cointegration among all the variables, and that an increase in financial integration leads to an increase in economic growth in the long run. There is a positive impact of energy consumption on growth in both the short run and long run. The causality test of Toda and Yamamoto [Toda, HY and T Yamamoto (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250.] confirm that there is bi-directional causality between the pairs, financial integration and economic growth, and energy consumption and growth, which support the feedback hypothesis. However, there is only uni-directional causality from energy consumption to financial integration. The empirical results should be of major empirical importance for public policy decision-makers to plan sustainable development goals for Vietnam.
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32

Chiasson, Paul, Jean Lafleur, Michel Soulié, and K. Tim Law. "Characterizing spatial variability of a clay by geostatistics." Canadian Geotechnical Journal 32, no. 1 (February 1, 1995): 1–10. http://dx.doi.org/10.1139/t95-001.

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This paper presents a characterization of the variability of a lightly overconsolidated and highly sensitive clay deposit located near Saint-Hilaire, 50 km east of Montréal. The geotechnical investigation consisted of in situ and laboratory tests. The variability of the in situ test results is the subject of this paper. The working hypothesis assumes that piezocone and vane test results may be modelled by a random function. This is done on the basis of a geostatistical approach. In situ vane and piezocone tests are found to increase with depth following a linear trend. This is a nonstationary problem and inference of the autocorrelation function must be made through the estimation of a generalized covariance. Results for both types of tests give the same shape of generalized covariance. Measurements made with both testing devices yield the same 2 m autocorrelation distance but the standard deviations are different. The standard deviations for the piezocone cone resistance, pore pressure behind the cone tip, and sleeve friction are 74, 34, and 2.1 kPa, respectively. Vane measurements have a standard deviation of 4.9 kPa. Results are also presented for the estimation of the vertical linear trend and for the statistical distributions of fluctuations. Key words : sensitive clay, spatial variability, stochastic representation, geostatistics, piezocone testing, vane testing.
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Anvari, Farid, and Davide Marchiori. "Priming exploration across domains: does search in a spatial environment influence search in a cognitive environment?" Royal Society Open Science 8, no. 8 (August 2021): 201944. http://dx.doi.org/10.1098/rsos.201944.

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Is there a general tendency to explore that connects search behaviour across different domains? Although the experimental evidence collected so far suggests an affirmative answer, this fundamental question about human behaviour remains open. A feasible way to test the domain-generality hypothesis is that of testing the so-called priming hypothesis: priming explorative behaviour in one domain should subsequently influence explorative behaviour in another domain. However, only a limited number of studies have experimentally tested this priming hypothesis, and the evidence is mixed. We tested the priming hypothesis in a registered report. We manipulated explorative behaviour in a spatial search task by randomly allocating people to search environments with resources that were either clustered together or dispersedly distributed. We hypothesized that, in a subsequent anagram task, participants who searched in clustered spatial environments would search for words in a more clustered way than participants who searched in the dispersed spatial environments. The pre-registered hypothesis was not supported. An equivalence test showed that the difference between conditions was smaller than the smallest effect size of interest ( d = 0.36). Out of several exploratory analyses, we found only one inferential result in favour of priming. We discuss implications of these findings for the theory and propose future tests of the hypothesis.
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Fathurahman, M., Purhadi, Sutikno, and Vita Ratnasari. "Geographically Weighted Multivariate Logistic Regression Model and Its Application." Abstract and Applied Analysis 2020 (August 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/8353481.

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This study investigates the geographically weighted multivariate logistic regression (GWMLR) model, parameter estimation, and hypothesis testing procedures. The GWMLR model is an extension to the multivariate logistic regression (MLR) model, which has dependent variables that follow a multinomial distribution along with parameters associated with the spatial weighting at each location in the study area. The parameter estimation was done using the maximum likelihood estimation and Newton-Raphson methods, and the maximum likelihood ratio test was used for hypothesis testing of the parameters. The performance of the GWMLR model was evaluated using a real dataset and it was found to perform better than the MLR model.
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35

Negrelli, C., L. Kraiselburd, S. Landau, and E. García-Berro. "Spatial variation of fundamental constants: Testing models with thermonuclear supernovae." International Journal of Modern Physics D 27, no. 09 (July 2018): 1850099. http://dx.doi.org/10.1142/s0218271818500992.

