MEDseq: Mixtures of Exponential-Distance Models with Covariates

MEDseq v1.1.1 - (4^th release [patch update]: 2020-05-12)

Maintenance release for compatibility with R 4.0.0 - minor edits.
summary.MEDseq gains the printing-related arguments
classification=TRUE, parameters=FALSE, and gating=FALSE.
x$params$lambda now inherits the MEDlambda class,
with its own print method as per x$params$theta.
x$params$tau now has informative dimnames.
Minor changes when supplying x.axis to plot.MEDseq(..., type="gating").
Documentation, vignette, examples, and references improvements.
Added rmarkdown to Suggests:.
Reformatted package startup message.

Significant efficiency gains when ignoring duplicates in the presence of weights:
- before, unique cases were defined as unique sequence/covariates/weight combinations,
- now, cases with different weights that are otherwise duplicates are treated as duplicates.
MEDseq_stderr is provided for computing the standard errors of the
coefficients for the covariates in the gating network via either the
weighted likelihood bootstrap or jackknife methods.
Small robustifications in the presence of empty components.
Fixed get_MEDseq_results when what="MAP" and non-noise models are chosen.
Fixed bug related to the colours used in the vignette plots.
Odds ratios now returned (and printed) when calling summary on x$gating.
Cosmetic fixes to plot.MEDseq when type="clusters" for small sample sizes.
Other small cosmetic plotting & reference-formatting changes.
Spell-checking of documentation and fixes to donttest examples.