Other packages > Find by keyword >

MARSGWR  

A Hybrid Spatial Model for Capturing Spatially Varying Relationships Between Variables in the Data
View on CRAN: Click here


Download and install MARSGWR package within the R console
Install from CRAN:
install.packages("MARSGWR")

Install from Github:
library("remotes")
install_github("cran/MARSGWR")

Install by package version:
library("remotes")
install_version("MARSGWR", "0.1.0")



Attach the package and use:
library("MARSGWR")
Maintained by
Nobin Chandra Paul
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-09
Latest Update: 2023-05-09
Description:
It is a hybrid spatial model that combines the strength of two widely used regression models, MARS (Multivariate Adaptive Regression Splines) and GWR (Geographically Weighted Regression) to provide an effective approach for predicting a response variable at unknown locations. The MARS model is used in the first step of the development of a hybrid model to identify the most important predictor variables that assist in predicting the response variable. For method details see, Friedman, J.H. (1991). .The GWR model is then used to predict the response variable at testing locations based on these selected variables that account for spatial variations in the relationships between the variables. This hybrid model can improve the accuracy of the predictions compared to using an individual model alone.This developed hybrid spatial model can be useful particularly in cases where the relationship between the response variable and predictor variables is complex and non-linear, and varies across locations.
How to cite:
Nobin Chandra Paul (2023). MARSGWR: A Hybrid Spatial Model for Capturing Spatially Varying Relationships Between Variables in the Data. R package version 0.1.0, https://cran.r-project.org/web/packages/MARSGWR. Accessed 13 Sep. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited MARSGWR R package
View MARSGWR citation profile
Other R packages that MARSGWR depends, imports, suggests or enhances
Complete documentation for MARSGWR
Functions, R codes and Examples using the MARSGWR R package
Full MARSGWR package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

oii  
Crosstab and Statistical Tests for OII MSc Stats Course
Provides simple crosstab output with optional statistics (e.g., Goodman-Kruskal Gamma, Somers' d, an ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
tvmComp  
Discounting and Compounding Calculations for Various Scenarios
Functions for compounding and discounting calculations included here serve as a complete reference f ...
Download / Learn more Package Citations See dependency  
TSEwgt  
Total Survey Error Under Multiple, Different Weighting Schemes
Calculates total survey error (TSE) for a survey under multiple, different weighting schemes, using ...
Download / Learn more Package Citations See dependency  
cmdfun  
Framework for Building Interfaces to Shell Commands
Writing interfaces to command line software is cumbersome. 'cmdfun' provides a framework for buildi ...
Download / Learn more Package Citations See dependency  
saeMSPE  
Computing MSPE Estimates in Small Area Estimation
We describe a new R package entitled 'saeMSPE' for the well-known Fay Herriot model and nested error ...
Download / Learn more Package Citations See dependency  

28,565

R Packages

239,283

Dependencies

75,677

Author Associations

28,566

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA