Package: DSSP 0.1.1.9000

DSSP: Implementation of the Direct Sampling Spatial Prior

Draw samples from the direct sampling spatial prior model as described in G. White, D. Sun, P. Speckman (2019) <arxiv:1906.05575>. The basic model assumes a Gaussian likelihood and derives a spatial prior based on thin-plate splines.

Authors:Gentry White [aut, cre], Rex Parsons [aut]

DSSP_0.1.1.9000.tar.gz
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DSSP.pdf |DSSP.html✨
DSSP/json (API)
NEWS

# Install 'DSSP' in R:

install.packages('DSSP', repos = c('https://gentrywhite.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gentrywhite/dssp/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

3.70 score 1 stars 6 scripts 141 downloads 6 exports 47 dependencies

Last updated 2 years agofrom:a4b48f16ea. Checks:OK: 1 NOTE: 8. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 07 2024
R-4.5-win-x86_64	NOTE	Nov 07 2024
R-4.5-linux-x86_64	NOTE	Nov 07 2024
R-4.4-win-x86_64	NOTE	Nov 07 2024
R-4.4-mac-x86_64	NOTE	Nov 07 2024
R-4.4-mac-aarch64	NOTE	Nov 07 2024
R-4.3-win-x86_64	NOTE	Nov 07 2024
R-4.3-mac-x86_64	NOTE	Nov 07 2024
R-4.3-mac-aarch64	NOTE	Nov 07 2024

Exports:DSSP make.M sample.delta sample.eta sample.nu tps.rbf

Dependencies:abind backports brio callr checkmate cli crayon desc diffobj digest distributional ellipse evaluate fansi fftwtools fs generics glue jsonlite lattice lifecycle magrittr matrixStats mcmcse numDeriv pillar pkgbuild pkgconfig pkgload posterior praise processx ps R6 Rcpp RcppArmadillo rlang rprojroot rust sp tensorA testthat tibble utf8 vctrs waldo withr

DSSP: Direct Sampling Spatial Prior

Rendered fromdssp.Rmdusingknitr::rmarkdownon Nov 07 2024.

Last update: 2022-07-19
Started: 2022-01-19

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Implementation of the Direct Sampling Spatial Prior	DSSP-package
DSSP	DSSP
Precision Matrix Function	make.M
Diagnostic, Density and Contour Plots	plot.dsspMod
Predictions from a model with new data.	predict.dsspMod
Get residuals from 'dsspMod' model	residuals.dsspMod
Function to sample from the posterior of the variance parameter	sample.delta
Function to sample from the posterior of the smoothing parameter eta conditioned on the data y.	sample.eta
Function to sample from the posterior of the spatial effects	sample.nu
Summarise a 'dsspMod' model	summary.dsspMod
TPS radial basis function	tps.rbf