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dedup_wf_001--30c077d2fc8c7cca7a8ed3c9be419230
We study herein an autoregressive model with spatially correlated error terms and missing data. A logistic regression model with completely observed covariates is used to model... -
Bivariate negative binomial regression model with excess zeros and right cens...
We propose a bivariate hurdle negative binomial (BHNB) regression model with right censoring to model correlated bivariate count data with excess zeros and few extreme... -
dedup_wf_001--cdf832365357a45d6c4c4ea6206c3023
In the existing literature of MCMC diagnostics, we have identified two areas for improvement. Firstly, the density-based diagnostic tools currently available in the literature... -
Variable Selection for Skewed Model-Based Clustering: Application to the Iden...
In sleep research, applying finite mixture models to sleep characteristics captured through multiple data types, including self-reported sleep diary, a wrist monitor capturing... -
The i3+3 design for phase I clinical trials
Purpose: The 3+3 design has been shown to be less likely to achieve the objectives of phase I dose-finding trials when compared with more advanced model-based designs. One major... -
Sparse Vector Autoregressive Modeling
The vector autoregressive (VAR) model has been widely used for modeling temporal dependence in a multivariate time series. For large (and even moderate) dimensions, the number... -
Iterative method for tuning complex simulation code
Tuning a complex simulation code refers to the process of improving the agreement of a code calculation with respect to a set of experimental data by adjusting parameters... -
Volatility Martingale Difference Divergence Matrix and Its Application to Dim...
In this article, we propose the so-called volatility martingale difference divergence matrix (VMDDM) to quantify the conditional variance dependence of a random vector Y∈Rp... -
Testing for Uncorrelated Residuals in Dynamic Count Models With an Applicatio...
This article proposes new model checks for dynamic count models. Both portmanteau and omnibus-type tests for lack of residual autocorrelation are considered. The resulting test... -
Multiple regression model averaging and the focused information criterion wit...
We consider multiple regression (MR) model averaging using the Focused Informati on Criterion (FIC). Our approach is motivated by the problem of implementing a mean-variance... -
dedup_wf_001--a75b6378752be8b8617b919c58dcd8f9
Despite the popularity of the general linear mixed model for data analysis, power and sample size methods and software are not generally available for commonly used test... -
Embracing the Blessing of Dimensionality in Factor Models
Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the... -
A new estimation method for continuous threshold expectile model
The continuous threshold expectile regression model could capture the effect of a covariate on the response variable with two different straight lines, while intersecting an... -
dedup_wf_001--104bd21b45fed5b4f4998c5a7bb60fb2
A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on... -
dedup_wf_001--e1900d96e629dac7d6dc7153d3dc773b
The accurate estimation of an individual's usual dietary intake is an important topic in nutritional epidemiology. This paper considers the best linear unbiased predictor (BLUP)... -
Dynamic Visualization and Fast Computation for Convex Clustering via Algorith...
Convex clustering is a promising new approach to the classical problem of clustering, combining strong performance in empirical studies with rigorous theoretical foundations.... -
Single index based CoVaR with very high dimensional covariates
Systemic risk analysis reveals the interdependencies of risk factors especially in tail event situations. In applications the focus of interest is on capturing joint tail... -
On Design Orthogonality, Maximin Distance, and Projection Uniformity for Comp...
Space-filling designs are widely used in both computer and physical experiments. Column-orthogonality, maximin distance, and projection uniformity are three basic and popular... -
dedup_wf_001--54e7741cb02c4932539dc6960e846e1a
Rapid sequential comparison between the longitudinal pattern of a given subject and a target pattern has become increasingly important in modern scientific research for... -
Threshold Regression With a Threshold Boundary
This article studies computation, estimation, inference, and testing for linearity in threshold regression with a threshold boundary. We first put forward a new algorithm to...
