Description: Do data management functions common in real-time monitoring (also called: ecological momentary assessment, experience sampling, micro-longitudinal) data, including creating power curves for multilevel data, centering on participant means and merging event-level data into momentary data sets where you need

Description: Do data management functions common in real-time monitoring (also called: ecological momentary assessment, experience sampling, micro-longitudinal) data, including creating power curves for multilevel data, centering on participant means and merging event-level data into momentary data sets where you need the events to correspond to the nearest data point in the momentary data. This is VERY early release software, and more features will be added over time.
Imports: DataCombine,ggplot2,lmerTest, sjstats (>= 0.10.2)

Imports: DataCombine,ggplot2,lmerTest, sjstats (>= 0.10.2), anytime,
Packaged: 2021-10-31 12:59:29 UTC; evankleiman

Title: Evolutionary Monte Carlo (EMC) algorithm
Description: Random walk Metropolis, Metropolis Hasting, parallel tempering, evolutionary Monte Carlo, temperature ladder construction and placement
Packaged: Fri Jan 11 13:48:55 2008; gopi

Description: Random walk Metropolis, Metropolis Hasting, parallel tempering, evolutionary Monte Carlo, temperature ladder construction and placement.
Packaged: Mon Feb  4 17:35:12 2008; gopi

Depends: R (>= 1.9.0), mvtnorm, MASS, graphics
Description: random walk Metropolis, Metropolis Hasting, parallel tempering, evolutionary Monte Carlo, temperature ladder construction and placement

Title: Evolutionary Monte Carlo (EMC) methods for clustering
Depends: R (>= 1.9.0), MASS, mclust, EMC
Description: evolutionary Monte Carlo methods for clustering, temperature ladder construction and placement
Packaged: Wed Feb  6 00:40:41 2008; gopi

Description: evolutionary Monte Carlo methods for clustering,
temperature ladder construction and placement. For mclust see

Title: Evolutionary Monte Carlo (EMC) Methods for Clustering
Description: Evolutionary Monte Carlo methods for clustering, temperature
ladder construction and placement. This package implements methods
The paper above introduced probabilistic genetic-algorithm-style crossover
moves for clustering. The paper applied the algorithm to several clustering
problems including Bernoulli clustering, biological sequence motif
clustering, BIC based variable selection, mixture of Normals clustering,
and showed that the proposed algorithm performed better both as a sampler
and as a stochastic optimizer than the existing tools, namely, Gibbs sampling,
``split-merge'' Metropolis-Hastings algorithm, K-means clustering, and the
MCLUST algorithm (in the package 'mclust').