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PredPsych  

Predictive Approaches in Psychology
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PredPsych", "0.4")



Attach the package and use:
library("PredPsych")
Maintained by
Atesh Koul
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-02-15
Latest Update: 2019-07-23
Description:
Recent years have seen an increased interest in novel methods for analyzing quantitative data from experimental psychology. Currently, however, they lack an established and accessible software framework. Many existing implementations provide no guidelines, consisting of small code snippets, or sets of packages. In addition, the use of existing packages often requires advanced programming experience. 'PredPsych' is a user-friendly toolbox based on machine learning predictive algorithms. It comprises of multiple functionalities for multivariate analyses of quantitative behavioral data based on machine learning models.
How to cite:
Atesh Koul (2017). PredPsych: Predictive Approaches in Psychology. R package version 0.4, https://cran.r-project.org/web/packages/PredPsych
Previous versions and publish date:
0.1 (2017-02-15 09:59), 0.2 (2017-06-26 15:57), 0.3 (2017-09-12 10:02)
Other packages that cited PredPsych R package
View PredPsych citation profile
Other R packages that PredPsych depends, imports, suggests or enhances
Functions, R codes and Examples using the PredPsych R package
Some associated functions: ClassPerm . DTModel . DimensionRed . KinData . LinearDA . ModelCluster . PredPsych . classifyFun . fscore . overallConfusionMetrics . predictNewData . 
Some associated R codes: ClassPerm.R . DTModel.R . DimReduction.R . LinearDA.R . ModelCluster.R . classifyFun.R . fscores.R . overallConfusionMetrics.R . predictNewData.R .  Full PredPsych package functions and examples
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