RMC_overview: Package Description

In RMC: Functions for fitting Markov models

Description

RMC is a package that fits and predicts reversible Markov models with a particular parameterisation described in Foster et al (2009). The core work-horse of the estimation routines is the function RMC.mod, but also see MVfill for (single) imputing of associated chained covariates, and RMC.pred for prediction of the local area stationary distribution.

Also contained in the RMC package is a bunch of methods that provide graphical diagnostics for this class of models (see Foster and Bravington 2010). This is performed through the functions diagnos for calculation of residuals, diagnos.envel for calculation of residuals and simulation envelopes, and hrplot for subsequent plotting.

Author(s)

Scott D. Foster

References

Foster, S.D., Bravington, M.V., Williams, A., Althaus, F, Laslett, G.M., and Kloser, R.J. (2008) Analysis and prediction of faunal distributions from video and multi-beam sonar data using Markov models. Environmetrics, 20: 541-560.

Foster, S.D. and Bravington, M.V. (2009) Graphical Diagnostics for Markov Models for Categorical Data. Journal of Computational and Graphical Statistics, to appear.

See Also

diagnos, diagnos.envel, examplesForDiagnostics, hrplot, MVfill, RMC.mod, RMC.pred.

RMC documentation built on May 30, 2017, 2:55 a.m.