Browsing by Subject "Statistics"
Now showing items 160 of 130

A Bayesian hierarchical model for detecting associations between haplotypes and disease using unphased SNPs
(2008)This thesis addresses using haplotypes to detect disease predisposing chromosomal regions based on a Bayesian hierarchical model for casecontrol data. By utilizing the Stochastic Search Variable Selection (SSVS) procedure ... 
A comparison of three methods used to determine functionally important protein residues
(2003)A new method for determining functionally important protein residues is analyzed and compared with two previously existing methods. This thesis presents the analysis of several different protein sequences and shows how the ... 
A comprehensive approach to spatial and spatiotemporal dependence modeling
(2000)One of the most difficult tasks of modeling spatial and spatiotemporal random fields is that of deriving an accurate representation of the dependence structure. In practice, the researcher is faced with selecting the best ... 
A dynamic model for survival data with longitudinal covariates
(2006)Analyses involving both longitudinal and timetoevent data are quite common in medical research. The primary goal of such studies may be to simultaneously study the effect of treatment on both the longitudinal covariate ... 
A geometry for detection theory
(1993)The optimal detector for a binary detection problem under a variety of criteria is the likelihood ratio test. Despite this simple characterization of the detector, analytic performance analysis in most cases is difficult ... 
A hierarchical waveletbased framework for pattern analysis and synthesis
(2000)Despite their success in other areas of statistical signal processing, current waveletbased image models are inadequate for modeling patterns in images, due to the presence of unknown transformations inherent in most ... 
A microsatellitebased statistic for inferring patterns of population growth: Sampling properties and hypothesis testing
(2000)DNA sequences sampled from a genetic locus within a population are related by a genealogy. If there is no recombination within the locus, each pair of sequences is descended from some ancestral sequence, one of which is ... 
A new method for robust nonparametric regression
(1990)Consider the problem of estimating the mean function underlying a set of noisy data. Least squares is appropriate if the error distribution of the noise is Gaussian, and if there is good reason to believe that the underlying ... 
A nonparametric regression algorithm for time series forecasting applied to daily maximum urban ozone concentrations
(1989)Using techniques of nonparametric regression, we develop a nonparametric approach in the context of kernel estimation to realize shortterm forecastings of time series. This procedure is applied to an OZONE ($O\sb3)$ daily ... 
A stochastic approach to prepayment modeling
(1996)A new type of prepayment model for use in the valuation of mortgagebacked securities is presented. The model is based on a simple axiomatic characterization of the prepayment decision by the individual in terms of a ... 
A STUDY OF PROJECTION PURSUIT METHODS (MULTIVARIATE STATISTICS, DIMENSION REDUCTION, DENSITY ESTIMATION, GRAPHICS, ENTROPY)
(1985)A standard method for analyzing high dimensional multivariate data is to view scatterplots of 2dimensional projections of the data. Since all projections are not equally informative and the number of significantly different ... 
A test of mode existence with applications to multimodality
(1993)Modes, or local maxima, are often among the most interesting features of a probability density function. Given a set of data drawn from an unknown density, it is frequently desirable to know whether or not the density is ... 
A time series approach to quality control
(1991)One way that a process may be said to be "outofcontrol" is when a cyclical pattern exists in the observations over time. It is necessary that an accurate control chart be developed to signal when a cycle is present in ... 
Active learning and adaptive sampling for nonparametric inference
(2008)This thesis presents a general discussion of active learning and adaptive sampling. In many practical scenarios it is possible to use information gleaned from previous observations to focus the sampling process, in the ... 
Adaptive kernel density estimation
(1994)The need for improvements over the fixed kernel density estimator in certain situations has been discussed extensively in the literature, particularly in the application of density estimation to mode hunting. Problem ... 
An approach to modeling a multivariate spatialtemporal process
(2000)Although modeling of spatialtemporal stochastic processes is a growing area of research, one underdeveloped area in this field is the multivariate spacetime setting. The motivation for this research originates from air ... 
An automatic algorithm for the estimation of mode location and numerosity in general multidimensional data
(1995)Exploratory data analysis in four or more dimensions present many challenges that are unknown in lower dimensionalities. The emptiness of high dimensional space makes merely locating the regions in which data is concentrated ... 
An empirical evaluation of dependence analysis in parallel program comprehension
(1995)This research contributes two advances to the field of empirical study of parallel programming: first, the introduction of the Xbrowser system, a unique generalpurpose hypertext/hypermedia system combining highqualify ... 
