SelectedWorks - Robert L. Paige

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Selected Works of Robert L. Paige

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Dr. Robert L. Paige is a Professor in the department of Mathematics and Statistics at Missouri University of Science and Technology. He has a Ph.D. in Statistics from Colorado State University--Fort Collins. Dr. Paige joined Missouri S&T in 2008.

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About Robert L. Paige

Dr. Robert L. Paige is a Professor in the department of Mathematics and Statistics at Missouri University of Science and Technology. He has a Ph.D. in Statistics from Colorado State University--Fort Collins. Dr. Paige joined Missouri S&T in 2008.

Optimal Equivalence Testing in Exponential Families

Statistical Papers (2022)

Renren Zhao and Robert L. Paige

We develop uniformly most powerful unbiased (UMPU) two sample equivalence test for a difference of canonical parameters in exponential families. ...

Small Sample Inference for Exponential Survival Times with Heavy Right-Censoring

Communications in Statistics - Theory and Methods (2021)

Robert L. Paige and Noroharivelo V. Randrianampy

We develop a saddlepoint-based method and several generalized Bartholomew methods for generating confidence intervals about the hazard rate of exponential ...

An Empirical Saddlepoint Approximation Based Method for Smoothing Survival Functions ...

The Canadian Journal of Statistics (2019)

Pratheepa Jeganathan, Noroharivelo V. Randrianampy, Robert L. Paige and A. Alexandre Trindade

The Kaplan-Meier (KM) estimator is ubiquitously used for estimating survival functions, but it provides only a discrete approximation at the ...

A Nonparametric Approach to 3D Shape Analysis from Digital Camera ...

Journal of Applied Statistics (2019)

Mingfei Qiu, Robert L. Paige and Vic Patrangenaru

With the wide availability of digital cameras and high quality smart phone cameras the world is awash in digital images. ...

Challenges in Topological Object Data Analysis

Sankhya A: The Indian Journal of Statistics (2019)

Vic Patrangenaru, Peter Bubenik, Robert L. Paige and Daniel Osborne

Statistical analysis on object data presents many challenges. Basic summaries such as means and variances are difficult to compute. We ...

Small Sample Confidence Intervals for Survival Functions under the Proportional ...

Communications in Statistics - Theory and Methods (2018)

Robert L. Paige and Emad Abdurasul

We develop a saddlepoint-based method for generating small sample confidence bands for the population surviival function from the Kaplan-Meier (KM), ...

Small Sample Equivalence Tests for Exponentiality

Communications in Statistics: Simulation and Computation (2018)

Robert L. Paige and Renren Zhao

We consider small sample equivalence tests for exponentialy. Statistical inference in this setting is particularly challenging since equivalence testing procedures ...

A Link-Free Approach for Testing Common Indices for Three or ...

Journal of Multivariate Analysis (2017)

Xuejing Liu, Lei Huo, Xuerong Meggie Wen and Robert L. Paige

Liu et al. (2015) proposed a novel link-free procedure for testing whether two multi-index models share identical indices via the ...

Projective Shape Analysis of Contours and Finite 3d Configurations from ...

Statistical Papers (2016)

Victor Patrangenaru, Robert L. Paige, K. David Yao, Mingfei Qiu, et al.

We analyze infinite dimensional projective shape data collected from digital camera images, focusing on two-sample hypothesis testing for both finite ...

Saddlepoint-Based Bootstrap Inference for the Spatial Dependence Parameter in the ...

Spatial Statistics (2015)

Pratheepa Jeganathan, Robert L. Paige and A. Alexandre Trindade

A saddlepoint-based bootstrap (SPBB) method for inference on the spatial dependence parameter in Gaussian lattice regression models is proposed. The ...

On Testing Common Indices for Two Multi-Index Models: A Link-Free ...

Journal of Multivariate Analysis (2015)

Xuejing Liu, Zhou Yu, Xuerong Meggie Wen and Robert L. Paige

We propose a link-free procedure for testing whether two multi-index models share identical indices via the sufficient dimension reduction approach. ...

