Package: PredPsych 0.6

PredPsych: Predictive Approaches in Psychology

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.

Authors:Atesh Koul [aut, cre]

PredPsych_0.6.tar.gz
PredPsych_0.6.zip(r-4.7-any)PredPsych_0.6.zip(r-4.6-any)PredPsych_0.6.zip(r-4.5-any)
PredPsych_0.6.tgz(r-4.6-any)PredPsych_0.6.tgz(r-4.5-any)
PredPsych_0.6.tar.gz(r-4.7-any)PredPsych_0.6.tar.gz(r-4.6-any)
PredPsych_0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PredPsych/json (API)

# Install 'PredPsych' in R:

install.packages('PredPsych', repos = c('https://ateshkoul.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ateshkoul/predpsych/issues

Datasets:

KinData - Kinematics Dataset A dataset containing part of the motion capture dataset freely available in the publication (Ansuini et al., 2015).The dataset was obtained by recording 15 naive participants performing reach-to-grasp movements towards two differently sized objects: a small object (i.e., hazelnut) and a large object (i.e., grapefruit). The variables are as follows:

On CRAN:

2.94 score 2 stars 11 scripts 313 downloads 4 mentions 9 exports 87 dependencies

Last updated from:813b543a3b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	231
source / vignettes	OK	216
linux-release	OK	187
macos-release	OK	235
macos-oldrel	OK	276
windows-devel	OK	148
windows-release	OK	135
windows-oldrel	OK	105
wasm-release	OK	118

Exports:classifyFun ClassPerm DimensionRed DTModel fscore LinearDA ModelCluster overallConfusionMetrics predictNewData

Dependencies:caret class cli clock codetools coin cpp11 data.table diagram digest dplyr e1071 farver foreach future future.apply generics ggplot2 globals glue gower gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava libcoin lifecycle listenv lubridate magrittr MASS Matrix matrixStats mclust ModelMetrics modeltools multcomp mvtnorm nlme nnet numDeriv parallelly party pillar pkgconfig plyr pROC prodlim progressr proxy purrr R6 randomForest RColorBrewer Rcpp recipes reshape2 rlang rpart S7 sandwich scales shape sparsevctrs SQUAREM statmod stringi stringr strucchange survival TH.data tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr zoo

Help page	Topics
Generic Classification Analyses	classifyFun
Permutation Analysis for classification	ClassPerm
Generic Dimensionallity Reduction Function	DimensionRed
Generic Decision Tree Function	DTModel
f-score	fscore
Kinematics Dataset A dataset containing part of the motion capture dataset freely available in the publication (Ansuini et al., 2015).The dataset was obtained by recording 15 naive participants performing reach-to-grasp movements towards two differently sized objects: a small object (i.e., hazelnut) and a large object (i.e., grapefruit). The variables are as follows:	KinData
Cross-validated Linear Discriminant Analysis	LinearDA
Model based Clustering	ModelCluster
Confusion Matrix metrics for Cross-validation	overallConfusionMetrics
Predict Class membership for New Data	predictNewData
PredPsych.	PredPsych-package PredPsych

Package: PredPsych 0.6

PredPsych: Predictive Approaches in Psychology

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)