Constructing spatial density maps of seismic events, such as earthquake hypocentres, is complicated by the fact that events are not located precisely. In this paper, we present a method for estimating density maps from event locations that are measured with error. The estimator is based on the...

Intervention trials such as studies on smoking cessation may observe multiple, discrete outcomes over time. When the outcome is binary, participant observations may alternate between two states over the course of the study. The generalized estimating equation (GEE) approach is commonly used to...

The autoregressive (AR) model is a popular method for fitting and prediction in analyzing time-dependent data, where selecting an accurate model among considered orders is a crucial issue. Two commonly used selection criteria are the Akaike information criterion and the Bayesian information...

To emphasize growth rate analysis, we develop a general method to reparametrize growth curve models to analyze rates of growth for a variety of growth trajectories, such as quadratic and exponential growth. The resulting growth rate models are shown to be related to rotations of growth curves....

Two types of confidence intervals (CIs) and confidence bands (CBs) for the receiver operating characteristic (ROC) curve are studied: pointwise CIs and simultaneous CBs. An optimized version of the pointwise CI with the shortest width is developed. A new ellipse-envelope simultaneous CB for the...

Government policy on employment, transport, and housing often depends on reliable information about spatial variation in commuting flows across a region. Simple commuting rates summarising inter-area flows may not provide a full perspective on the underlying levels of commuting attractivity of...

In this paper, a discrete time series of stock price process is modeled by the two-dimensional lattice-oriented bond percolation system. Percolation theory, as one of statistical physics systems, has brought new understanding and techniques to a broad range of topics in nature and society....

Herein, we propose a fully Bayesian approach to the greenhouse gas emission problem. The goal of this work is to estimate the emission rate of polluting gases from the area flooded by hydroelectric reservoirs. We present models for gas concentration evolution in two ways: first, by proposing...