Package: telefit
Type: Package
Title: Estimation and Prediction for Remote Effects Spatial Process
        Models
Version: 1.0.1
Date: 2019-02-15
Author: Joshua Hewitt
Maintainer: Joshua Hewitt <joshua.hewitt@colostate.edu>
Description: Implementation of the remote effects spatial process (RESP) model for teleconnection.  The RESP model is a geostatistical model that allows a spatially-referenced variable (like average precipitation) to be influenced by covariates defined on a remote domain (like sea surface temperatures).  The RESP model is introduced in Hewitt et al. (2018) <doi:10.1002/env.2523>.  Sample code for working with the RESP model is available at <https://jmhewitt.github.io/research/resp_example>. This material is based upon work supported by the National Science Foundation under grant number AGS 1419558. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
License: GPL-3
Depends: R (>= 3.0.2)
Imports: abind, coda, cowplot, doRNG, dplyr, fields, itertools,
        mvtnorm, raster, scoringRules, stringr, foreach, ggplot2,
        gtable, reshape2, scales, sp, SDMTools
LinkingTo: Rcpp (>= 0.12.4), RcppArmadillo, RcppEigen (>= 0.3.3.3.1)
RoxygenNote: 6.1.1
Suggests: testthat
LazyData: true
SystemRequirements: A system with a recent-enough C++11 compiler (such
        as g++-4.8 or later).
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2019-02-15 22:34:18 UTC; pointdex
Repository: CRAN
Date/Publication: 2019-02-18 10:50:03 UTC
Built: R 3.4.4; x86_64-w64-mingw32; 2019-04-25 22:25:07 UTC; windows
Archs: i386, x64
