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GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm
Computer experiments, clustering, near-singularity, nugget
2013/6/13
Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in the in...
PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
Profile regression Clustering Dirichlet process mixture model
2013/4/27
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vect...
Iterative bias reduction multivariate smoothing in R: The ibr package
multivariate smoothing L2 boosting thin-plate splines kernel regression R
2011/6/20
In multivariate nonparametric analysis, sparseness of the co-
variates also called curse of dimensionality, forces one to use large smoothing
parameters. This leads to a biased smoother. Instead of ...
Temporal and Spatial Independent Component Analysis for fMRI data sets embedded in a R package
Computation (stat.CO) Medical Physics (physics.med-ph) Applications (stat.AP)
2010/12/17
For statistical analysis of functional Magnetic Resonance Imaging (fMRI) data sets, we propose a data-driven approach based on Independent Component Analysis (ICA) implemented in a new version of the ...
AsympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem
parametric tests and confidence intervals central limit theorem R package
2010/3/18
This paper describes an R package implementing large sample tests and confidence
intervals (based on the central limit theorem) for various parameters. The one and
two sample mean and variance conte...