Package: DSSP 0.1.1
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:
DSSP_0.1.1.tar.gz
DSSP_0.1.1.tar.gz(r-4.5-noble)DSSP_0.1.1.tar.gz(r-4.4-noble)
DSSP_0.1.1.tgz(r-4.4-emscripten)DSSP_0.1.1.tgz(r-4.3-emscripten)
DSSP.pdf |DSSP.html✨
DSSP/json (API)
NEWS
# Install 'DSSP' in R: |
install.packages('DSSP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gentrywhite/dssp/issues
Last updated 2 years agofrom:dde20f00e5. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 13 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 13 2024 |
Exports:DSSPmake.Msample.deltasample.etasample.nutps.rbf
Dependencies:abindbackportsbriocallrcheckmateclicrayondescdiffobjdigestdistributionalellipseevaluatefansifftwtoolsfsgenericsgluejsonlitelatticelifecyclemagrittrmatrixStatsmcmcsenumDerivpillarpkgbuildpkgconfigpkgloadposteriorpraiseprocessxpsR6RcppRcppArmadillorlangrprojrootrustsptensorAtestthattibbleutf8vctrswaldowithr
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 |