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strm is an R package that fits spatio-temporal regression model based on Chi & Zhu Spatial Regression Models for the Social Sciences (2019). The approach here fits a simultaneous spatial error model (SAR) while incorporating a temporally lagged response variable and temporally lagged explanatory variables.

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strm

strm

strm is an R package that fits spatio-temporal regression model based on Chi & Zhu Spatial Regression Models for the Social Sciences (2019). The approach here fits a simultaneous spatial error model (SAR) while incorporating a temporally lagged response variable and temporally lagged explanatory variables.

This package builds on the errorsarlm() function from the spatialreg package.

This package is still under development. Please report bugs or constructive tips to issues here.

Installation

strm was built on R version 4.0.2 ("Taking Off Again").

Package dependencies include:

- R (>= 3.6),
- spatialreg (>= 1.1-5),

Package imports include:

- dplyr (>= 1.0.0),
- rlang (>= 0.4.6),
- tidyr (>= 1.0.0),
- purrr (>= 0.3.4),
- magrittr (>= 1.5),
- rgdal (>= 1.5.10),
- spdep (>= 1.1.3),
- lazyeval,
- stats,
- grDevices,
- methods,
- graphics,
- utils,
- knitr,
- testthat (>= 2.3.2),
- rmarkdown (>= 2.3)

Package suggests include:

- splm (>= 1.4.11),
- spdep (>= 1.1-3),
- sf (>= 0.9-4),
- Ecdat (>= 0.3-7),
- tidycensus (>= 0.9.9),
- ggplot2 (3.3.2),
- patchwork (>= 1.0.1),
- broom (>= 0.7.0)

To download the latest version of strm:

library("devtools")
devtools::install_github("mkamenet3/strm")

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About

strm is an R package that fits spatio-temporal regression model based on Chi & Zhu Spatial Regression Models for the Social Sciences (2019). The approach here fits a simultaneous spatial error model (SAR) while incorporating a temporally lagged response variable and temporally lagged explanatory variables.

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