Compares the distribution of a single attribute's values to normal distribution by using several statistic tests.
R6::R6Class object.
featureNameReturns the instance variable featureName. (character)
rawDataReturns the instance variable rawData. (tibble::tibble)
setRawDataSets the instance variable rawData. (tibble::tibble)
histogramReturns the instance variable histogram. (tibble::tibble)
expMuReturns the instance variable expMu. (numeric)
expSigmaReturns the instance variable expSigma. (numeric)
dataPointsReturns the instance variable dataPoints. (numeric)
logLikelihoodReturns the instance variable logLikelihood. (numeric)
degOfFreedomReturns the instance variable degOfFreedom. (numeric)
nReturns the instance variable n. (integer)
bicReturns the instance variable bic. (numeric)
aicReturns the instance variable aic. (numeric)
aiccReturns the instance variable aicc. (numeric)
rmseReturns the instance variable rmse. (numeric)
fitSuccessReturns the instance variable fitSuccess. (logical)
testNamesReturns the instance variable testNames. (character)
testParameterNamesReturns the instance variable testParameterNames. (character)
alphaReturns the instance variable alpha. (numeric)
w.shapiroReturns the instance variable w.shapiro. (numeric)
p.shapiroReturns the instance variable p.shapiro. (numeric)
d.kolmogorowReturns the instance variable d.kolmogorow. (numeric)
p.kolmogorowReturns the instance variable p.kolmogorow. (numeric)
a.andersonReturns the instance variable a.anderson. (numeric)
p.andersonReturns the instance variable p.anderson. (numeric)
new()Creates and returns a new pgu.normDist object.
pgu.normDist$new(data = "tbl_df")
dataThe data to be analyzed. (tibble::tibble)
A new pgu.normDist object.
(pguIMP::pgu.normDist)
finalize()Clears the heap and
indicates that instance of pgu.normDist is removed from heap.
pgu.normDist$finalize()
print()Prints instance variables of a pgu.normDist object.
pgu.normDist$print()
string
resetNormDist()Resets instance variables
pgu.normDist$resetNormDist(data = "tbl_df")
dataDataframe to be analyzed. (tibble::tibble)
resetFail()Resets instance variables in case of a failed analysis.
pgu.normDist$resetFail()
optimize()Optimizes the logLikelihood between the data and a normal distribution with respect to the expectation value and standard deviation. The quality of the best model ist calculated subsequently.
pgu.normDist$optimize()
createHistogram()Creates a histogram from the instance variable rawData.
The histogram is stored in the instance variable histogram.
pgu.normDist$createHistogram()
normalQQData()Performes a qq-analysis of the instance variable rawData
The qq-analysis is stored in the attributes sample_quantile
and theoretical_quantile of the instance variable rawData.
pgu.normDist$normalQQData()
test.shapiro()Performes Shapiro-Wilk's test for normality on the
instance variable rawData.
The test result is stored in the instance variable
w.shapiro.
The p-value of the test is stored in the instance variable
p.shapiro
pgu.normDist$test.shapiro()
test.kolmogorow()Performes Kolmogorow-Smirnow's test for normality on the
instance variable rawData.
The test result is stored in the instance variable
d.kolmogorow.
The p-value of the test is stored in the instance variable
p.kolmogorow
pgu.normDist$test.kolmogorow()
test.anderson()Performes Anderson-Darling's test for normality on the
instance variable rawData.
The test result is stored in the instance variable
a.anderson.
The p-value of the test is stored in the instance variable
p.anderson
pgu.normDist$test.anderson()
fitResult()Returns the result of the classes optimize function in form of a formated string.
pgu.normDist$fitResult()
String of the results of the fitting routine (character)
testResult()Returns the result of the classes test functions in form of a formated string.
pgu.normDist$testResult(testName = "Shapiro-Wilk")
testNameDefines the test which result shall be returned.
Can be of type:Shapiro-Wilk, Kolmogorow-Smirnow
or Anderson-Darling.
(character)
String of the results of the testing routine (character)
testResultCompendium()Returns the result of the classes test functions
Shapiro-Wilk, Kolmogorow-Smirnow and
Anderson-Darling
in form of a formated string.
(character)
pgu.normDist$testResultCompendium()
String of the results of the testing routine (character)
plotHistogram()Displays the instance variable histogram
in form of a bar plot and overlays the corresponding normal distribution.
pgu.normDist$plotHistogram()
A bar plot. (ggplot2::ggplot)
plotResiduals()Displays the residuals between the instance variable
histogram and the corresponding normal distribution.
pgu.normDist$plotResiduals()
A scatter plot. (ggplot2::ggplot)
plotResidualDist()Displays the distribution of the residuals between the distribution of the instance variable
histogram in form of a histogram.
pgu.normDist$plotResidualDist()
A bar plot. (ggplot2::ggplot)
plotRawResidualDist()Displays the distribution of the residuals between the distribution of the instance variable
rawData in form of a histogram.
pgu.normDist$plotRawResidualDist()
A bar plot. (ggplot2::ggplot)
plotRawDataDist()Displays the distribution of the instance variable
rawData in form of a histogram.
pgu.normDist$plotRawDataDist()
A bar plot. (ggplot2::ggplot)
normalQQPlot()Displays a qqplot of the instance variable
rawData.
pgu.normDist$normalQQPlot()
A qq-plot. (ggplot2::ggplot)
fit()Runs the optimization process and performs all implemented quality controls. Additionally performs hypothesis tests for nromality.
pgu.normDist$fit()
clone()The objects of this class are cloneable with this method.
pgu.normDist$clone(deep = FALSE)
deepWhether to make a deep clone.
The distribution of a single value is tested for normality by Shapiro-Wilk test, Kolmogorov-Smirnov test, Anderson-Darling test. The expectation value and standard deviation of a normal distribution representing the data are determined by maximizing the log Likelihood with respect to the expectation value and standard deviation. This object is used by the shiny based gui and is not for use in individual R-scripts!