Man pages for rforge/march
Markov Chains

marchComputation of Markovian models for categorical data
march.AICCompute Akaike Information Criterion (AIC). The AIC (Akaike...
march.BICCompute Bayesian Information Criterion (BIC).
march.Dataset-classDataset for march package.
march.dataset.h.extractSequenceExtract a sequence from a dataset.
march.dataset.loadFromDataFrameConstruct a dataset from a data.frame or a matrix.
march.dataset.loadFromFileLoad a dataset from a file.
march.Dcmm-classA Double Chain Markov Model (DCMM).
march.dcmm.constructConstruct a double chain Markov model (DCMM).
march.dcmm.viterbiViterbi algorithm for a DCMM model.
march.Indep-classAn independence model.
march.indep.constructConstruct an independence model (zero-order Markov chain).
march.Mc-classA Markov chain of order >= 1.
march.mc.constructConstruct an homogeneous Markov Chain.
march.Model-classA basic and virtual march model.
march.Mtd-classA Mixture Transition Distribution (MTD) model.
march.mtd.constructConstruct a Mixture Transition Distribution (MTD) model.
march.namemarch.Model name.
march.readLoad a march.Model.
march.summarymarch.Model Summary.
march.thompsonThompson Confidence Intervals for a march.Model.
march.writeSave a march.Model
peweeSong of the Wood Pewee (march dataset format)
pewee_dfSong of the Wood Pewee (data frame format)
pewee_tSong of the Wood Pewee (text format)
sleepSleep disorders (march dataset format)
sleep_dfSleep disorders (data frame format)
rforge/march documentation built on Oct. 7, 2017, 10:46 a.m.