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Dissertations / Theses on the topic 'Parameter estimates'
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Munster, Drayton William. "Robust Parameter Inversion Using Stochastic Estimates." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/96399.
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For parameter inversion problems governed by systems of partial differential equations, such as those arising in Diffuse Optical Tomography (DOT), even the cost of repeated objective function evaluation can be overwhelming. Despite the linear (in the state variable) nature of the DOT problem, the nonlinear parameter inversion process is dominated by the computational burden of solving a large linear system for each source and frequency. To compute the Jacobian for use in Newton-type methods, an adjoint solve is required for each detector and frequency. When a three-dimensional tomography problem may have nearly 1,000 sources and detectors, the computational cost of an optimization routine is a large burden. While techniques from model order reduction can partially alleviate the computational cost, obtaining error bounds in parameter space is typically not feasible. In this work, we examine two different remedies based on stochastic estimates of the objective function.
In the first manuscript, we focus on maximizing the efficiency of using stochastic estimates by replacing our objective function with a surrogate objective function computed from a reduced order model (ROM). We use as few as a single sample to detect a misfit between the full-order and surrogate objective functions. Once a sufficiently large difference is detected, it is necessary to update the ROM to reduce the error. We propose a new technique for improving the ROM with very few large linear solutions. Using this techniques, we observe a reduction of up to 98% in the number of large linear solutions for a three-dimensional tomography problem.
In the second manuscript, we focus on establishing a robust algorithm. We propose a new trust region framework that replaces the objective function evaluations with stochastic estimates of the improvement factor and the misfit between the model and objective function gradients. If these estimates satisfy a fixed multiplicative error bound with a high, but fixed, probability, we show that this framework converges almost surely to a stationary point of the objective function. We derive suitable bounds for the DOT problem and present results illustrating the robust nature of these estimates with only 10 samples per iteration.Doctor of Philosophy
For problems such as medical imaging, the process of reconstructing the state of a system from measurement data can be very expensive to compute. The ever increasing need for high accuracy requires very large models to be used. Reducing the computational burden by replacing the model with a specially constructed smaller model is an established and effective technique. However, it can be difficult to determine how well the smaller model matches the original model. In this thesis, we examine two techniques for estimating the quality of a smaller model based on randomized combinations of sources and detectors. The first technique focuses on reducing the computational cost as much as possible. With the equivalent of a single randomized source, we show that this estimate is an effective measure of the model quality. Coupled with a new technique for improving the smaller model, we demonstrate a highly efficient and robust method. The second technique prioritizes robustness in its algorithm. The algorithm uses these randomized combinations to estimate how the observations change for different system states. If these estimates are accurate with a high probability, we show that this leads to a method that always finds a minimum misfit between predicted values and the observed data.
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Tao, Zuoyu. "Improved uncertainty estimates for geophysical parameter retrieval." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61516.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 167-169).
Algorithms for retrieval of geophysical parameters from radiances measured by instruments onboard satellites play a large role in helping scientists monitor the state of the planet. Current retrieval algorithms based on neural networks are superior in accuracy and speed compared to physics-based algorithms like iterated minimum variance (IMV). However, they do not have any form of error estimation, unlike IMV. This thesis examines the suitability of several different approaches to adding in confidence intervals and other methods of error estimation to the retrieval algorithm, as well as alternative machine learning methods that can both retrieve the parameters desired and assign error bars. Test datasets included both current generation operational instruments like AIRS/AMSU, as well as a hypothetical future hyper- spectral microwave sounder. Mixture density networks (MDN) and Sparse Pseudo Input Gaussian processes (SPGP) were found to be the most accurate at variance prediction. Both of these are novel methods in the field of remote sensing. MDNs also had similar training and testing time to neural networks, while SPGPs often took three times as long to train in typical cases. As a baseline, neural networks trained to estimate variance were also tested, but found to be lacking in accuracy and reliability compared to the other methods.
by Zuoyu Tao.
M.Eng.
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Hu, Huilin. "Large sample theory for pseudo-maximum likelihood estimates in semiparametric models /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/8936.
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Courdin, Marie Claire. "Laboratory reactor design and the precision of parameter estimates." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/7951.
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This study is concerned with investigating the dependence of the precision of estimated kinetic parameters on the type of reactor used for performing the kinetic measurements. Two ideal reactors, the plug-flow reactor (PFR) and the continuous-stirred-tank reactor (CSTR), were simulated using a Monte-Carlo computer simulation. Parameters were estimated using nonlinear multiresponse estimation techniques, and the distributional characteristics of the parameter estimates were calculated. Comparison between the reactors involved the study of overall measures of precision such as the size, shape and orientation of the 95% joint confidence region, and the determinant of the covariance matrix of the parameter estimates. Five variables were identified as having a possible affect on the precision: the nature of the reaction network, the kinetic model, the magnitudes of the rate parameters, the covariance structure of the responses, and the experimental design. The dependence of parameter precision on these variables is presented along with recommendations for determining the reactor type to give the most precise kinetic parameters.
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Wall, Nathan Lane. "Augmented testing and effects on item and proficiency estimates in different calibration designs." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/1100.
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Broadening the term augmented testing to include a combination of multiple measures to assess examinee performance on a single construct, the issues of IRT item parameter and proficiency estimates were investigated. The intent of this dissertation is to determine if different IRT calibration designs result in differences to item and proficiency parameter estimates and to understand the nature of those differences.
Examinees were sampled from a testing program in which each examinee was administered three mathematics assessments measuring a broad mathematics domain at the high school level. This sample of examinees was used to perform a real data analysis to investigate the item and proficiency estimates. A simulation study was also conducted based upon the real data.
