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analytics (version 3.0)

Regression Outlier Detection, Stationary Bootstrap, Testing Weak Stationarity, NA Imputation, and Other Tools for Data Analysis

Description

Current version includes outlier detection in a fitted linear model, stationary bootstrap using a truncated geometric distribution, a comprehensive test for weak stationarity, missing value imputation, column/rows sums/means by group, weighted biplots, and a heuristic to obtain a better initial configuration in non-metric MDS.

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Version

Install

install.packages('analytics')

Monthly Downloads

39

Version

3.0

License

GPL-2

Maintainer

Last Published

October 14th, 2018

Functions in analytics (3.0)

rowmean

Give Column Means of a Matrix-like Object, Based on a Grouping Variable
tgsboot

Bootstrap for Stationary Data
Wbiplot

Weighted Biplot
weakly.stationary

Testing for Weak Stationarity in a Time Series
colmean

Give Row Means of a Matrix-like Object, Based on a Grouping Variable
Minstress

Better Starting Configuration For Non-Metric MDS
colsum

Give Row sums of a Matrix-like Object, Based on a Grouping Variable
na.cleaner

Missing Value Imputation
offliers

Takes Outliers Off