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cowbell (version 0.1.0)

Performs Segmented Linear Regression on Two Independent Variables

Description

Implements a specific form of segmented linear regression with two independent variables. The visualization of that function looks like a quarter segment of a cowbell giving the package its name. The package has been specifically constructed for the case where minimum and maximum value of the dependent and two independent variables are known a prior, which is usually the case when those values are derived from Likert scales.

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Version

Install

install.packages('cowbell')

Monthly Downloads

216

Version

0.1.0

License

GPL-3

Maintainer

Christoph Luerig

Last Published

May 5th, 2017

Functions in cowbell (0.1.0)

predict.cowbell

Performs a prediction on the cowbell model that has been generated.
print.cowbell

Summarizes the cowbell regression analysis
allFun

allFun: Data set for Fluency, Absorption, Fit and Fun.
cowbell

Computes a response surface as segmented linear regression that resembles a cowbell.
fitted.cowbell

Implementation of the
generateCowbell

Performs the segmented linear regression analysis generating the cowbell function.
generateCowbellConcept

Expresses the fitting formula and the value range of the variables.
plot.cowbell

Plots the obtained cowbell function.
print.cowbellConcept

Summarizes the cowbell concept with the formula and value ranges.
print.summary.cowbell

Prints the summary obtained by
residuals.cowbell

Implementation of the
summary.cowbell

Generates the core information of the cowbell analysis.
testA

testA: Artificial data set for testing.