Package: SpTe2M 1.0.3

Kai Yang

SpTe2M: Nonparametric Modeling and Monitoring of Spatio-Temporal Data

Spatio-temporal data have become increasingly popular in many research fields. Such data often have complex structures that are difficult to describe and estimate. This package provides reliable tools for modeling complicated spatio-temporal data. It also includes tools of online process monitoring to detect possible change-points in a spatio-temporal process over time. More specifically, the package implements the spatio-temporal mean estimation procedure described in Yang and Qiu (2018) <doi:10.1002/sim.7622>, the spatio-temporal covariance estimation procedure discussed in Yang and Qiu (2019) <doi:10.1002/sim.8315>, the three-step method for the joint estimation of spatio-temporal mean and covariance functions suggested by Yang and Qiu (2022) <doi:10.1007/s10463-021-00787-2>, the spatio-temporal disease surveillance method discussed in Qiu and Yang (2021) <doi:10.1002/sim.9150> that can accommodate the covariate effect, the spatial-LASSO-based process monitoring method proposed by Qiu and Yang (2023) <doi:10.1080/00224065.2022.2081104>, and the online spatio-temporal disease surveillance method described in Yang and Qiu (2020) <doi:10.1080/24725854.2019.1696496>.

Authors:Kai Yang [aut, cre], Peihua Qiu [ctb]

SpTe2M_1.0.3.tar.gz
SpTe2M_1.0.3.tar.gz(r-4.5-noble)SpTe2M_1.0.3.tar.gz(r-4.4-noble)
SpTe2M_1.0.3.tgz(r-4.4-emscripten)SpTe2M_1.0.3.tgz(r-4.3-emscripten)
SpTe2M.pdf |SpTe2M.html
SpTe2M/json (API)

# Install 'SpTe2M' in R:
install.packages('SpTe2M', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ili_dat - Florida influenza-like illness data
  • pm25_dat - PM2.5 concentration data
  • sim_dat - A simulated spatio-temporal dataset

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.32 score 21 scripts 166 downloads 9 exports 59 dependencies

Last updated 1 years agofrom:aa2c6666d8. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-linux-x86_64OKOct 24 2024

Exports:cv_mspemod_cvspte_covestspte_decorspte_meanestspte_semiparmregsptemnt_cusumsptemnt_ewmacsptemnt_ewsl

Dependencies:base64encbslibcachemclicodetoolscolorspacedigestevaluatefansifarverfastmapfontawesomeforeachfsggplot2glmnetgluegtablehighrhtmltoolsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrmapprojmapsMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigR6rappdirsRColorBrewerRcppRcppEigenrlangrmarkdownsassscalesshapesurvivaltibbletinytexutf8vctrsviridisLitewithrxfunyaml

SpTe2M: Nonparametric Modeling and Monitoring of Spatio-Temporal Data

Rendered fromSpTe2M.Rmdusingknitr::rmarkdownon Oct 24 2024.

Last update: 2023-09-30
Started: 2023-09-29