The factors investigated for the real data study included three IRT calibration designs and two IRT models. The calibration designs included: separately calibrating each assessment, calibrating all assessments in one joint calibration, and separately calibrating items in three distinct content areas. Joint calibration refers to the use of IRT methodology to calibrate two or more tests, which have been administered to a single group, together so as to place all of the items on a common scale. The two IRT models were the one- and three-parameter logistic model. Also investigated were five proficiency estimators: maximum likelihood estimates, expected a posteriori, maximum a posteriori, summed-score EAP, and test characteristic curve estimates. The simulation study included the same calibration designs and IRT models but the data were simulated with varying levels of correlations among the proficiencies to determine the affect upon the item parameter estimates.
The main findings indicate that item parameter and proficiency estimates are affected by the IRT calibration design. The discrimination parameter estimates of the three-parameter model were larger when calibrated under the joint calibration design for one assessment but not for the other two. Noting that equal item discrimination is an assumption of the 1-PL model, this finding raises questions as to the degree of model fit when the 1-PL model is used. Items on a second assessment had lower difficulty parameters in the joint calibration design while the item parameter estimates of the other two assessments were higher. Differences in proficiency estimates between calibration designs were also discovered, which were found to result in examinees being inconsistently classified into performance categories. Differences were observed in regards to the choice of IRT model. Finally, as the level of correlation among proficiencies increased in the simulation data, the differences observed in the item parameter estimates were decreased.
Based upon the findings, IRT item parameter estimates resulting from differing calibrations designs should not be used interchangeably. Practitioners who use item pools should base the pool refreshment calibration design upon the one used to originally create the pool. Limitations to this study include the use of a single dataset consisting of high school examinees in only one subject area, thus the degree of generalization regarding research findings to other content areas of grade levels should be made with caution.
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Fernandes, Tamara. "Genetic parameter estimates for ultrasound-measured carcass traits in sheep." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0024/MQ51063.pdf.
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Piwonski, Jaroslaw [Verfasser]. "Parameter estimates for marine ecosystem models in 3-D / Jaroslaw Piwonski." Kiel : Universitätsbibliothek Kiel, 2015. http://d-nb.info/107021874X/34.
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Parekh, Namita. "Validity and efficiency of parameter estimates in frequency matched case-control studies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq45405.pdf.
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Devitt, Crosby Jordan Blake. "Genetic parameter estimates for finished steer carcass and yearling bull ultrasound measurements." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0026/MQ51058.pdf.
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Man, Peter Lau Weilen. "Statistical methods for computing sensitivities and parameter estimates of population balance models." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608291.
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Melka, Hailu Dadi. "Genetic parameter estimates for weaning traits in a multibreed beef cattle population." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52285.
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Thesis (MScAgric)--University Stellenbosch, 2001.ENGLISH ABSTRACT: The aim of this study was to estimate genetic parameters as well as to evaluate the influence of some genetic factors on preweaning growth traits in a multi breed beef cattle population. These preweaning growth traits were birth weight (BW), weaning weight (WW) and average daily gain (ADG). Three aspects were addressed in this particular study; namely the Estimation of (co)variance components and genetic parameters, the effect of sire breeds and dam genotypes and the contribution of Charolais and Angus breeding levels on weaning traits in a multibreed beef cattle herd. Variance components and resulting genetic parameters of BW, WW and ADG in the population were estimated by Restricted Maximum Likelihood (REML) procedures. Four different unitrait and multitrait animal models were fitted ranging from a simple model with the animal direct effects as the only random effect to the model allowing for both genetic and permanent maternal environmental effects. The model that included directgenetic and permanent maternal environmental effects generally best described the data analysed. The simple model ignoring maternal effects most likely inflated direct heritability estimates. Direct heritability estimates were 0.11, 0.19, and 0.15 for BW, WW and ADG, respectively, fitting a multitrait model that comprised of both the genetic and maternal environmental effects. Under this comprehensive model, maternal heritabilties were low under both analyses, ranging from 0.02 to 0.10. Permanent maternal environmental effects were more important than maternal additive genetic effects for WW and ADG. Direct and maternal genetic correlations range from 0.42 to 0.44 for BW, -0.22 to -0.25 for WW and -0.17 to -0.23 for ADG, while the corresponding estimates ofunitrait analysis varied from 0.58 to 0.61 for BW, -0.43 to-0.53 for WW and -0.49 to -0.79 for ADG. The effect of Charolais and Hereford sires and dam breed genotypes on BW and WW in calves of Hereford, F I, two and three breed rotational as well as terminal crosses among the Charolais, Hereford, Angus and Bonsmara breeds were investigated. BW and WW of the Charolais sired calves were significantly (P
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Williams, N. G. "Frequency domain parameter identification and the statistical properties of frequency response estimates." Thesis, Loughborough University, 1993. https://dspace.lboro.ac.uk/2134/25141.
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Frequency domain techniques in systems theory have their origins in Heavyside's operational calculus (Heavyside, 1889). Such work was later developed by Foster and Campbell (1931), Brune (1931), Nyquist (1932), Black (1934), Darlington (1939) and subsequently Bode (1948). This interest in the frequency domain was due to its appeal to the intuition of the engineer. The dominance of frequency domain techniques was subsequently eroded from the late 1950s through the 1960s by the influence of the space programmes. The space systems being analysed were based on strong theoretical foundations with well-defined sets of differential equations. The analysis led to the development of the state-space methods which were able to cope with the multivariable problems and were amenable to numerical solution. As a result of these developments, control engineering was largely dominated by the state-space approach and the associated areas of LQG optimal control, Kaiman-Bucy filters, observability and controllability. Two factors led to a resurgence of interest amongst academics in the development of frequency domain techniques in the 1970s and 1980s. The first was the development of the Fast Fourier Transform (FFT) (Cooley & Tookey, 1965). This provided an efficient method of analysing the Fourier transforms of signals and allowed the development of spectral methods of obtaining frequency response estimates. The collection of data was greatly speeded up and this enabled frequency domain methods to be increasingly applied to on-line control problems. The second factor was that the developments in the time domain were never fully embraced by practicing engineers in traditional control environments.
