R: Mixtures of Exponential-Distance Models with Covariates

# Mixtures of Exponential-Distance Models with Covariates

## Documentation for package ‘MEDseq’ version 1.4.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

MEDseq-package | MEDseq: Mixtures of Exponential-Distance Models with Covariates
biofam | Family life states from the Swiss Household Panel biographical survey
dbs | Compute the Density-based Silhouette
dist_freqwH | Pairwise frequency-Weighted Hamming distance matrix for categorical data
fitted.MEDgating | Predictions from MEDseq gating networks
get_MEDseq_results | Extract results from a MEDseq model
MEDseq | MEDseq: Mixtures of Exponential-Distance Models with Covariates
MEDseq_AvePP | Average posterior probabilities of a fitted MEDseq model
MEDseq_clustnames | Automatic labelling of clusters using central sequences
MEDseq_compare | Choose the best MEDseq model
MEDseq_control | Set control values for use with MEDseq_fit
MEDseq_entropy | Entropy of a fitted MEDseq model
MEDseq_fit | MEDseq: Mixtures of Exponential-Distance Models with Covariates
MEDseq_meantime | Compute the mean time spent in each sequence category
MEDseq_nameclusts | Automatic labelling of clusters using central sequences
MEDseq_news | Show the NEWS file
MEDseq_stderr | MEDseq gating network standard errors
mvad | MVAD: Transition from school to work
plot.MEDseq | Plot MEDseq results
predict.MEDgating | Predictions from MEDseq gating networks
print.MEDseq | MEDseq: Mixtures of Exponential-Distance Models with Covariates
print.MEDseqCompare | Choose the best MEDseq model
print.MEDseqMeanTime | Compute the mean time spent in each sequence category
residuals.MEDgating | Predictions from MEDseq gating networks
summary.MEDseq | MEDseq: Mixtures of Exponential-Distance Models with Covariates
wKModes | Weighted K-Modes Clustering with Tie-Breaking