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SpTe2M
View on CRAN: Click
here
Download and install SpTe2M package within the R console
Install from CRAN:
install.packages("SpTe2M")
Install from Github:
library("remotes")
install_github("cran/SpTe2M")
Install by package version:
library("remotes")
install_version("SpTe2M", "1.0.3")
Attach the package and use:
library("SpTe2M")
Maintained by
Kai Yang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.SpTe2M . SpTe2M results . SpTe2M.pdf . SpTe2M: Nonparametric Modeling and Monitoring of Spatio-Temporal Data . SpTe2M_1.0.3.tar.gz . SpTe2M_1.0.3.zip . SpTe2M_1.0.3.zip . SpTe2M_1.0.3.zip . SpTe2M_1.0.3.tgz . SpTe2M_1.0.3.tgz . SpTe2M_1.0.3.tgz . SpTe2M_1.0.3.tgz . SpTe2M_1.0.3.tgz . SpTe2M_1.0.3.tgz . SpTe2M archive . https://CRAN.R-project.org/package=SpTe2M .
First Published: 2022-06-06
Latest Update: 2023-09-30
Description:
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>.
How to cite:
Kai Yang (2022). SpTe2M: Nonparametric Modeling and Monitoring of Spatio-Temporal Data. R package version 1.0.3, https://cran.r-project.org/web/packages/SpTe2M. Accessed 29 Mar. 2025.
Previous versions and publish date:
Other packages that cited SpTe2M R package
View SpTe2M citation profile
Other R packages that SpTe2M depends,
imports, suggests or enhances
Complete documentation for SpTe2M
Functions, R codes and Examples using
the SpTe2M R package
Some associated functions: CV_MSPE . ILI . Mod_CV . SimDat . SpTe2M-package . SpTeMnt_CUSUM . SpTeMnt_EWMAC . SpTeMnt_EWSL . SpTe_CovEst . SpTe_DeCor . SpTe_MeanEst . SpTe_SemiParmReg .
Some associated R codes: CV_MSPE.R . Mod_CV.R . SpTeMnt_CUSUM.R . SpTeMnt_EWMAC.R . SpTeMnt_EWSL.R . SpTe_CovEst.R . SpTe_DeCor.R . SpTe_MeanEst.R . SpTe_SemiParmReg.R . Full SpTe2M package functions and examples
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