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Jensen, Brady Robert. "Genetic parameter estimates for feet and leg traits in Red Angus cattle." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/36247.
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Master of ScienceDepartment of Animal Sciences and Industry
Jennifer M. Bormann
Robert L. Weaber
The objective of this study was to investigate the parameter estimates for feet and leg traits, relationships within feet and leg traits, and between feet and leg traits and production traits in Red Angus cattle. Subjective scores for 14 traits including: Body Condition Score (BCS), Front Hoof Angle (FHA), Front Heel Depth (FHD), Front Claw Shape (FCS), Rear Hoof Angle (RHA), Rear Heel Depth (RHD), Rear Claw Shape (RCS), Size of Hoof (Size), Front Side View (FSV), Knee Orientation (KNEE), Front Hoof Orientation (FHO), Rear Side View (RSV), Rear View (RV), and a Composite Score (COMP) were collected by trained evaluators on 1885 Red Angus cattle at different ranches across the United States. A three-generation pedigree file was obtained from the Red Angus Association of America (RAAA) that contained 13,306 animals, and EPDs on all animals with feet and leg scores were obtained. All traits except COMP were scored as intermediate optimum traits. Data were modeled using a linear bivariate animal model with random additive genetic and residual effects, and fixed effects of age and contemporary group (herd-year). Variances were estimated with ASREML 3.0 and 4.0. Heritability estimates of BCS, FHA, FHD, FCS, RHA, RHD, RCS, Size, FSV, Knee, FHO, RSV, RV, and COMP were 0.11, 0.20, 0.17, 0.09, 0.19, 0.25, 0.17, 0.36, 0.16, 0.17, 0.17, 0.30, 0.14, and 0.12, respectively. These results showed feet and leg traits were lowly to moderately heritable. Strong, positive genetic correlations were found between FHA and FHD (0.89), FHA and RHA (0.88), FHD and RHA (0.85), FHA and RHD (0.85), FHD and RHD (0.94), and FHO and Knee (0.95), indicating these traits may be highly related to one another. Strong negative correlations were found between Knee and FSV (-0.59) and FHO and FSV (-0.75). The strongest correlation was between front limb traits (FHA, FHD, FSV, FHO, Knee, and Comp) and the Stayability EPD (STAY) was FSV (r =0.16; r_s =0.20) and for rear limb traits (RHA, RHD, RCS, RSV, RV, and Comp) and STAY was RCS (r = -0.12; r_s=-0.14). This indicates that cattle with more slope to the angle of the shoulder stay in the herd longer and cattle with less curl to the inside of the claw tend to stay in the herd longer. Further studies with more data could help validate the relationship between feet and leg traits and production traits.
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Torres, Marcella. "DETERMINATION OF OPTIMAL PARAMETER ESTIMATES FOR MEDICAL INTERVENTIONS IN HUMAN METABOLISM AND INFLAMMATION." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5890.
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In this work we have developed three ordinary differential equation models of biological systems: body mass change in response to exercise, immune system response to a general inflammatory stimulus, and the immune system response in atherosclerosis. The purpose of developing such computational tools is to test hypotheses about the underlying biological processes that drive system outcomes as well as possible real medical interventions. Therefore, we focus our analysis on understanding key interactions between model parameters and outcomes to deepen our understanding of these complex processes as a means to developing effective treatments in obesity, sarcopenia, and inflammatory diseases.
We develop a model of the dynamics of muscle hypertrophy in response to resistance exercise and have shown that the parameters controlling response vary between male and female group means in an elderly population. We further explore this individual variability by fitting to data from a clinical obesity study. We then apply logistic regression and classification tree methods to the analysis of between- and within-group differences in underlying physiology that lead to different long-term body composition outcomes following a diet or exercise program. Finally, we explore dieting strategies using optimal control methods.
Next, we extend an existing model of inflammation to include different macrophage phenotypes. Complications with this phenotype switch can result in the accumulation of too many of either type and lead to chronic wounds or disease. With this model we are able to reproduce the expected timing of sequential influx of immune cells and mediators in a general inflammatory setting. We then calibrate this base model for the sequential response of immune cells with peritoneal cavity data from mice. Next, we develop a model for plaque formation in atherosclerosis by adapting the current inflammation model to capture the progression of macrophages to inflammatory foam cells in response to cholesterol consumption. The purpose of this work is ultimately to explore points of intervention that can lead to homeostasis.
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Dupuis, Michelle Annie. "Simulation of measles epidemics, behaviour of parameter estimates for different models of vaccine action." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ45456.pdf.
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Ready, Doreen. "The stability of item parameter estimates in the context of a second language competency test." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/9721.
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The purpose of this study was to examine the feasibility of using IRT models to equate test versions of an English second language (ESL) test through the use of subsets of linking items. The test was designed to measure global comprehension at the intermediate level, of listening and reading texts and general knowledge of vocabulary, grammar and structure as measured by a cloze text. The data were subsets of listening, reading and cloze items used on two or more occasions. The procedure used was to ascertain the stability of the item parameter estimates from correlations and other descriptive measures. The estimates were obtained using three estimation methods (LOGIST, BILOG, NoHarm) and three IRT models. In addition the unidimensionality of the data sets was examined using a method described by Gessaroli and De Champlain (1991). The results suggest that IRT models may not be suitable with test data such as those used in this study. Failure could not be consistently linked to too few candidates, issues of statistical dimensionality, too few items, or the difficulty of the material in which the target subsets were embedded. If an expanded study yields similar results, then the issue is one of validity, whether the definition of ESL global comprehension at the intermediate level is compatible with how an ability is defined under an IRT model.
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Stål, Karin. "Identifying Influential Observations in Nonlinear Regression : a focus on parameter estimates and the score test." Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-114324.
