In this paper, we suggest a new randomized response model useful for collecting information on quantitative sensitive variables such as drug use and income. The resultant estimator has been found to be better than the usual additive randomized response model. An interesting feature of the...

Control charts are one of the widest used techniques in statistical process control. In Phase I, historical observations are analysed in order to construct a control chart. Because of the existence of multiple outliers that are undetected by control charts such as Hotelling's T2 due to the...

Two sample surveys of Post-Docs were planned and carried out at the University of Ferrara in 2004 and 2007 aimed at determining the professional status of Post-Docs, the relationship between their PhD education and employment, and their satisfaction with certain aspects of the education and...

Count data series with extra zeros relative to a Poisson distribution are common in many biomedical applications. A score test is presented to assess whether the zero-inflation problem is significant to warrant the analysis by the more complex zero-inflated Poisson autoregression model. The...

An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A...

This article presents a novel shape-invariant modeling approach to quasi-periodic data. We propose a dynamic semiparametric method that estimates the common cycle shape in a nonparametric way and the individual phase and amplitude variability in a parametric way. An efficient algorithm to...

In epidemiologic studies where the outcome is binary, the data often arise as clusters, as when siblings, friends or neighbors are used as matched controls in a case-control study. Conditional logistic regression (CLR) is typically used for such studies to estimate the odds ratio for an exposure...

The development of new technologies to measure gene expression has been calling for statistical methods to integrate findings across multiple-platform studies. A common goal of microarray analysis is to identify genes with differential expression between two conditions, such as treatment versus...

The first two stages in modelling times series are hypothesis testing and estimation. For long memory time series, the second stage was studied in the paper published in [M. Boutahar et al., Estimation methods of the long memory parameter: monte Carlo analysis and application, J. Appl. Statist....

Data envelopment analysis (DEA) is a deterministic econometric model for calculating efficiency by using data from an observed set of decision-making units (DMUs). We propose a method for calculating the distribution of efficiency scores. Our framework relies on estimating data from an...