CRAN/E | spCP

spCP

Spatially Varying Change Points

Installation

About

Implements a spatially varying change point model with unique intercepts, slopes, variance intercepts and slopes, and change points at each location. Inference is within the Bayesian setting using Markov chain Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), probit or Tobit link and the five spatially varying parameter are modeled jointly using a multivariate conditional autoregressive (MCAR) prior. The MCAR is a unique process that allows for a dissimilarity metric to dictate the local spatial dependencies. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in the corresponding paper on arXiv by Berchuck et al (2018): "A spatially varying change points model for monitoring glaucoma progression using visual field data", .

Key Metrics

Version 1.3
R ≥ 3.0.2
Published 2022-09-05 761 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks spCP results

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Maintainer

Maintainer

Samuel I. Berchuck

Authors

Samuel I. Berchuck

aut / cre

Material

Reference manual
Package source

Vignettes

spCP-example

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

spCP archive

Depends

R ≥ 3.0.2

Imports

graphics
grDevices
msm ≥ 1.0.0
mvtnorm ≥ 1.0-0
Rcpp ≥ 0.12.9
stats
utils

Suggests

coda
classInt
knitr
rmarkdown
womblR ≥ 1.0.3

LinkingTo

Rcpp
RcppArmadillo ≥ 0.7.500.0.0