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Since Dirac stated his Large Number Hypothesis the space-time variation of fundamental constants has been an active subject of research. Here we analyze the possible spatial variation of two fundamental constants: the fine structure constant [Formula: see text] and the speed of light [Formula: see text]. We study the effects of such variations on the luminosity distance and on the peak luminosity of Type Ia supernovae (SNe Ia). For this, we consider the change of each fundamental constant separately and discuss a dipole model for its variation. Elaborating upon our previous work, we take into account the variation of the peak luminosity of Type Ia supernovae resulting from the variation of each of these fundamental constants. Furthermore, we also include the change of the energy release during the explosion, which was not studied before in the literature. We perform a statistical analysis to compare the predictions of the dipole model for [Formula: see text] and [Formula: see text] variation with the Union 2.1 and JLA compilations of SNe Ia. Allowing the nuisance parameters of the distance estimator [Formula: see text] and the cosmological density matter [Formula: see text] to vary. As a result of our analysis, we obtain a first estimate of the possible spatial variation of the speed of light [Formula: see text]. On the other hand, we find that there is no significant difference between the several phenomenological models studied here and the standard cosmological model, in which fundamental constants do not vary at all. Thus, we conclude that the actual set of data of Type Ia supernovae does not allow to verify the hypothetical spatial variation of fundamental constants.
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36

Tevie, Justin, Kristine M. Grimsrud, and Robert P. Berrens. "Testing the Environmental Kuznets Curve Hypothesis for Biodiversity Risk in the US: A Spatial Econometric Approach." Sustainability 3, no. 11 (November 16, 2011): 2182–99. http://dx.doi.org/10.3390/su3112182.

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37

Guan, Yongtao. "Bias-Corrected Variance Estimation and Hypothesis Testing for Spatial Point and Marked Point Processes Using Subsampling." Biometrics 67, no. 3 (December 6, 2010): 926–36. http://dx.doi.org/10.1111/j.1541-0420.2010.01517.x.

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38

Osmon, D. C., and Y. Suchy. "Regional functional magnetic resonance imaging activation in a spatial working memory task: An hypothesis testing approach." NeuroImage 3, no. 3 (June 1996): S237. http://dx.doi.org/10.1016/s1053-8119(96)80239-4.

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39

Ricotta, Carlo. "Random sampling does not exclude spatial dependence: The importance of neutral models for ecological hypothesis testing." Folia Geobotanica 42, no. 2 (June 2007): 153–60. http://dx.doi.org/10.1007/bf02893881.

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40

Huang, Yuan, Liping Wang, Xueying Wang, and Wei An. "Anti-clutter Gaussian Inverse Wishart PHD Filter for Extended Target Tracking." Sensors 19, no. 23 (November 23, 2019): 5140. http://dx.doi.org/10.3390/s19235140.

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The extended target Gaussian inverse Wishart probability hypothesis density (ET-GIW-PHD) filter overestimates the number of targets under high clutter density. The reason for this is that the source of measurements cannot be determined correctly if only the number of measurements is used. To address this problem, we proposed an anti-clutter filter with hypothesis testing, we take into account the number of measurements in cells, the target state and spatial distribution of clutter to decide whether the measurements in cell are clutter. Specifically, the hypothesis testing method is adopted to determine the origination of the measurements. Then, the likelihood functions of targets and clutter are deduced based on the information mentioned above, resulting in the likelihood ratio test statistic. Next, the likelihood ratio test statistic is proved to be subject to a chi-square distribution and a threshold corresponding to the confidence coefficient is introduced and the measurements below this threshold are considered as clutter. Then the correction step of ET-GIW-PHD is revised based on hypothesis testing results. Extensive experiments have demonstrated the significant performance improvement of our proposed method.
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41

Nilsen, Tine, Johannes P. Werner, Dmitry V. Divine, and Martin Rypdal. "Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory." Climate of the Past 14, no. 6 (June 29, 2018): 947–67. http://dx.doi.org/10.5194/cp-14-947-2018.

