Categorization is often needed for clinical decision making when dealing with diagnostic (prognostic) biomarkers and a binary outcome (true disease status). Four common methods used to dichotomize a continuous biomarker X are compared: the minimum P-value, the Youden index, the concordance...

An estimation framework and a user-friendly software implementation are described for maximum likelihood estimation of panel data models with random effects, a spatially lagged dependent variable and spatially and serially correlated errors. This specification extends static panel data models in...

Identification of active factors in supersaturated designs (SSDs) has been the subject of much recent study. Although several methods have been previously proposed, a solution to the problem beyond one or two active factors still seems to be unsatisfactory. The smoothly clipped absolute...

Option pricing using mixed normal heteroscedasticity models is considered. It is explained how to perform inference and price options in a Bayesian framework. The approach allows to easily compute risk neutral predictive price densities which take into account parameter uncertainty. In an...

To alleviate the computational burden of making the relevant estimation algorithms stable for nonlinear and semiparametric regression models with, particularly, high-dimensional data, a transformation-based method combining sufficient dimension reduction approach is proposed. To this end,...

It is often necessary to test for the presence of seasonal unit roots when working with time series data observed at intervals of less than a year. One of the most widely used methods for doing this is based on regressing the seasonal difference of the series over the transformations of the...

A framework of using t mixture models with fourteen eigen-decomposed covariance structures for the unsupervised learning of heterogeneous multivariate data with possible missing values is designed and implemented. Computationally flexible EM-type algorithms are developed for parameter estimation...

It is well-known that the estimated GARCH dynamics exhibit common patterns. Starting from this fact the Dynamic Conditional Correlation (DCC) model is extended by allowing for a clustering structure of the univariate GARCH parameters. The model can be estimated in two steps, the first devoted to...

Several strategies relying on kriging have recently been proposed for adaptively estimating contour lines and excursion sets of functions under severely limited evaluation budget. The recently released R package KrigInv33URL: http://cran.r-project.org/web/packages/KrigInv/index.html. is...

A judgment post-stratified (JPS) sample is used in order to develop statistical inference for population quantiles and variance. For the pth order of the population quantile, a test is constructed, an estimator is developed, and a distribution-free confidence interval is provided. An unbiased...