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This thesis contributes to influence analysis in nonlinear regression and in particular the detection of influential observations. The focus is on a regression model with a known mean function, which is nonlinear in its parameters and where the function is chosen according to the knowledge about the process generating the data. The error term in the regression model is assumed to be additive. The main goal of this thesis is to work out diagnostic measures for assessing the influence of observations on various results from a nonlinear regression analysis. The obtained results comprise diagnostic tools for detecting observations that, individually or jointly with some other observations, are influential on the parameter estimates. Moreover, assessing conditional influence, i.e. the influence of an observation conditional on the deletion of another observation, is of interest. This can help to identify influential observations which could be missed due to complex relationships among the observations. Novelties of the proposed diagnostic tools include the possibility to assess influence of observations on a specific parameter estimate and to assess influence of multiple observations. A further emphasis of this thesis is on the observations' influence on the outcome of a hypothesis testing procedure based on Rao's score test. An innovative solution to the problem of visual identification of influential observations regarding the score test statistic obtained in this thesis is the so called added parameter plot. As a complement to the added parameter plot, new diagnostic measures are derived for assessing the influence of single and multiple observations on the score test statistic.
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Li, Jingjie. "Drift parameter estimates for stochastic differential equations of mean-reversion type arising from financial modelings." Thesis, Swansea University, 2012. https://cronfa.swan.ac.uk/Record/cronfa42887.
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Tuffner, Francis K. "Computationally efficient weighted updating of statistical parameter estimates for time varying signals with application to power system identification." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1674094221&sid=4&Fmt=2&clientId=18949&RQT=309&VName=PQD.
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Gwaze, David Pasipanodya. "Genetic parameter estimates for height and stem straightness in Pinus taeda linnaeus and implications for breeding." Thesis, University of Edinburgh, 1997. http://hdl.handle.net/1842/13970.
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Fossceco, Stewart Lee. "Logistic growth curve parameter estimates for scrotal circumference and relationships with female reproduction in crossbred sheep." Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/37241.
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Data from two groups of lambs were analyzed. In group one, seasonal patterns of testis growth through 16 mo of age were assessed on 40 spring-born ram lambs (eight Barbados Blackbelly, 10 Suffolk and 22 1/2-Dorset, 1/4-Finnish Landrace, 1/4-Rambouillet). Scrotal circumference (sc) and body weight (wt) were measured at mean ages of 30, 62, 96, 124, 153, 180, 212, 243, 290, 333, 364, 398, 427, 454, 488 and 517 d. A multivariate repeated measures analysis indicated that there were breed differences in ram sc and wt measurements at each age. When logistic growth curves were fit to ram sc data, breed differences were associated with parameters of the logistic curve that defined mature testis size and the period of rapid testis growth.
For group two, data were collected on 1,044 lambs from 727 spring lambings over 5 years; 67 sires and 525 dams were represented. Sc and wt were measured in rams at 5 times (mean ages of 44, 63, 97, 129 and 156 d); ewes were weighed at these times and at three additional times (187, 230 and 271 d). All ewe lambs were kept for fall breeding. Fertility, prolificacy and postweaning spring mating behavior of ewes that had lambed were measured. After ewes lambed, they were exposed to vasectomized rams and checked for postweaning spring mating behavior.
Restricted maximum likelihood (REML) was used to estimate variance components for additive genetic, ewe, and litter effects in group two Jambs. Heritability estimates for wt at birth to 150 d ranged from .14 to .42. Heritabilities for sc and sc scaled to the 1/3 power of body weight (rsc) ranged from .09 to .57 and from .13 to .55, respectively, and were largest at approximately 90 d. Logistic sc growth curves were fitted to data from individual ram lambs. Heritabilities of the estimated logistic parameters mature sc (A), sc maturing rate (k), age at inflection of the sc growth curve (t₁) and initial 14-d sc (SC14), were estimated at .09±.15, .17±.18, .37±.29 and .40±.14, respectively. Heritability estimates for fertility and spring mating behavior (spbrd) were .04±.13 and .41±.19, respectively. The heritability estimate for prolificacy was zero.
Longitudinal additive genetic covariances among wt, sc and rsc at the second, third and fourth measurements were estimated from approximate multivariate REML analysis treating variances as known. Estimated genetic correlations among wts were largest, and ranged from. 77 to .93. Estimated genetic correlations for rsc traits were between .48 and .90. Estimated genetic correlations for sc ranged only from .10 to .67. Pairwise genetic correlations among sc or rsc with fertility or spbrd were estimated to be moderate and positive (.20 and .34, respectively); t₁ had correlations of -.32 and -.48 with fertility and spbrd, respectively.Ph. D.
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Pretorius, Samantha. "The effect of observation errors on parameter estimates applied to seismic hazard and insurance risk modelling." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/79774.
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The research attempts to resolve which method of estimation is the most consistent for the parameters of the earthquake model, and how these different methods of estimation, as well as other changes, in the earthquake model parameters affect the damage estimates for a specific area. The research also investigates different methods of parameter estimation in the context of the log-linear relationship characterised by the Gutenberg-Richter relation. Traditional methods are compared to those methods that take uncertainty in the underlying data into account. Alternative methods based on Bayesian statistics are investigated briefly. The efficiency of the feasible methods is investigated by comparing the results for a large number of synthetic earthquake catalogues for which the parameters are known and errors have been incorporated into each observation. In the second part of the study, the effects of changes in key parameters of the earthquake model on damage estimates are investigated. This includes an investigation of the different methods of estimation and their effect on the damage estimates. It is found that parameter estimates are affected by observation errors. If errors are not included in the method of estimation, the estimate is subject to bias. The nature of the errors determines the level of bias. It is concluded that uncertainty in the data used in earthquake parameter estimates is largely a function of the quality of the data that is available. The inaccuracy of parameter estimates depends on the nature of the errors that are present in the data. In turn, the nature of the errors in an earthquake catalogue depends on the method of compilation of the catalogue and can vary from being negligible, for single source catalogues for an area with a sophisticated seismograph network, to fairly impactful, for historical earthquake catalogues that predate seismograph networks. Probabilistic seismic risk assessment is used as a catastrophe modelling tool to circumvent the problem of scarce loss data in areas of low seismicity and is applied in this study for the greater Cape Town region in South Africa. The results of the risk assessment demonstrate that seemingly small changes in underlying earthquake parameters as a result of the incorporation of errors can lead to significant changes in loss estimates for buildings in an area of low seismicity.Dissertation (MSc)--University of Pretoria, 2014.