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Abstract. The skill of the state-of-the-art climate field reconstruction technique BARCAST (Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time) to reconstruct temperature with pronounced long-range memory (LRM) characteristics is tested. A novel technique for generating fields of target data has been developed and is used to provide ensembles of LRM stochastic processes with a prescribed spatial covariance structure. Based on different parameter setups, hypothesis testing in the spectral domain is used to investigate if the field and spatial mean reconstructions are consistent with either the fractional Gaussian noise (fGn) process null hypothesis used for generating the target data, or the autoregressive model of order 1 (AR(1)) process null hypothesis which is the assumed temporal evolution model for the reconstruction technique. The study reveals that the resulting field and spatial mean reconstructions are consistent with the fGn process hypothesis for some of the tested parameter configurations, while others are in better agreement with the AR(1) model. There are local differences in reconstruction skill and reconstructed scaling characteristics between individual grid cells, and the agreement with the fGn model is generally better for the spatial mean reconstruction than at individual locations. Our results demonstrate that the use of target data with a different spatiotemporal covariance structure than the BARCAST model assumption can lead to a potentially biased climate field reconstruction (CFR) and associated confidence intervals.
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42

Aggio, Daniel, Lee Smith, and Mark Hamer. "Early life cognitive function and health behaviours in late childhood: testing the neuroselection hypothesis." Journal of Epidemiology and Community Health 72, no. 1 (November 9, 2017): 41–46. http://dx.doi.org/10.1136/jech-2017-208896.

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BackgroundHigher cognitive function in childhood is associated with healthier behaviours and a reduced risk of chronic disease in adulthood, but it is unclear whether this selection of healthier behaviours occurs in childhood or later in life. The present study investigated how cognitive function at age 3–7 years was associated with health behaviours at age 11.MethodsVerbal, non-verbal and spatial abilities were assessed using the British Ability Scales at ages 3–7. At age 11, children reported how often they engaged in sport/physical activity, sedentary behaviours (eg, reading and games console usage), cigarette smoking and alcohol consumption. Logistic regression was used to estimate odds of engaging in health behaviours at age 11 according to early life cognition.ResultsA 1 SD increase in early childhood verbal ability was associated with reduced odds of attempting smoking in boys and girls (OR 0.69 (95% CI 0.57 to 0.84)) and reduced odds of computer gaming in girls (OR 0.79 (95% CI 0.72 to 0.86)) by age 11. Early childhood verbal ability was also associated with reduced odds of regular participation in sport/active games (boys: OR 0.91 (95% CI 0.84 to 0.99); girls: OR 0.81 (95% CI 0.74 to 0.88)) and increased odds of reading for enjoyment (boys: OR 1.47 (95% CI 1.35 to 1.60); girls: OR 1.48 (95% CI 1.36 to 1.62)) at age 11. Early childhood non-verbal ability was associated with reduced odds of alcohol consumption in boys and girls (OR 0.92 (95% CI 0.85 to 0.99)) and reduced odds of online messaging in boys (OR 0.89 (95% CI 0.81 to 0.98)) at age 11. Early childhood spatial ability was associated with reduced odds of participating in sport/active games in boys at age 11 (OR 0.88 (95% CI 0.82 to 0.95).ConclusionNeuroselection may occur during early childhood resulting in some, but not all, healthier behaviours by age 11.
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Luo, Qing, Daniel A. Griffith, and Huayi Wu. "On the Statistical Distribution of the Nonzero Spatial Autocorrelation Parameter in a Simultaneous Autoregressive Model." ISPRS International Journal of Geo-Information 7, no. 12 (December 12, 2018): 476. http://dx.doi.org/10.3390/ijgi7120476.

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This paper focuses on the spatial autocorrelation parameter ρ of the simultaneous autoregressive model, and furnishes its sampling distribution for nonzero values, for two regular square (rook and queen) tessellations as well as a hexagonal case with rook connectivity, using Monte Carlo simulation experiments with a large sample size. The regular square lattice directly relates to increasingly used, remotely sensed images, whereas the regular hexagonal configuration is frequently used in sampling and aggregation situations. Results suggest an asymptotic normal distribution for estimated ρ. More specifically, this paper posits functions between ρ and its variance for three adjacency structures, which makes hypothesis testing implementable and furnishes an easily-computed version of the asymptotic variance for ρ at zero for each configuration. In addition, it also presents three examples, where the first employed a simulated dataset for a zero spatial autocorrelation case, and the other two used two empirical datasets—of these, one is a census block dataset for Wuhan (with a Moran coefficient of 0.53, allowing a null hypothesis of, e.g., ρ=0.7) to illustrate a moderate spatial autocorrelation case, and the other is a remotely sensed image of the Yellow Mountain region, China (with a Moran coefficient of 0.91, allowing a null hypothesis of, e.g., ρ=0.95) to illustrate a high spatial autocorrelation case.
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Sifriyani, I. N. Budiantara, S. H. Kartiko, and Gunardi. "A New Method of Hypothesis Test for Truncated Spline Nonparametric Regression Influenced by Spatial Heterogeneity and Application." Abstract and Applied Analysis 2018 (September 12, 2018): 1–13. http://dx.doi.org/10.1155/2018/9769150.

