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SpiceFP  

Sparse Method to Identify Joint Effects of Functional Predictors
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SpiceFP", "0.1.2")



Attach the package and use:
library("SpiceFP")
Maintained by
Girault Gnanguenon Guesse
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-15
Latest Update: 2023-06-01
Description:
A set of functions allowing to implement the 'SpiceFP' approach which is iterative. It involves transformation of functional predictors into several candidate explanatory matrices (based on contingency tables), to which relative edge matrices with contiguity constraints are associated. Generalized Fused Lasso regression are performed in order to identify the best candidate matrix, the best class intervals and related coefficients at each iteration. The approach is stopped when the maximal number of iterations is reached or when retained coefficients are zeros. Supplementary functions allow to get coefficients of any candidate matrix or mean of coefficients of many candidates. The methods in this package are describing in Girault Gnanguenon Guesse, Patrice Loisel, Bénedicte Fontez, Thierry Simonneau, Nadine Hilgert (2021) "An exploratory penalized regression to identify combined effects of functional variables -Application to agri-environmental issues" <https://hal.archives-ouvertes.fr/hal-03298977>.
How to cite:
Girault Gnanguenon Guesse (2021). SpiceFP: Sparse Method to Identify Joint Effects of Functional Predictors. R package version 0.1.2, https://cran.r-project.org/web/packages/SpiceFP. Accessed 23 Dec. 2024.
Previous versions and publish date:
0.1.0 (2021-09-15 10:40), 0.1.1 (2022-05-11 10:10)
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Complete documentation for SpiceFP
Functions, R codes and Examples using the SpiceFP R package
Full SpiceFP package functions and examples
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