Finite mixture modeling approach is widely used for the analysis of bimodal or multimodal data that are individually observed in many situations. However, in some applications, the analysis becomes substantially challenging as the available data are grouped into categories. In this work, we...

We report evidence that boundary solutions can cause a bias in the estimate of the probability of informed trading (PIN). We develop an algorithm to overcome this bias and use it to estimate PIN for nearly 80,000 stock-quarters between 1993 and 2004. We obtain two sets of PIN estimates by using...

This paper studies modeling of nonignorable nonresponse in panel surveys. A class of sequential conditional logistic models for nonresponse is considered. Model-based maximum likelihood estimation and imputation are used for estimating population proportions. Various models are evaluated, and...

In this paper we propose a general framework to deal with datasets where a binary outcome is subject to misclassification and, for some sampling units, neither the error-prone variable of interest nor the covariates are recorded. A model to describe the observed data is for-malized and eficient...

Good estimates of HIV prevalence are important for policy makers in order to plan control programs and interventions. Although population-based surveys are now considered the "gold standard" to monitor the HIV epidemic, they are usually plagued by problems of nonignorable nonresponse. This paper...

This paper investigates formation of expected longevity in an elderly popu- lation. We use Italian data from the early (2004) release of the Survey of Health, Ageing and Retirement in Europe (SHARE). The SHARE provides a numerical measure for subjective survival probability (SSP). To assess...

This paper develops a finite mixture distribution analysis of Beauty- Contest data obtained from diverse groups of experiments. ML estimation using the EM approach provides estimates for the means and variances of the component distributions, which are common to all the groups, and estimates of...

Combination of forecasts from survey data is complicated by the frequent entry and exit of individual forecasters which renders conventional least squares regression approaches infeasible. We explore the consequences of this issue for existing combination methods and propose new methods for...