Distribution function of quadratic forms in normal variables
P. Lafaye de Micheaux <lafaye@dms.umontreal.ca>
Computes the distribution function of quadratic forms in
normal variables using Imhof's method, Davies's algorithm,
Farebrother's algorithm or Liu et al.'s algorithm.

Distribution Function of Quadratic Forms in Normal Variables
Computes the distribution function of quadratic forms in normal variables using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s algorithm.

P. Lafaye de Micheaux <lafaye@unsw.edu.au>

R (>= 3.1), methods, utils, MASS, graphics, stats
Different tools for describing and analysing paired comparison data are presented. Main methods are estimation of products scores according Bradley Terry Luce model. A segmentation of the individual could be conducted on the basis of a mixture distribution approach. The number of classes can be tested by the use of Monte Carlo simulations. This package deals also with multi-criteria paired comparison data.

Composite-likelihood based Analysis of Random Fields
Simone Padoan <simone.padoan@epfl.ch>, Moreno Bevilacqua
<bevilacqua@stat.unipd.it>
The aim of this package is to collect a set of procedures
for the analysis of Random Fields by Composite Likelihood
methods. Spatial analysis often involves dealing with large
dataset. Therefore even simple studies may be too
computationally demanding. Composite likelihood based methods
are emerging as useful tools for mitigating such computational
problems and show satisfactory results when compared with other
techniques such as, for example the tapering method. Moreover,
composite likelihood (and related quantities) have some good
properties similar to those of the standard likelihood.

Simone Padoan <simone.padoan@epfl.ch>, Moreno Bevilacqua
<moreno.bevilacqua@unive.it>

Simone Padoan <simone.padoan@unibg.it>, Moreno Bevilacqua
<moreno.bevilacqua@unibg.it>

Simone Padoan <simone.padoan@stat.unipd.it>, Moreno Bevilacqua
<moreno.bevilacqua@unibg.it>

Simone Padoan <simone.padoan@unibocconi.it>, Moreno Bevilacqua <moreno.bevilacqua@uv.cl>
The aim of this package is to collect a set of procedures for the analysis of Random Fields by Composite Likelihood methods. Spatial analysis often involves dealing with large dataset. Therefore even simple studies may be too computationally demanding. Composite likelihood based methods are emerging as useful tools for mitigating such computational problems and show satisfactory results when compared with other techniques such as, for example the tapering method. Moreover, composite likelihood (and related quantities) have some good properties similar to those of the standard likelihood.
RandomFields, spam, scatterplot3d, fields, mapproj