In this paper, three sampling-estimating strategies involving linear, balanced and modified systematic sampling are considered for the estimation of a finite population total in the presence of parabolic trend. Using appropriate super-population models, their performances are evaluated. For...

This article presents a continuous-time Bayesian model for analyzing durations of behavior displays in social interactions. Duration data of social interactions are often complex because of repeated behaviors (events) at individual or group (e.g. dyad) level, multiple behaviors (multistates),...

Exact, resampling, and Pearson type III permutation methods are provided to compute probability values for Piccarreta's nominal-ordinal index of association. The resampling permutation method provides good approximate probability values based on the proportion of resampled test statistic values...

The purpose of this article is to compare efficiencies of several cluster randomized designs using the method of quantile dispersion graphs (QDGs). A cluster randomized design is considered whenever subjects are randomized at a group level but analyzed at the individual level. A prior knowledge...

This article is concerned with the analysis of a random sample from a binomial distribution when all the outcomes are zero (or unity). We discuss how elicitation of the prior can be reduced to asking the expert whether (and which of) the so-called borderline or equilibrium priors are plausible.

A Bayesian network (BN) is a probabilistic graphical model that represents a set of variables and their probabilistic dependencies. Formally, BNs are directed acyclic graphs whose nodes represent variables, and whose arcs encode the conditional dependencies among the variables. Nodes can...

This paper develops a fully nonparametric method for estimating value-at-risk based on the adaptive volatility estimation and the nonparametric quantile estimation. The proposed method is simple, fast and easy to implement. We evaluated its numerical performance on the basis of Monte Carlo study...

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a...

In a recent volume of this journal, Holden [Testing the normality assumption in the Tobit Model, J. Appl. Stat. 31 (2004) pp. 521-532] presents Monte Carlo evidence comparing several tests for departures from normality in the Tobit Model. This study adds to the work of Holden by considering...

When VAR models are used to predict future outcomes, the forecast error can be substantial. Through imposition of restrictions on the off-diagonal elements of the parameter matrix, however, the information in the process may be condensed to the marginal processes. In particular, if the...