An empirical study of feature selection in binary classification with DNA microarray data
(2005)Motivation. Binary classification is a common problem in many types of research including clinical applications of gene expression microarrays. This research is comprised of a largescale empirical study that involves a ... 
An examination of some open problems in time series analysis
(2005)We investigate two open problems in the area of time series analysis. The first is developing a methodology for multivariate time series analysis when our time series has components that are both continuous and categorical. ... 
An unconditional test for the singlesample binomial
(2004)An unconditional test is presented for a singlesample Binomial experiment with random sample size. The test is shown to be uniformly more powerful than the standard Binomial Test, and is shown through several simulations ... 
Analysis and interpretation of gammaray burst continuum spectral evolution with BATSE data
(1999)Once a day, a flash of gammarays erupts somewhere in space and is detected by an international fleet of satellites. Since their first detection over a quarter century ago, these gammaray bursts have puzzled researchers ... 
Analysis of longrange dependence in auditorynerve fiber recordings
(1994)The pattern of occurrence of isolated action potentials recorded from the cat's auditory nerve fiber is modeled over short time scales as a renewal process. For counting times greater than one second, the count variancetomean ... 
Analysis of regulatory mechanisms of genes controlled by the transcription factor NFkappaB
(2005)NFkappaB transcription factors are central to the regulation of many vital processes including immune response. It is known from microarray measurements and clustering methods that NFkappaB dependent genes in humans are ... 
Analyzing statistical dependencies in neural populations
(2005)Neurobiologists recently developed tools to record from large populations of neurons, and early results suggest that neurons interact to encode information jointly. However, traditional statistical analysis techniques are ... 
Applications of Bayesian sequential decision theory to medical decisionmaking
(2003)This thesis considers the use of Bayesian sequential decision theory for the diagnosis of precancerous lesions of the cervix otherwise known as cervical intraepithelial neoplasia (CIN). We consider a sequence of n ... 
Applying regularization to the fusion of empirical and numerical data
(2001)A method is presented to integrate computational and experimental data sets, allowing development of an accurate and comprehensive model of a system response surface. The method is derived from Generalized Tikhonov ... 
Aspects of functional data inference and its applications
(2006)We consider selected topics in estimation and testing of functional data. In many applications of functional data analysis, we aim to compare the sample functional data from two or more populations. However, the raw ... 
Autocorrelated data in quality control charts
(1994)Control charts are regularly developed with the assumption that the process observations have an independent relationship. However, a common occurrence in certain industries is the collection of autocorrelated data. Two ... 
Bayesian graphical models for biological network inference
(20131120)In this work, we propose approaches for the inference of graphical models in the Bayesian framework. Graphical models, which use a network structure to represent conditional dependencies among random variables, provide a ... 
Bayesian inference for ordinal data
(2006)Albert & Chib proposed a Bayesian ordinal probit regression model using the Gibbs sampler to model ordinal data. Their method defines a relationship between latent variables and ordinal outcomes using cutpoint parameters. ... 
Bayesian optimal design for phase II screening trials
(2006)Rapid progress in biomedical research necessitates clinical evaluation that identifies promising innovations quickly and efficiently. Rapid evaluation is especially important if the number of innovations is large compared ... 
Bayesian semiparametric and flexible models for analyzing biomedical data
(2010)In this thesis I develop novel Bayesian inference approaches for some typical data analysis problems as they arise with biomedical data. The common theme is the use of flexible and semiparametric Bayesian models and ... 
Branching processes with biological applications
(2010)Branching processes play an important role in models of genetics, molecular biology, microbiology, ecology and evolutionary theory. This thesis explores three aspects of branching processes with biological applications. ... 
Change detection using types for nonstationary processes
(1999)Space shuttle operation requires the monitoring of a large number of stationary signals in the search for "anomalies." This problem amounts to determining whether a change has occurred in a signal having a partially known ... 
Clustering timecourse geneexpression array data
(2008)This thesis examines methods used to cluster timecourse gene expression array data. In the past decade, various modelbased methods have been published and advocated for clustering this type of data in place of classic ... 
Computational models of signaling processes in cells with applications: Influence of stochastic and spatial effects
(2012)The usual approach to the study of signaling pathways in biological systems is to assume that high numbers of cells and of perfectly mixed molecules within cells are involved. To study the temporal evolution of the system ... 
Computing diversity in undergraduate admissions decisions
(2009)The Supreme Court decision in the University of Michigan case in 2003 ruled the university's admissions procedures unconstitutional, giving minorities an unfair advantage of acceptance. The ruling stated race may still be ... 