Insurance and Actuarial Science
MSc
Unrestricted
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Abed, Jamil, and Bert-Wolfgang Schulze. "Edge-degenerate families of ΨDO’s on an infinite cylinder." Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2009/3036/.
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We establish a parameter-dependent pseudo-differential calculus on an infinite cylinder, regarded as a manifold with conical exits to infinity. The parameters are involved in edge-degenerate form, and we formulate the operators in terms of operator-valued amplitude functions.
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Xiao, Yu. "Crown structure, growth performance, nutritional characteristics, and their genetic parameter estimates in juvenile loblolly and slash pine." [Gainesville, Fla.] : University of Florida, 2000. http://etd.fcla.edu/etd/uf/2000/ane6001/Final%5FThesis.PDF.
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Thesis (Ph. D.)--University of Florida, 2000.Title from first page of PDF file. Document formatted into pages; contains xv, 221 p.; also contains graphics. Vita. Includes bibliographical references (p. 203-220).
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Kellermann, Anh Pham. "Missing Data in Complex Sample Surveys: Impact of Deletion and Imputation Treatments on Point and Interval Parameter Estimates." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7633.
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The purpose of this simulation study was to evaluate the relative performance of five missing data treatments (MDTs) for handling missing data in complex sample surveys. The five missing data methods included in this study were listwise deletion (LW), single hot-deck imputation (HS), single regression imputation (RS), hot-deck-based multiple imputation (HM), and regression-based multiple imputation (RM). These MDTs were assessed in the context of regression weight estimates in multiple regression analysis in complex sample data with two data levels. In this study, the multiple regression equation had six regressors without missing data and two regressors with missing data. The four performance measures used in this study were statistical bias, RMSE, CI width, and coverage probability (i.e., 95%) of the confidence interval.
The five MDTs were evaluated separately for three types of missingness: MCAR, MAR, and MNAR. For each type of missingness, the studied MDTs were evaluated at four levels of missingness (10%, 30%, 50%, and 70%) along with complete sample conditions as a reference point for interpretation of results. In addition, ICC levels (.0, .25, .50) and high and low density population were also manipulated as studied factors.
The study’s findings revealed that the performance of each individual MDT varied across missing data types, but their relative performance was quite similar for all missing data types except for LW’s performance in MNAR. RS produced the most inaccurate estimates considering bias, RMSE, and coverage of confidence interval; RM and HM were the second poorest performers. LW as well as HS procedure outperformed the rest on the measures of accuracy and precision in MCAR; however LW’s measures of precision decreased in MAR and MNAR, and LW’s CI width was the widest in MNAR data. In addition, in all three missing data types, those poor performers were less accurate and less precise on variables with missing data than they were on variables without missing data; and the degree of accuracy and precision of these poor performers depended mostly on the level of data ICC. The proportion of missing data only noticeably affected the performance of HM such that in higher missing data levels, HM yielded worse performance measures. Population density factor had negligible effects on most of the measures produced by all studied MDTs except for RMSE, CI width, and CI coverage produced by LW which were modestly influenced by population density.
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Wu, Yi-Fang. "Accuracy and variability of item parameter estimates from marginal maximum a posteriori estimation and Bayesian inference via Gibbs samplers." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/5879.
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Item response theory (IRT) uses a family of statistical models for estimating stable characteristics of items and examinees and defining how these characteristics interact in describing item and test performance. With a focus on the three-parameter logistic IRT (Birnbaum, 1968; Lord, 1980) model, the current study examines the accuracy and variability of the item parameter estimates from the marginal maximum a posteriori estimation via an expectation-maximization algorithm (MMAP/EM) and the Markov chain Monte Carlo Gibbs sampling (MCMC/GS) approach.
In the study, the various factors which have an impact on the accuracy and variability of the item parameter estimates are discussed, and then further evaluated through a large scale simulation. The factors of interest include the composition and length of tests, the distribution of underlying latent traits, the size of samples, and the prior distributions of discrimination, difficulty, and pseudo-guessing parameters.
The results of the two estimation methods are compared to determine the lower limit--in terms of test length, sample size, test characteristics, and prior distributions of item parameters--at which the methods can satisfactorily recover item parameters and efficiently function in reality. For practitioners, the results help to define limits on the appropriate use of the BILOG-MG (which implements MMAP/EM) and also, to assist in deciding the utility of OpenBUGS (which carries out MCMC/GS) for item parameter estimation in practice.
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Patsula, Liane. "A comparison of item parameter estimates and ICCs produced with TESTGRAF and BILOG under different test lengths and sample sizes." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/9889.
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There are many procedures used to estimate IRT parameters; however, among the most popular techniques are those used in the LOGIST and BILOG computer programs. LOGIST requires large numbers of examinees and items (in the order of 1000 or more examinees and 40 or more items) for stable 3PL model parameter estimates. BILOG is a more recent estimation program and, in general, requires smaller numbers of examinees and items than LOGIST for stable 3PL model parameter estimates. It also has been found that, regardless of sample size and test length, BILOG estimates tend to be uniformly more or at least as accurate as LOGIST estimates. For this reason, BILOG is now used as the standard to which new estimation programs are compared. The purpose of this study was to examine the effects of varying sample size (N = 100, 250, 500, and 1000) and test length (20- and 40-item tests) on the accuracy and consistency of 3PL model item parameter estimates and ICCs obtained from TESTGRAF and BILOG. Overall, TESTGRAF seemed to perform better or just as well as BILOG. Where large bias effect sizes existed, in all but one case, TESTGRAF was more accurate than BILOG. TESTGRAF was slightly less accurate than BILOG in estimating the $P(\theta$)'s at high ability levels. Where large efficiency effect sizes existed, in all but two cases, TESTGRAF was more consistent than BILOG. TESTGRAF was slightly less consistent than BILOG in estimating the a parameter with a sample size of 1000 and in estimating the c parameter at all sample sizes. (Abstract shortened by UMI.)
