Package: dynr
Date: 2016-06-07
Title: Dynamic Modeling in R
Authors@R: c(person("Lu", "Ou", role=c("aut", "cre"), email="lzo114@psu.edu"),
    person(c("Michael", "D."), "Hunter", role="aut"),
    person("Sy-Miin", "Chow", role="aut"))
Author: Lu Ou [aut, cre],
    Michael D. Hunter [aut],
    Sy-Miin Chow [aut]
Maintainer: Lu Ou <lzo114@psu.edu>
Depends: R (>= 3.0.0), methods, ggplot2
Imports: numDeriv, xtable, latex2exp, grid, reshape2, plyr
Suggests: testthat, roxygen2 (>= 3.1)
Description: Dynamic modeling of all kinds in R. These include models of processes in 
    discrete time or continuous time.  They also include processes that are linear
    or nonlinear. Latent variables can be continuous (e.g. state space models) or 
    discrete (e.g. regime-switching models). The general approach involves maximum
    likelihood estimation of single- and multi-subject models of latent time series
    with the extended Kalman filter and Kim filter. The user provides recipes and
    data which are combined into a model that is then cooked to obtain free parameter
    estimates.
SystemRequirements: GNU make
NeedsCompilation: yes
License: Apache License (== 2.0)
LazyLoad: yes
LazyData: yes
Collate: 'dynrData.R' 'dynrRecipe.R' 'dynrModelInternal.R'
        'dynrModel.R' 'dynrCook.R' 'dynrPlot.R' 'dynrFuncAddress.R'
        'dynrVersion.R' 'dataDoc.R'
Version: 0.1.7
Packaged: 2016-06-07 18:33:18 UTC; mhunter
Repository: CRAN
Date/Publication: 2016-06-09 20:41:13
