Title: Massive Hierarchically Data Analysis
Description: Three main functions about analyzing massive data (missing observations are allowed) considered from multiple layers of categories.
Collate: MHDA.R MHDA.plot.R Steps.analysis.R AllClasses.R
Packaged: 2022-03-09 21:09:18 UTC; Administrator

Packaged: 2022-04-20 21:47:15 UTC; Administrator

Packaged: 2022-06-12 14:02:23 UTC; Administrator

Title: Finite Mixture of Hidden Markov Model
Author: Marie Du-Roy-De-Chaumary, Matthieu Marbac and Fabien Navarro
Description: Estimation of the latent states and partition by maximum likelihood. Model can be used for analyzing accelerometer data. In such a case, the latent states corresponds to activity levels and the partition permits to consider heterogeneity within the population. Emission laws are zero-inflated gamma distributions. Their parameters depends on the latent states but not on the partition, to compare the time spent by activity levels between classes. Model description is available in Du Roy de Chaumaray, M. and Marbac, M. and Navarro, F. (2019) <arXiv:1906.01547>.
Imports: Rcpp (>= 0.11.1), methods, parallel, ggplot2, reshape2,
Collate: 'param.R' 'checkinputs.R' 'rmodel.R' 'data.R' 'MHMM.R'
'results.R' 'plot.R' 'smartinit.R' 'viterbi.R' 'MHMMpackage.R'

Title: Tests Controlling the FDR / FWER under Certain Copula Models
person("Jonathan", "von Schroeder", email = "jvs@uni-bremen.de", role = c("aut","cre")),
person("Taras", "Bodnar", email = "bodnar@math.hu-berlin.de", role = "aut"),
person("Jens","Stange", email= "Jens.Stange@wias-berlin.de", role = "aut"))
Description: Implements tests controlling the false discovery rate (FDR) / family-wise error rate (FWER) for some copula models.
Imports: stats, copula, matrixStats, mvtnorm, stabledist, MCMCpack
Author: Jonathan von Schroeder [aut, cre],
Maintainer: Jonathan von Schroeder <jvs@uni-bremen.de>

Title: Multiple Hypotheses Testing for Discrete Data
Description: A Comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling
FWER/FDR for discrete data. In order to make decisions conveniently,  given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha.
Packaged: 2016-10-20 14:20:10 UTC; kaijingzhang