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Yang, Seungho. "A comparison of unidimensional and multidimensional rasch models using parameter estimates and fit indices when assumption of unidimensionality is violated." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1195695378.
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Othuon, Lucas Onyango A. "The accuracy of parameter estimates and coverage probability of population values in regression models upon different treatments of systematically missing data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ34604.pdf.
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Yegin, Oya Perim. "The Predictive Validity Of Baskent University Proficiency Exam (buepe) Through The Use Of The Three-parameter Irt Model&." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1013507/index.pdf.
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The purpose of the present study is to investigate the predictive validity of the BUEPE through the use of the three-parameter IRT model’
s ability estimates. The study made use of the BUEPE September 2000 data which included the responses of 699 students. The predictive validity was established by using the departmental English courses (DEC) passing grades of a total number of 371 students. As for the prerequisite analysis the best fitted model of IRT was determined by first, checking the assumptions of IRT
second, by analyzing the invariance of ability parameters and item parameters and thirdly, by interpreting the chi-square statistics. After the prerequisite analyses, the best fitted model&
#8217
s estimates were correlated with DEC passing grades to investigate the predictive power of BUEPE on DEC passing grades. The findings indicated that the minimal guessing assumption of the one- and two-parameter models was not met. In addition, the chi-square statistics indicated a better fit to the three-parameter model. Therefore, it was concluded that the best fitted model was the three-parameter model. The findings of the predictive validity analyses revealed that the best predictors for DEC passing grades were the three-parameter model ability estimates. The second best predictor was the ability estimates obtained from sixty high information items. In the third place BUEPE total scores and the total scores obtained from sixty high information items followed with nearly the same correlation coefficients. Among the three sub-tests, the reading sub-test was found to be the best predictor of DEC passing grades.
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Ainkaran, Ponnuthurai. "Analysis of Some Linear and Nonlinear Time Series Models." Thesis, The University of Sydney, 2004. http://hdl.handle.net/2123/582.
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Abstract This thesis considers some linear and nonlinear time series models. In the linear case, the analysis of a large number of short time series generated by a first order autoregressive type model is considered. The conditional and exact maximum likelihood procedures are developed to estimate parameters. Simulation results are presented and compare the bias and the mean square errors of the parameter estimates. In Chapter 3, five important nonlinear models are considered and their time series properties are discussed. The estimating function approach for nonlinear models is developed in detail in Chapter 4 and examples are added to illustrate the theory. A simulation study is carried out to examine the finite sample behavior of these proposed estimates based on the estimating functions.
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Ainkaran, Ponnuthurai. "Analysis of Some Linear and Nonlinear Time Series Models." University of Sydney. Mathematics & statistics, 2004. http://hdl.handle.net/2123/582.
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Abstract This thesis considers some linear and nonlinear time series models. In the linear case, the analysis of a large number of short time series generated by a first order autoregressive type model is considered. The conditional and exact maximum likelihood procedures are developed to estimate parameters. Simulation results are presented and compare the bias and the mean square errors of the parameter estimates. In Chapter 3, five important nonlinear models are considered and their time series properties are discussed. The estimating function approach for nonlinear models is developed in detail in Chapter 4 and examples are added to illustrate the theory. A simulation study is carried out to examine the finite sample behavior of these proposed estimates based on the estimating functions.
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Wiebe, Jonathan Andrew. "Texture estimates of operational forestry parameters." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0007/MQ35026.pdf.
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Favorite, Jeffrey Alan. "Variational estimates of point kinetics parameters." Thesis, Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/16756.
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Zachary, A. Glen. "The estimated parameter flood forecasting model." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/25148.
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Design flood estimates have traditionally been based on records of past events. However, there is a need for a method of estimating peak flows without these records. The Estimated Parameter Flood Forecasting Model (EPFFM) has been developed to provide such a method for small water resource projects based on a 200 year or less design flood. This "user friendly" computer model calculates the expected peak flow and its standard deviation from low, probable, and high estimates of thirteen user supplied parameters. These parameters describe physical characteristics of the drainage basin, infiltration rates, and rainstorm characteristics. The standard deviation provides a measure of reliability and is used to produce an 80% confidence interval on peak flows.
The thesis briefly reviews existing flow estimation techniques and then describes the development of EPFFM. This includes descriptions of the Chicago method of rainfall hyetograph synthesis, Horton's infiltration equation, inflow by time-area method, Muskingum routing equation, and an approximate method of estimating the variance of multivariate equations since these are all used by EPFFM to model the physical and mathematical processes involved. Two examples are included to demonstrate EPFFM's ability to estimate a confidence interval, and compare these with recorded peak flows.Applied Science, Faculty of
Civil Engineering, Department of
Graduate
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Strasser, Helmut. "Perturbation invariant estimates and incidental nuisance parameters." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 1996. http://epub.wu.ac.at/1138/1/document.pdf.
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It is shown (Proposition (3.9)) that the asymptotic information bound which is valid for the estimation of a parameter in the structure (mixture) model remains valid in the functional model (incidental nuisance parameters) if only perturbation symmetric estimators (Definition (3.6)) are admitted. Pertur- bation symmetry is a property which is closely related to permutation symmetry (Theorem (3.4)). In particular, equicontinuous functions of empirical processes are perturbation symmetric (Theorem (3.3)). Thus, the results of this paper continue a discussion initiated by Bickel and Klaassen (1986), Pfanzagl (1993) and Strasser (1996) on permutation symmetry of estimators and the exclusion of superefficiency in the functional model. (authors' abstract)Series: Forschungsberichte / Institut für Statistik
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Sousa, Rita Cristina Pinto de. "Parameter estimation in the presence of auxiliary information." Doctoral thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/11295.
