Items in this collection are the scholarly output of the Department of Statistics faculty, staff, and students, either alone or as co-authors, and which may or may not have been published in an alternate format. Items may contain more than one file type.

Recent Submissions

  • On the de la Garza Phenomenon 

    Yang, Min, 1970 Oct. 28- (Institute of Mathematical Statistics, 2010)
    Deriving optimal designs for nonlinear models is, in general, challenging. One crucial step is to determine the number of support points needed. Current tools handle this on a case-by-case basis. Each combination of ...
  • Universal Optimality in Balanced Uniform Crossover Design 

    Hedayat, A.; Yang, Min, 1970 Oct. 28- (Institute of Mathematical Statistics, 2003)
    Kunert [Ann. Statist. 12 (1984) 1006-1017] proved that, in the class of repeated measurement designs based on t treatments, p = t periods and n = λt experimental units, a balanced uniform design is universally optimal for ...
  • Strong Consistency of MLE in Nonlinear Mixed-effects Models with Large Cluster Size 

    Nie, Lei; Yang, Min, 1970 Oct. 28- (Indian Statistical Institute, 2005)
    The search for conditions for the consistency of maximum likelihood estimators in nonlinear mixed effects models is difficult due to the fact that, in general, the likelihood can only be expressed as an integral over the ...
  • Support Points of Locally Optimal Designs for Nonlinear Models with Two Parameters 

    Yang, Min, 1970 Oct. 28-; Stufken, John (Institute of Mathematical Statistics, 2009)
    We propose a new approach for identifying the support points of a locally optimal design when the model is a nonlinear model. In contrast to the commonly used geometric approach, we use an approach based on algebraic tools. ...
  • ComPhy: Prokaryotic Composite Distance Phylogenies Inferred from Whole-Genome Gene Sets 

    Lin, Guan Ning, 1978-; Cai, Zhipeng; Lin, Guohui; Chakraborty, Sounak; Xu, Dong, 1965- (BioMed Central, 2009)
    With the increasing availability of whole genome sequences, it is becoming more and more important to use complete genome sequences for inferring species phylogenies. We developed a new tool ComPhy, 'Composite Distance ...
  • A Bayesian Approach to Estimating the Long Memory Parameter 

    Holan, Scott; McElroy, Tucker; Chakraborty, Sounak (Bayesian Analysis, 2009)
    We develop a Bayesian procedure for analyzing stationary long-range dependent processes. Specifically, we consider the fractional exponential model (FEXP) to estimate the memory parameter of a stationary long-memory Gaussian ...
  • Gene Expression-Based Glioma Classification Using Hierarchical Bayesian Vector Machines 

    Chakraborty, Sounak; Mallick, Bani K., 1965-; Ghosh, Debashis; Ghosh, Malay; Dougherty, Edward (Indian Statistical Institute, 2007)
    This paper considers several Bayesian classification methods for the analysis of the glioma cancer with microarray data based on reproducing kernel Hilbert space under the multiclass setup. We consider the multinomial ...
  • Spatio-Temporal Hierarchical Bayesian Modeling: Tropical Ocean Surface Winds 

    Wikle, Christopher K., 1963-; Milliff, Ralph F.; Nychka, Douglas; Berliner, L. Mark (American Statistical Association, 2001)
    Spatio-temporal processes are ubiquitous in the environmental and physical sciences. This is certainly true of atmospheric and oceanic processes, which typically exhibit many different scales of spatial and temporal ...
  • Predicting the Spatial Distribution of Ground Flora on Large Domains Using a Hierarchical Bayesian Model 

    Hooten, Mevin B., 1976-; Larsen, David R. (David Rolf); Wikle, Christopher K., 1963- (Landscape Ecology, 2003)
    Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural ...
  • Efficient Statistical Mapping of Avian Count Data 

    Royle, J. Andrew; Wikle, Christopher K., 1963- (Environmental and Ecological Statistics, 2005)
    We develop a spatial modeling framework for count data that is efficient to implement in high-dimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of the Poisson model. The ...
  • Shifts in the Spatio-Temporal Growth Dynamics of Shortleaf Pine 

    Hooten, Mevin B., 1976-; Wikle, Christopher K., 1963- (Environmental and Ecological Statistics, 2007)
    Previous studies focusing on the growth history of pinus echinata at the edge of its geographical range have suggested that changes in growth correspond to climatic and non-climatic (e.g., anthropogenic) factors. We employ ...
  • A Hierarchical Bayesian Non-linear Spatio-temporal Model for the Spread of Invasive Species with Application to the Eurasian Collared-Dove 

    Hooten, Mevin B., 1976-; Wikle, Christopher K., 1963- (Environmental and Ecological Statistics, 2007)
    Differential equation based advection-diffusion models have been used in atmospheric science to mimic complex processes such as weather and climate. Differential and partial-differential equations (PDE's) have become popular ...
  • Accounting for Uncertainty in Ecological Analysis: The Strengths and Limitations of Hierarchical Statistical Modeling 

    Cressie, Noel A. C.; Calder, Catherine A., 1976-; Clark, James Samuel, 1957-; Ver Hoef, Jay M.; Wikle, Christopher K., 1963- (Ecological Society of America, 2009-04)
    Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. ...
  • Multiresolution Models for Nonstationary Spatial Covariance Functions 

    Nychka, Douglas; Wikle, Christopher K., 1963-; Royle, J. Andrew (Statistical Modelling, 2002)
    Many geophysical and environmental problems depend on estimating a spatial process that has nonstationary structure. A nonstationary model is proposed based on the spatial field being a linear combination of a multiresolution ...
  • A Kernel-Based Spectral Model for Non-Gaussian Spatio-Temporal Processes 

    Wikle, Christopher K., 1963- (Statistical Modelling, 2002)
    Spatio-temporal processes can often be written as hierarchical state-space processes. In situations with complicated dynamics such as wave propagation, it is difficult to parameterize state transition functions for ...
  • Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes 

    Wikle, Christopher K., 1963- (Ecological Society of America, 2003)
    There is increasing interest in predicting ecological processes. Methods to accomplish such predictions must account for uncertainties in observation, sampling, models, and parameters. Statistical methods for spatio-temporal ...
  • Hierarchical Bayesian Approach to Boundary Value Problems with Stochastic Boundary Conditions 

    Wikle, Christopher K., 1963-; Berliner, L. Mark; Milliff, Ralph F. (American Meteorological Society, 2003)
    Boundary value problems are ubiquitous in the atmospheric and ocean sciences. Typical settings include bounded, partially bounded, global and limited area domains, discretized for applications of numerical models of the ...