Denoising by wavelet thresholding using multivariate minimum distance partial density estimation
(2006)In this thesis, we consider waveletbased denoising of signals and images contaminated with white Gaussian noise. Existing waveletbased denoising methods are limited because they make at least one of the following three ... 
Dimension reduction methods with applications to high dimensional data with a censored response
(2010)Dimension reduction methods have come to the forefront of many applications where the number of covariates, p, far exceed the sample size, N. For example, in survival analysis studies using microarray gene expression data, ... 
Empirical detection for spread spectrum and code division multiple access (CDMA) communications
(1998)In this thesis, the method of "classification with empirically observed statistics"also known as empirical classification, empirical detection, universal classification, and typebased detectionis configured and applied ... 
Error detection and data smoothing based on local procedures
(1974)This thesis presents an algorithm which is able to locate isolated bad points and correct them without contaminating the rest of the good data. This work has been greatly influenced and motivated by what is currently done ... 
Essays on domestic and international airline economics with some bootstrap applications
(1999)We present several essays on topics in airline economics. The first essay presents a model of U.S. aircraft demand. This joint model of demand for and supply of commercial air service allow us to simulate the effects of ... 
Estimating marginal survival in the presence of dependent and independent censoring: With applications to dividend initiation policy
(2005)In many survival analysis settings, the assumption of noninformative (i.e. independent) censoring is not valid. Zheng and Klein (1995, 1996) develop a copulabased method for estimating the marginal survival functions of ... 
Estimating nonlinear functionals of a random field
(2001)Environmental data are gathered with the goal of estimating some quantity of interest. In particular, in the case of groundwater or soil contamination, it is desirable to estimate the total amount of contaminant present ... 
Estimating realized covariance using high frequency data
(2008)Assessing the economic value of increasingly precise covariance estimates is of great interest in finance. We present a realized ticktime covariance estimator that incorporates crossmarket tickmatching and intelligent ... 
Estimating the term structure with a semiparametric Bayesian population model: An application to corporate bonds
(2010)The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a new framework for estimating the term ... 
Estimation of contaminant concentration in ground water using a stochastic flow and transport model
(1996)Bioplume II, a widely used computer model developed by researchers at Rice University, models the transport of dissolved hydrocarbons in ground water under the influence of oxygenlimited biodegradation. The model is ... 
Evolution of microsatellite loci: Models and data
(1997)Microsatellite loci are important for genetic studies due to the many desirable qualities they possess. However, speculation continues about the types of mutation that act on microsatellites. In particular, whether different ... 
Forwardtime population genetics simulation and its applications in the mapping of complex human diseases
(2006)Forwardtime simulation has some unique advantages over the coalescent approach in the study of complex human diseases, but its application has been deterred, not only by its inherent inefficiency, but also by the lack of ... 
Functional data classification and covariance estimation
(2009)Focusing on the analysis of functional data, the first part of this dissertation proposes three statistical models for functional data classification and applies them to a real problem of cervical precancer diagnosis; the ... 
Futures prices: Data mining and modeling approaches
(2000)We present a series of models capturing the nonstationarities and dependencies in the variance of yields on natural gas futures. Both univariate and multivariate models are explored, based on the ARIMA and HiddenMarkov ... 
Galactic noise and the distance to Centaurus A
(1993)Deep B and R band photographic plates of the giant radio elliptical NGC 5128 (Centaurus A), obtained under photometric conditions at the f/3.3 prime focus of the AAT 3.9m telescope, clearly show surface brightness fluctuations ... 
Gaussian mixture regression and classification
(2004)The sparsity of high dimensional data space renders standard nonparametric methods ineffective for multivariate data. A new procedure, Gaussian Mixture Regression (GMR), is developed for multivariate nonlinear regression ... 
Genealogical methods for multitype branching processes with applications in biology
(2001)Biological populations are naturally organized into lineages of reproducing particles. Multitype branching processes are a probabilistic description of such systems. Historically, branching process models have been used ... 
Generalized Gaussian process models with Bayesian variable selection
(2010)This research proposes a unified Gaussian process modeling approach that extends to data from the exponential dispersion family and survival data. Our specific interest is in the analysis of datasets with predictors ... 
Haplotype block and genetic association
(2006)The recently identified (Daly et al. 2001 and Patil et al. 2001) blocklike structure in the human genome has attracted much attention since each haplotype block contains limited sequence variation, which can reduce the ... 
HISTOGRAM ESTIMATORS OF BIVARIATE DENSITIES (MULTIVARIATE, STATISTICS)
(1986)Onedimensional fixedinterval histogram estimators of univariate probability density functions are less efficient than the analogous variableinterval estimators which are constructed from intervals whose lengths are ...