Package: ideq
Title: Bayesian Dynamic Spatio-Temporal Models, Including the
        Integrodifference Equation Model
Version: 0.1.4
Authors@R: 
  c(person("Easton", "Huch", email = "easton.huch@gmail.com", role = c("aut", "cre")),
    person("Robert", "Richardson", email = "richardson@stat.byu.edu", rol = ("ths")))
Description: In contrast to other methods of modeling spatio-temporal data,
  dynamic spatio-temporal models (DSTMs) directly model the dynamic
  data-generating process.
  'ideq' supports two main classes of DSTMs:
  (1) empirical orthogonal function (EOF) models and
  (2) integrodifference equation (IDE) models.
  EOF models do not directly use any spatial information;
  instead, they make use of observed relationships in the data
  (the principal components) to model the underlying process.
  In contrast, IDE models are based on diffusion dynamics and the process
  evolution is governed by a (typically Gaussian) redistribution kernel.
  Both types have a variety of options for specifying the model components,
  including the process matrix, process error, and observation error.
  The classic reference for DSTMs is
  Noel Cressie and Christopher K. Wikle (2011, ISBN:978-0471692744).
  For IDE models specifically, see
  Christopher K. Wikle and Noel Cressie (1999, <https://www.jstor.org/stable/2673587>)
  and 
  Christopher K. Wikle (2002, <doi:10.1191/1471082x02st036oa>).
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
LinkingTo: Rcpp, RcppArmadillo, rgen
Imports: Rcpp, matrixcalc, pdist, mvtnorm
BugReports: https://github.com/eastonhuch/ideq/issues
NeedsCompilation: yes
Packaged: 2019-12-19 05:06:31 UTC; easton
Author: Easton Huch [aut, cre],
  Robert Richardson [ths]
Maintainer: Easton Huch <easton.huch@gmail.com>
Repository: CRAN
Date/Publication: 2019-12-19 22:20:02 UTC
Built: R 3.6.0; x86_64-apple-darwin15.6.0; 2019-12-20 19:53:12 UTC; unix
Archs: ideq.so.dSYM
