Estimation and Prediction for Remote Effects Spatial Process Models

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) . Sample code for working with the RESP model is available at < https://jmhewitt.github.io/research/resp_example>.


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install.packages("telefit")

1.0.0 by Joshua Hewitt, 6 months ago


Browse source code at https://github.com/cran/telefit


Authors: Joshua Hewitt


Documentation:   PDF Manual  


GPL-3 license


Imports abind, coda, cowplot, doRNG, dplyr, fields, itertools, mvtnorm, raster, scoringRules, stringr, foreach, ggplot2, gtable, reshape2, scales, sp, SDMTools

Suggests testthat

Linking to Rcpp, RcppArmadillo, RcppEigen

System requirements: A system with a recent-enough C++11 compiler (such as g++-4.8 or later).


See at CRAN