Abstract:
This paper introduces the elliptic package of R routines, for numerical calculation of elliptic and related functions. Elliptic functions furnish interesting and instructive examples of many ideas of complex analysis, and the package illustrates these numerically and visually. A statistical application in fluid mechanics is presented.

Abstract:
The R package MixSim is a new tool that allows simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of MixSim, there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models. All features of the package are illustrated in great detail. The utility of the package is highlighted through a small comparison study of several popular clustering algorithms.

Abstract:
We present two natural generalizations of the multinomial and multivariate binomial distributions, which arise from the multiplicative binomial distribution of Altham (1978). The resulting two distributions are discussed and we introduce an R package, MM, whichincludes associated functionality.

Abstract:
stpp is an R package for analyzing, simulating and displaying space-time point patterns. It covers many of the models encountered in applications of point process methods to the study of spatio-temporal phenomena. The package also includes estimators of the space-time inhomogeneous K-function and pair correlation function. stpp is the first dedicated unified computational environment in the area of spatio-temporal point processes. In this paper we describe space-time point processes and introduce the package stpp to new users.

Abstract:
We describe in these GLA2011 proceedings the software package LArSoft, a toolkit to perform simulation, analysis and reconstruction with the Liquid Argon (LAr) Time Projection Chambers (TPCs) within the US program of proposed detectors. We demonstrate that LArSoft is a fast-maturing, sophisticated package which has taken on important analyses already, and which stands ready to be adopted by as many as five Liquid Argon Time Projection Chambers.

Abstract:
Zero-inflation problem is very common in ecological studies as well as other areas. Nonparametric regression with zero-inflated data may be studied via the zero-inflated generalized additive model (ZIGAM), which assumes that the zero-inflated responses come from a probabilistic mixture of zero and a regular component whose distribution belongs to the 1-parameter exponential family. With the further assumption that the probability of non-zero-inflation is some monotonic function of the mean of the regular component, we propose the constrained zero-inflated generalized additive model (COZIGAM) for analyzingzero-inflated data. When the hypothesized constraint obtains, the new approach provides a unified framework for modeling zero-inflated data, which is more parsimonious and efficient than the unconstrained ZIGAM. We have developed an R package COZIGAM which contains functions that implement an iterative algorithm for fitting ZIGAMs and COZIGAMs to zero-inflated data basedon the penalized likelihood approach. Other functions included in the package are useful for model prediction and model selection. We demonstrate the use of the COZIGAM package via some simulation studies and a real application.

Abstract:
Our ltsa package implements the Durbin-Levinson and Trench algorithms and provides a general approach to the problems of fitting, forecasting and simulating linear time series models as well as fitting regression models with linear time series errors. For computational efficiency both algorithms are implemented in C and interfaced to R. Examples are given which illustrate the efficiency and accuracy of the algorithms. We provide a second package FGN which illustrates the use of the ltsa package with fractional Gaussian noise (FGN). It is hoped that the ltsa will provide a base for further time series software.

Abstract:
This is a sample produced using chet. This package is inspired by Paul Ginsparg's harvmac, but uses LaTeX2e instead of TeX. The commands provided are to be used as faster alternatives to LaTeX2e's default environments (which can all still be used with chet).

Abstract:
This paper describes the package PtProcess which uses the R statistical language. The package provides a unified approach to fitting and simulating a wide variety of temporal point process or temporal marked point process models. The models are specified by an intensity function which is conditional on the history of the process. The user needs to provide routines for calculating the conditional intensity function. Then the package enables one to carry out maximum likelihood fitting, goodness of fit testing, simulation and comparison of models. The package includes the routines for the conditional intensity functions for a variety of standard point process models. The package is intended to simplify the fitting of point process models indexed by time in much the same way as generalized linear model programs have simplified the fitting of various linear models. The primary examples used in this paper are earthquake sequences but the package is intended to have a much wider applicability.