Extensions of Saddlepoint-Based Bootstrap Inference

Annals of the Institute of Statistical Mathematics (2014)

Robert L. Paige, A. Alexandre Trindade and R. Indika P. Wickramasinghe

We propose two substantive extensions to the saddlepoint-based bootstrap (SPBB) methodology, whereby inference in parametric models is made through a ...

Fast and Accurate Inference for the Smoothing Parameter in Semiparametric ...

Australian and New Zealand Journal of Statistics (2013)

Robert Paige and A. Alexandre Trindade

A fast and accurate method of confidence interval construction for the smoothing parameter in penalised spline and partially linear models ...

Trap Design for the Brown Recluse Spider, Loxosceles Reclusa

Journal of Insect Science (2013)

Jennifer Parks, William V. Stoecker and Robert L. Paige

While there are limited options for chemical-free Arachnid pest control, glue-traps are one suitable alternative to pesticides. The effectiveness of ...

Exact Distributional Computations for Roy's Statistic and the Largest ...

Statistics and Computing (2011)

Ronald W. Butler and Robert Paige

Computational expressions for the exact CDF of Roy's test statistic in MANOVA and the largest eigenvalue of a Wishart matrix ...

Small Sample LD50 Confidence Intervals Using Saddlepoint Approximations

Journal of the American Statistical Association (2011)

Robert Paige, Phillip L. Chapman and Ronald W. Butler

Confidence intervals for the median lethal dose (LD50) and other dose percentiles in logistic regression models are developed using a ...

Closed-form Likelihoods for Stochastic Differential Equation Growth Models

Canadian Journal of Statistics (2010)

Robert Paige and Edward Allen

The authors derive closed-form expressions for the full, profile, conditional and modified profile likelihood functions for a class of random ...

The Hodrick-prescott Filter: A Special Case of Penalized Spline Smoothing

Electronic Journal of Statistics (2010)

Robert Paige and A. A. Trindade

We prove that the Hodrick-Prescott Filter (HPF), a commonly used method for smoothing econometric time series, is a special case ...

Variance Reduction for Kernel Estimators in Clustered/longitudinal Data Analysis

Journal of Statistical Planning and Inference (2010)

Ming-Yen Cheng, Robert Paige, Shan Sun and Ke Yan

We develop a variance reduction method for the seemingly unrelated (SUR) kernel estimator of Wang (2003). We show that the ...

A Habitat-Based Model for the Spread of Hantavirus between Reservoir ...

Journal of Theoretical Biology (2009)

Linda J. S. Allen, Curtis L. Wesley, Robert D. Owen, Douglas G. Goodin, et al.

New habitat-based models for spread of hantavirus are developed which account for interspecies interaction. Existing habitat-based models do not consider ...

Microhabitat Characteristics of Akodon Montensis, a Reservoir for Hantavirus, and ...

Journal of Vector Ecology (2009)

Douglas G. Goodin, Robert Paige, Robert D. Owen, Kabita Ghimire, et al.

Hantaviruses may cause serious disease when transmitted to humans by their rodent hosts. Since their emergence in the Americas in ...

Saddlepoint-based Bootstrap Inference for Quadratic Estimating Equations

Scandinavian Journal of Statistics (2009)

Robert Paige, A. Alexandre Trindade and P. Harshini Fernando

We propose an easy to implement method for making small sample parametric inference about the root of an estimating equation ...

Variance Reduction in Smoothing Splines

Scandinavian Journal of Statistics (2009)

Robert Paige, Shan Sun and Keyi Wang

We develop a variance reduction method for smoothing splines. For a given point of estimation, we define a variance-reduced spline ...

Practical Small Sample Inference for Single Lag Subset Autoregressive Models

Journal of Statistical Planning and Inference (2008)

Robert Paige and A. Alexandre Trindade

We propose a method for saddlepoint approximating the distribution of estimators in single lag subset autoregressive models of order one. ...

Robust Inference in Conditionally Linear Nonlinear Regression Model

Scandinavian Journal of Statistics (2008)

Robert Paige and P. Harshini Fernando

We consider robust methods of likelihood and frequentist inference for the nonlinear parameter, say α, in conditionally linear nonlinear regression ...