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Dissertação para obtenção do Grau de Doutora em
Estatística e Gestão de Risco, Especialidade em EstatísticaIn survey research, there are many situations when the primary variable of interest is sensitive. The sensitivity of some queries can give rise to a refusal to answer or to false answers given intentionally. Survey can be conducted in a variety of settings, in part dictated by the mode of data collection, and these settings can differ in how much privacy they offer the respondent. The estimates obtained from a direct survey on sensitive questions would be subject to high bias. A variety of techniques have been used to improve reporting by increasing the privacy of the respondents. The Randomized Response Technique (RRT), introduced byWarner in 1965, develops a random relation between the individual’s response and the question. This technique provides confidentiality to respondents and still allows the interviewers to estimate the characteristic of interest at an aggregate level. In this thesis we propose some estimators to improve the mean estimation of a sensitive variable based on a RRT by making use of available non-sensitive auxiliary information. In the first part of this thesis we present the ratio and the regression estimators as well as some generalizations in order to study the gain in the estimation over the ordinary RRT mean estimator. In chapters 4 and 5 we study the performance of some exponential type estimators, also based on a RRT. The final part of the thesis illustrates an approach to mean estimation in stratified sampling. This study confirms some previous results for a different sample design. An extensive simulation study and an application to a real dataset are done for all the study estimators to evaluate their performance. In the last chapter we present a general discussion referring to the main results and conclusions as well as showing an application to a real dataset which compares the performance of study estimators.
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Strasser, Helmut. "Asymptotic Efficiency of Estimates for Models with Incidental Nuisance Parameters." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 1995. http://epub.wu.ac.at/498/1/document.pdf.
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In this paper we show that the wellknown asymptotic efficiency bounds for full mixture models remain valid if individual sequences of nuisance parameters are considered. This is made precise both for some classes of random (i.i.d.) and nonrandom nuisance parameters. For the random case it is shown that superefficiency of the kind given by an example of Pfanzagl (1993) can happen only with low probability. The non-random case deals with permutation invariant estimators under onedimensional nuisance parameters. It is shown that the efficiency bounds remain valid for individual nonrandom arrays of nuisance parameters whose empirical process, if it is centered around its limit and standardized, satisfies a compactness condition. The compactness condition is satisfied in the random case with high probability. The results make use of basic LAN-theory. Regularity conditions are stated in terms of L^2 differentiability. (authors' abstract)Series: Forschungsberichte / Institut für Statistik
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Mahoney, Craig. "Improved estimates of vegetation and terrain parameters from waveform LiDAR." Thesis, Swansea University, 2014. https://cronfa.swan.ac.uk/Record/cronfa42490.
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Light Detection And Ranging (LiDAR) technologies have evolved rapidly over the last decade, contributing to our knowledge of the Earth's surface evolution from local to global scales. A relatively young form of LiDAR is continuous waveform, which has not yet been fully exploited. The current research investigates and develops new methods, highlighting the potential and possible pitfalls of working with continuous waveform LiDAR. The first piece of research investigates the effects of shadowing in LiDAR waveforms in physically observed, large footprint LiDAR waveforms, based on previous works noting shadowing effects in radiative transfer models, and in a controlled environment experiment. For this investigation airborne LiDAR derived digital elevation models were employed in conjunction with spatially corresponding waveform returns to identify possible shadowing effects. It was found that shadows occur more frequently over more severely sloped terrain, affecting the accuracy of waveform derived vegetation parameters. The implications of shadows in waveform data are also discussed. The second piece of research develops and tests two methods, the Slope Screening Model and Independent Slope Model, such to determine ground slope information from LiDAR waveforms. Both methods were validated against discrete return airborne LiDAR data, and British Ordnance Survey data, such to identify winch method is most suited to retrieving slope. The third piece of research utilises the favoured method for slope prediction from the second research topic to correct vegetation height estimates for slope. Two methods (Lox' and modified) are investigated and tested, and validated against airborne LiDAR equivalent results at the regional scale, and against normalised difference vegetation index at the near global scale. Both correction methods produced statistically significant differences in mean global vegetation heights with regards to a control dataset.
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Saatchi, Mustafa. "Genetic parameters of production traits in Welsh mountain sheep." Thesis, Bangor University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263274.
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Warwick, Jane. "Selecting tuning parameters in minimum distance estimators." Thesis, Open University, 2002. http://oro.open.ac.uk/19918/.
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Many minimum distance estimators have the potential to provide parameter estimates which are both robust and efficient and yet, despite these highly desirable theoretical properties, they are rarely used in practice. This is because the performance of these estimators is rarely guaranteed per se but obtained by placing a suitable value on some tuning parameter. Hence there is a risk involved in implementing these methods because if the value chosen for the tuning parameter is inappropriate for the data to which the method is applied, the resulting estimators may not have the desired theoretical properties and could even perform less well than one of the simpler, more widely used alternatives. There are currently no data-based methods available for deciding what value one should place on these tuning parameters hence the primary aim of this research is to develop an objective way of selecting values for the tuning parameters in minimum distance estimators so that the full potential of these estimators might be realised. This new method was initially developed to optimise the performance of the density power divergence estimator, which was proposed by Basu, Harris, Hjort and Jones [3]. The results were very promising so the method was then applied to two other minimum distance estimators and the results compared.
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Warwick, Jane. "Selecting tuning parameters in minimum distance estimators." n.p, 2001. http://ethos.bl.uk/.
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Dang, Thi To Nhu. "Estimation des indices de stabilité et d'autosimilarité par variations de puissances négatives." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM033/document.
