In this paper we show how Perl, an expressive and extensible high-level programming language, with network and ob ject-oriented programming support, can be used in processing data for statistics and statistical computing. The paper is organized in two parts. In Part I, we introduce the Perl...

To the worker who only has a hammer, we are told, everything looks like a nail. Solutions to applied statistical problems are framed by the limitations imposed by statistical computing packages and languages. For better or worse, we can do what the packages do; we cannot do what the packages...

This manual details the implementation of the profile matching techniques introduced in Robust Estimation of Air-Borne Particulate Matter (Wiens, Florence and Hiltz, Environmetrics, 2001 - included as an appendix). The program consists of a collection of functions written in S. It runs in...

In this paper, we present a spectral analysis method based upon least square approximation. Our method deals with nonuniform sampling. It provides meaningful phase information that varies in a predictable way as the samples are shifted in time. We compare least square approximations of real and...

The mimR package for graphical modelling in R is introduced. We present some facilities of mimR, namely those relating specifying models, editing models, fitting models and doing model search. We also discuss the entities needed for flexible graphical modelling in terms of an ob ject structure....

In their'70 paper titled "Mean and Variance Control Chart Limits Based on a Small Number of Subgroups" (Journal of Quality Technology, Volume 2, Number 1, pp. 9-16), Yang and Hillier originally derived equations for calculating the factors required to determine second stage short run control...

A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers with specified intercorrelation is proposed. The procedure works with positive and non-positive definite population correlation matrix. A SAS module is also provided to run the procedure.

In this paper we introduce and illustrate the use of an S-PLUS set of functions to fit M-type smoothing splines with the smoothing parameter chosen by a robust criterion (either a robust version of cross-validation or a robust version of Mallows's Cp ). The main reference is: Cantoni, E. and...

Robust statistical methods are designed to work well when classical assumptions, typically normality and/or the lack of outliers, are violated. Almost everyone agrees on the value of robust statistical procedures. Nonetheless, after more than 40 years and thousands of papers, few robust methods...