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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... -
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... -
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... -
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.... -
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... -
dedup_wf_001--2750e85e2172ef0fd5ba645e438e6c50
Actuarial practitioners now have access to multiple sources of insurance data corresponding to various situations: multiple business lines, umbrella coverage, multiple hazards,... -
Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework
Multi-dimensional data constituted by measurements along multiple axes have emerged across many scientific areas such as genomics and cancer surveillance. A common objective is... -
I-Optimal Design of Mixture Experiments
© 2016, © American Statistical Association. In mixture experiments, the factors under study are proportions of the ingredients of a mixture. The special nature of the factors... -
Easily Parallelizable and Distributable Class of Algorithms for Structured Sp...
Many statistical learning problems can be posed as minimization of a sum of two convex functions, one typically a composition of non-smooth and linear functions. Examples... -
dedup_wf_001--fb6a32a16af5f4eb48235f765bf30689
© 2018, American Statistical Association. We consider a statistical model for directed network formation that features both node-specific parameters that capture degree... -
dedup_wf_001--05329493e4c2b3adc91e6f655708daa9
In applications of multivariate finite mixture models, estimating the number of unknown components is often difficult. We propose a bootstrap information criterion, whereby we... -
Bayesian hierarchical joint modeling using skew-normal/independent distributions
The multiple longitudinal outcomes collected in many clinical trials are often analyzed by multilevel item response theory (MLIRT) models. The normality assumption for the... -
Estimating a Parametric Component Lifetime Distribution from a Collection of ...
Maintenance data can be used to make inferences about the lifetime distribution of system components. Typically, a fleet contains multiple systems. Within each system, there is... -
Mini-Batch Metropolis–Hastings With Reversible SGLD Proposal
Traditional Markov chain Monte Carlo (MCMC) algorithms are computationally intensive and do not scale well to large data. In particular, the Metropolis–Hastings (MH) algorithm... -
Selection of terms in random coefficient regression models
The selection of suitable terms in random coefficient regression models is a challenging problem to practitioners. Although many techniques, ranging from those with a...