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Ce travail porte sur l'estimation des indices d'autosimilarité et de stabilité d'un processus ou champ stable fractionnaire et autosimilaire ou d'un processus stable multifractionnaire.Plus précisément, soit X un processus ou un champ stable H-autosimilaire à accroissements stationnaires (H-sssi) ou un processus stable multifractionnaire. Nous observons X aux points k/n, k=0,..., n.Nos estimations sont basées sur des variations de puissances négatives beta avec -1/2This work is concerned with the estimation of the self-similarity and the stability indices of a H-self-similarity stable process (field) or a multifractional stable process.More precisely, let X be a H-sssi (self-similar stationary increments) symmetric alpha-stable process (field) or a multifractional stable process. We observe X at points k/n, k=0,...,n.Our estimates are based on beta-negative power variations with -1/2
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Bhagawat, Pankaj. "Design of a robust parameter estimator for nominally Laplacian noise." Texas A&M University, 2003. http://hdl.handle.net/1969/107.
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Völcker, Björn. "Performance Analysis of Parametric Spectral Estimators." Doctoral thesis, KTH, Signals, Sensors and Systems, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3323.
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Gao, Song. "The Exploration of the Relationship Between Guessing and Latent Ability in IRT Models." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/423.
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This study explored the relationship between successful guessing and latent ability in IRT models. A new IRT model was developed with a guessing function integrating probability of guessing an item correctly with the examinee's ability and the item parameters. The conventional 3PL IRT model was compared with the new 2PL-Guessing model on parameter estimation using the Monte Carlo method. SAS program was used to implement the data simulation and the maximum likelihood estimation. Compared with the traditional 3PL model, the new model should reflect: a) the maximum probability of guessing should not be more than 0.5, even for the highest ability examinees; b) different ability of examinees should have different probability of successful guessing, because a basic assumption for the new models is that higher ability examinees have a higher probability of successful guessing than lower ability examinees; c) smaller standard error in estimating parameters; and d) faster running time. The results illustrated that the new 2PL-Guessing model was superior to the 3PL model in all four aspects.
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Lee, Wonwoo. "Fractional principal components regression: a general approach to biased estimators." Diss., Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/49819.
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Setiadi, Hari. "Small sample IRT item parameter estimates." 1997. https://scholarworks.umass.edu/dissertations/AAI9737583.
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Item response theory (IRT) has great potential for solving many measurement problems. The success of specific IRT applications can be obtained only when the fit between the model and the test data is satisfactory. But model fit is not the only concern. Many tests are administered to relatively small numbers of examinees. If sample sizes are small, item parameter estimates will be of limited usefulness. There appear to be a number of ways that estimation might be improved. The purpose of this study was to investigate IRT parameter estimation using several promising small sample procedures. Computer simulation was used to generate the data. Two item banks were created with items described by a three parameter logistic model. Tests of length 30 and 60 items were simulated; examinee samples of 100, 200, and 500 were used in item calibration. Four promising models and associated estimation procedures were selected: (1) the one-parameter logistic model, (2) a modified one-parameter model in which a constant value for the "guessing parameter" was assumed, (3) a non-parametric three parameter model (called "Testgraf"), and (4) a one-parameter Bayesian model (with a variety of priors on the item difficulty parameter). Several criteria were used in evaluating the estimates. The main results were that (1) the modified one-parameter model seemed to consistently lead to the best estimates of item difficulty and examinee ability compared to the Rasch model and the non-parametric three-parameter model and related estimation procedures (the finding was observed across both test lengths and all three sample sizes and seemed to be true with both normal and rectangular distributions of ability), (2) the Bayesian estimation procedures with reasonable priors led to comparable results to the modified one-parameter model, and (3) the results with Testgraf, for the smallest sample of 100, typically led to the poorest results. Future studies seem justified to (1) replicate the findings with more relevant evaluation criteria, (2) determine the source of the problem with Testgraf and small samples/short tests, and (3) further investigate the utility of Bayesian estimation procedures.
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Wells, Craig Stephen. "The effect of item parameter drift on examinee ability estimates." 2000. http://catalog.hathitrust.org/api/volumes/oclc/46614526.html.
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Thesis (M.S.)--University of Wisconsin--Madison, 2000.Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 26-28).
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McLean, Kevin. "Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data." Thesis, 2011. http://hdl.handle.net/1974/6757.
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Engineers who develop fundamental models for chemical processes are often unable to estimate all of the model parameters due to problems with parameter identifiability and estimability. The literature concerning these two concepts is reviewed and techniques for assessing parameter identifiability and estimability in nonlinear dynamic models are summarized. Modellers often face estimability problems when the available data are limited or noisy. In this situation, modellers must decide whether to conduct new experiments, change the model structure, or to estimate only a subset of the parameters and leave others at fixed values. Estimating only a subset of important model parameters is a technique often used by modellers who face estimability problems and it may lead to better model predictions with lower mean squared error (MSE) than the full model with all parameters estimated. Different methods in the literature for parameter subset selection are discussed and compared.
An orthogonalization algorithm combined with a recent MSE-based criterion has been used successfully to rank parameters from most to least estimable and to determine the parameter subset that should be estimated to obtain the best predictions. In this work, this strategy is applied to a batch reactor model using additional data and results are compared with computationally-expensive leave-one-out cross-validation. A new simultaneous ranking and selection technique based on this MSE criterion is also described. Unfortunately, results from these parameter selection techniques are sensitive to the initial parameter values and the uncertainty factors used to calculate sensitivity coefficients. A robustness test is proposed and applied to assess the sensitivity of the selected parameter subset to the initial parameter guesses. The selected parameter subsets are compared with those selected using another MSE-based method proposed by Chu et al. (2009). The computational efforts of these methods are compared and recommendations are provided to modellers.Thesis (Master, Chemical Engineering) -- Queen's University, 2011-09-27 10:52:31.588