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This study developed a new method of hypothesis testing of model conformity between truncated spline nonparametric regression influenced by spatial heterogeneity and truncated spline nonparametric regression. This hypothesis test aims to determine the most appropriate model used in the analysis of spatial data. The test statistic for model conformity hypothesis testing was constructed based on the likelihood ratio of the parameter set under H0 whose components consisted of parameters that were not influenced by the geographical factor and the set under the population parameter whose components consisted of parameters influenced by the geographical factor. We have proven the distribution of test statistics V and verified that each of the numerators and denominators in the statistic test V followed a distribution of χ2. Since there was a symmetric and idempotent matrix S, it could be proved that Y~TS Y~/σ2~χn-lm-12. Matrix Dui,vi was positive semidefinite and contained weighting matrix Wui,vi which had different values in every location; therefore matrix Dui,vi was not idempotent. If Y~TDui,viY~≥0 and Dui,vi was not idempotent and also Y~ was a N0,I distributed random vector, then there were constants k and r; hence Y~TDui,viY~~kχr2; therefore it was concluded that test statistic V followed an F distribution. The modeling is implemented to find factors that influence the unemployment rate in 38 areas in Java in Indonesia.
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Chi, Bowen, Jixian Zhang, Lijun Lu, Shucheng Yang, Guoman Huang, and Xu Gao. "A Reflection Symmetric Target Extraction Method Based on Hypothesis Testing for PolSAR Calibration." Remote Sensing 15, no. 5 (February 24, 2023): 1252. http://dx.doi.org/10.3390/rs15051252.

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Polarimetric calibration is indispensable to quantitatively apply and analyze the polarimetric synthetic aperture radar (PolSAR) image. At present, the polarimetric calibration methods relying on the assumption of reflection symmetry have been widely used, which need to extract the reference targets that meet the assumptions before calibration and then calculate the cross-pol channel imbalance and crosstalk errors. However, the distortion in the uncalibrated image will affect the calculation of polarization features, resulting in inaccurate target extraction results. Consequently, we proposed a reflection symmetric target extraction method that combines with spatial statistics information. The method first takes the initial extraction result based on the polarization power total Span and introduces the hypothesis testing to judge the homogeneous samples. Finally, we automatically calculate the threshold by the Otsu algorithm to achieve high-precision extraction of the reflection symmetric targets. Meanwhile, we carried out the polarimetric calibration experiments based on real C- and X-band airborne PolSAR data and conducted qualitative and quantitative evaluation and analysis of the experimental results. The studies demonstrated that, compared with classical approaches, the proposed approach further improved the accuracy of polarimetric calibration by extracting more accurate reference samples.
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Yuan, Jili, Xiaolei Lv, and Rui Li. "A Speckle Filtering Method Based on Hypothesis Testing for Time-Series SAR Images." Remote Sensing 10, no. 9 (August 30, 2018): 1383. http://dx.doi.org/10.3390/rs10091383.

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To improve the suppression effect for the speckle noise of synthetic aperture radar (SAR) images and the ability of spatiotemporal information preservation of the filtered image without losing the spatial resolution, a novel multitemporal filtering method based on hypothesis testing is proposed in this paper. A framework of a two-step similarity measure strategy is adopted to further enhance the filtering results. Firstly, bi-date analysis using a two-sample Kolmogorov-Smirnov (KS) test is conducted in step 1 to extract homogeneous patches for 3-D patch stacks generation. Subsequently, the similarity between patch stacks is compared by a sliding time-series likelihood ratio (STSLR) test algorithm in step 2, which utilizes the multi-dimensional data structure of the stacks to improve the accuracy of unchanged pixels detection. Finally, the filtered values are obtained by averaging the similar pixels in time-series. The experimental results and analysis of two multitemporal datasets acquired by TerraSAR-X show that the proposed method outperforms the other typical methods with regard to the overall filtering effect, especially in terms of the consistency between the filtered images and the original ones. Furthermore, the performance of the proposed method is also discussed by analyzing the results from step 1 and step 2.
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Cole, Jason C., Lisa A. Fasnacht-Hill, Scott K. Robinson, and Caroline Cordahi. "Differentiation of Fluid, Visual, and Simultaneous Cognitive Tasks." Psychological Reports 89, no. 3 (December 2001): 541–46. http://dx.doi.org/10.2466/pr0.2001.89.3.541.

