In this paper we propose two bootstrap goodness of fit tests for the log-gamma distribution with three parameters, location, scale and shape. These tests are built using the properties of this distribution family and are based on the sample correlation coefficient which has the property of...

Ranking data appear in everyday life and arise in many fields of study such as marketing, psychology and politics. Very often, the key objective of analyzing and modeling ranking data is to identify underlying factors that affect the individuals’ choice behavior. Factor analysis for ranking...

We consider the treatment comparison problem in a general high-dimensional regression setting. In this article, we propose a nonparametric estimation approach based on partial sliced inverse regression (SIR) (Chiaromonte et al. in Ann Stat 30:475–497, <CitationRef CitationID="CR4">2002</CitationRef>) and an extension of partial inverse...</citationref>

In this manuscript we introduce R package <Emphasis FontCategory="NonProportional">Compounding for dealing with continuous distributions obtained by compounding continuous distributions with discrete distributions. We demonstrate its use by computing values of cumulative distribution function, probability density function, quantile...</emphasis>

The noncentral gamma distribution can be viewed as a generalization of the noncentral chi-squared distribution and it can be expressed as a mixture of a Poisson density function with a incomplete gamma function. The noncentral gamma distribution is not available in free conventional statistical...

This paper investigates a semi-parametric model for functional data, based on partial linear ideas. A methodology is developped for testing the linear component of such a functional partial linear model. The behavior of the test is studied through some finite simulated samples before being...

This paper focuses on a procedure to test for structural changes in the first two moments of a time series, when no information about the process driving the breaks is available. We model the series as a finite-order auto-regressive process plus an orthogonal Bernstein polynomial to capture...

Binary data represent a very special condition where both measures of distance and co-occurrence can be adopted. Euclidean distance-based non-hierarchical methods, like the k-means algorithm, or one of its versions, can be profitably used. When the number of available attributes increases the...

Classification of samples into two or multi-classes is to interest of scientists in almost every field. Traditional statistical methodology for classification does not work well when there are more variables (p) than there are samples (n) and it is highly sensitive to outlying observations. In...

Efficiency and robustness are two essential concerns on statistical estimation. Unfortunately, it was widely accepted that there existed a contradiction between achieving efficiency and robustness simultaneously. For parametric models with complete data, the minimum Hellinger distance estimation...