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mosaicModel  

An Interface to Statistical Modeling Independent of Model Architecture
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mosaicModel", "0.3.0")



Attach the package and use:
library("mosaicModel")
Maintained by
Daniel Kaplan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-22
Latest Update: 2017-09-22
Description:
Provides functions for evaluating, displaying, and interpreting statistical models. The goal is to abstract the operations on models from the particular architecture of the model. For instance, calculating effect sizes rather than looking at coefficients. The package includes interfaces to both regression and classification architectures, including lm(), glm(), rlm() in 'MASS', random forests and recursive partitioning, k-nearest neighbors, linear and quadratic discriminant analysis, and models produced by the 'caret' package's train(). It's straightforward to add in other other model architectures.
How to cite:
Daniel Kaplan (2017). mosaicModel: An Interface to Statistical Modeling Independent of Model Architecture. R package version 0.3.0, https://cran.r-project.org/web/packages/mosaicModel
Previous versions and publish date:
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