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The constructs of fluid reasoning and spatial visualization (Horn, 1989) as well as the construct of simultaneous processing (Luria, 1966) have been tapped by various cognitive assessment batteries. In order to determine whether these constructs could be differentiated from one another, factor analyses of subtest scores from six cognitive tasks were conducted. Fluid reasoning, spatial visualization, and simultaneous processing emerged as separate factors in the analysis, supporting the hypothesis that these constructs can be differentiated in psychoeducational testing. These results extend the findings of a preliminary study which found factorial differentiation between fluid and simultaneous reasoning.
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48

Raine, Nigel E., D. Kim Rossmo, and Steven C. Le Comber. "Geographic profiling applied to testing models of bumble-bee foraging." Journal of The Royal Society Interface 6, no. 32 (July 29, 2008): 307–19. http://dx.doi.org/10.1098/rsif.2008.0242.

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Geographic profiling (GP) was originally developed as a statistical tool to help police forces prioritize lists of suspects in investigations of serial crimes. GP uses the location of related crime sites to make inferences about where the offender is most likely to live, and has been extremely successful in criminology. Here, we show how GP is applicable to experimental studies of animal foraging, using the bumble-bee Bombus terrestris . GP techniques enable us to simplify complex patterns of spatial data down to a small number of parameters (2–3) for rigorous hypothesis testing. Combining computer model simulations and experimental observation of foraging bumble-bees, we demonstrate that GP can be used to discriminate between foraging patterns resulting from (i) different hypothetical foraging algorithms and (ii) different food item (flower) densities. We also demonstrate that combining experimental and simulated data can be used to elucidate animal foraging strategies: specifically that the foraging patterns of real bumble-bees can be reliably discriminated from three out of nine hypothetical foraging algorithms. We suggest that experimental systems, like foraging bees, could be used to test and refine GP model predictions, and that GP offers a useful technique to analyse spatial animal behaviour data in both the laboratory and field.
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Pataky, Todd C., Michihiko Koseki, and Phillip G. Cox. "Probabilistic biomechanical finite element simulations: whole-model classical hypothesis testing based on upcrossing geometry." PeerJ Computer Science 2 (November 7, 2016): e96. http://dx.doi.org/10.7717/peerj-cs.96.

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Statistical analyses of biomechanical finite element (FE) simulations are frequently conducted on scalar metrics extracted from anatomically homologous regions, like maximum von Mises stresses from demarcated bone areas. The advantages of this approach are numerical tabulability and statistical simplicity, but disadvantages include region demarcation subjectivity, spatial resolution reduction, and results interpretation complexity when attempting to mentally map tabulated results to original anatomy. This study proposes a method which abandons the two aforementioned advantages to overcome these three limitations. The method is inspired by parametric random field theory (RFT), but instead uses a non-parametric analogue to RFT which permits flexible model-wide statistical analyses through non-parametrically constructed probability densities regarding volumetric upcrossing geometry. We illustrate method fundamentals using basic 1D and 2D models, then use a public model of hip cartilage compression to highlight how the concepts can extend to practical biomechanical modeling. The ultimate whole-volume results are easy to interpret, and for constant model geometry the method is simple to implement. Moreover, our analyses demonstrate that the method can yield biomechanical insights which are difficult to infer from single simulations or tabulated multi-simulation results. Generalizability to non-constant geometry including subject-specific anatomy is discussed.
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LAMMERING, BIRGER. "SLICES OF MULTIFRACTAL MEASURES AND APPLICATIONS TO RAINFALL DISTRIBUTIONS." Fractals 08, no. 04 (December 2000): 337–48. http://dx.doi.org/10.1142/s0218348x00000391.

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We discuss the relationship between the multifractal functions of a plane measure and those of slices or sections of the measure with a line. Motivated by recent mathematical ideas about the relationship between measures and their slices, we formulate the "slice hypothesis," and consider the theoretical limitations of this hypothesis. We compute the multifractal functions of several standard self-similar and self-affine measures and their slices to examine the validity of the slice hypothesis. We are particularly interested in using the slice hypothesis to estimate multifractal properties of spatial rainfall fields by analyzing rainfall data representing slices of rainfall fields. We consider how rainfall time series at a fixed site and slices of composite radar images can be used for this purpose, testing this on field data from a radar composite in the USA and on appropriate time series.
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