pgu.model: pgu.model
In pguIMP: 'pguIMP'
Description
Format
Details
Active bindings
Methods
Author(s)
Description
Comprises a list of models for data manipulation.
Format
R6::R6Class object.
Details
Comprises a list of pgu.normDist objects and model parameters.
These can be used to scale data.
This object is used by the shiny based gui and is not for use in individual R-scripts!
Active bindings
modelListReturns a vector of pgu-normDist objects.
(pgu.normDist)
modelParameterReturns a dataframe comrising model parameters.
(tibble::tibble)
Methods
Public methods
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Method new()
Creates and returns a new pgu.model object.
Usage
pgu.model$new(data = "tbl_df")
Arguments
dataThe data to be analyzed.
(tibble::tibble)
Returns
A new pgu.model object.
(pguIMP::pgu.model)
Method finalize()
Clears the heap and
indicates that instance of pgu.model is removed from heap.
Usage
pgu.model$finalize()
Method print()
Prints instance variables of a pgu.model object.
Usage
pgu.model$print()
Returns
string
Method resetModelParameter()
Resets instance variable modelParameter
Usage
pgu.model$resetModelParameter(data = "tbl_df")
Arguments
dataDataframe to be analyzed.
(tibble::tibble)
Method resetModelList()
Resets instance variable modelList
Usage
pgu.model$resetModelList(data = "tbl_df")
Arguments
dataDataframe to be analyzed.
(tibble::tibble)
Method resetModel()
Resets instance variable modelList.
Resets instance variable modelParameter.
Displays progress if shiny is loaded.
Usage
pgu.model$resetModel(data = "tbl_df", progress = "Progress")
Arguments
dataDataframe to be analyzed.
(tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored in this instance of the shiny Progress class.
(shiny::Progress)
Method setNormDist()
Stores the information of a pgu.norDist object in an
entry of the instance variable modelList
Usage
pgu.model$setNormDist(data = "pgu.normDist", feature = "character")
Arguments
dataInstance of pgu.normDist
(pguIMP::pgu.normDist)
featureAttribute corresponding to the pgu.normDist object data.
(character)
Method featureIdx()
Returns the index of a pgu.normDist object wihtin the instance variable modelParameter.
Usage
pgu.model$featureIdx(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Index of attribute entry in dataframe
(numeric)
Method fitFeature()
Runs the fit function of a pgu.normDist object at a
user denied position within the instance variable modelList.
Usage
pgu.model$fitFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Method fitData()
Loops through all attributes and calls the object's
ftiFeature function.
Displays progress if shiny is loaded.
Usage
pgu.model$fitData(progress = "Progress")
Arguments
progressIf shiny is loaded, the analysis' progress is stored in this instance of the shiny Progress class.
(shiny::Progress)
Method logFitResultsFeature()
Stores results from fitting procedure of a user defined attribute
into the corrsponding attribute of instance variable modelParameter.
Usage
pgu.model$logFitResultsFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Method logFailedFitResultsFeature()
Stores results from fitting procedure of a user defined attribute
into the corrsponding attribute of instance variable modelParameter
in case of a failed fitting routine.
Usage
pgu.model$logFailedFitResultsFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Method scaleNumeric()
Scales numeric data based upon the model of a user defined attribute.
Usage
pgu.model$scaleNumeric(value = "numeric", feature = "character")
Arguments
valueNumeric vector
(numeric)
featureAttribute's name.
(character)
Returns
scaled version of the given vector
(numeric)
Method scaleData()
Scales a dataframe based upon a list of models
stored in the instance variable modelList..
Usage
pgu.model$scaleData(data = "tbl_df")
Arguments
dataDataframe to be analyzed.
(tibble::tibble)
Returns
scaled version of the given dataframe
(tibble::tibble)
Method rescaleNumeric()
Re-scales numeric data based upon the model of a user defined attribute.
Usage
pgu.model$rescaleNumeric(value = "numeric", feature = "character")
Arguments
valueNumeric vector
(numeric)
featureAttribute's name.
(character)
Returns
Re-scaled version of the given vector
(numeric)
Method rescaleData()
Re-scales a dataframe based upon a list of models
stored in the instance variable modelList..
Usage
pgu.model$rescaleData(data = "tbl_df")
Arguments
dataDataframe to be analyzed.
(tibble::tibble)
Returns
Re-scaled version of the given dataframe
(tibble::tibble)
Method modelParameterData()
Returns the model parameter (expectation value, standard deviation).
Usage
pgu.model$modelParameterData()
Returns
Dataframe comprising model parameter.
(tibble::tibble)
Method modelParameterFeature()
Returns the model parameter (expectation value, standard deviation)
for a user deined attribute.
Usage
pgu.model$modelParameterFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Dataframe comprising model parameter.
(tibble::tibble)
Method modelQualityData()
Returns the model parameters connected to model quality.
Usage
pgu.model$modelQualityData()
Returns
Dataframe comprising model parameter.
(tibble::tibble)
Method modelQualityFeature()
Returns the model parameters connected to model quality
for a user deined attribute.
Usage
pgu.model$modelQualityFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Dataframe comprising model parameter.
(tibble::tibble)
Method fitResultData()
Returns the model fit results.
Usage
pgu.model$fitResultData()
Returns
Dataframe comprising model fit results.
(tibble::tibble)
Method fitResultFeature()
Returns the model fit results
for a user deined attribute.
Usage
pgu.model$fitResultFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Dataframe comprising model fit results.
(tibble::tibble)
Method testResultData()
Returns the hypothesis test results.
Usage
pgu.model$testResultData()
Returns
Dataframe comprising the hypothesis test results.
(tibble::tibble)
Method testResultFeature()
Returns the hypothesis test results.
for a user deined attribute.
Usage
pgu.model$testResultFeature(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Dataframe comprising the hypothesis test results.
(tibble::tibble)
Method plotModel()
Creates and returns a composite graphical analysis
of the modeling procedure of
a user defined attribute.
Usage
pgu.model$plotModel(feature = "character")
Arguments
featureAttribute's name.
(character)
Returns
Composite result plot.
(ggplot2::ggplot)
Method clone()
The objects of this class are cloneable with this method.
Usage
pgu.model$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Author(s)
Sebastian Malkusch, malkusch@med.uni-frankfurt.de
pguIMP documentation built on Sept. 30, 2021, 5:08 p.m.
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Description Format Details Active bindings Methods Author(s)
Description
Comprises a list of models for data manipulation.
Format
R6::R6Class object.
Details
Comprises a list of pgu.normDist objects and model parameters. These can be used to scale data. This object is used by the shiny based gui and is not for use in individual R-scripts!
Active bindings
modelListReturns a vector of pgu-normDist objects. (pgu.normDist)
modelParameterReturns a dataframe comrising model parameters. (tibble::tibble)
Methods
Public methods
Method new()
Creates and returns a new pgu.model object.
Usage
pgu.model$new(data = "tbl_df")
Arguments
dataThe data to be analyzed. (tibble::tibble)
Returns
A new pgu.model object.
(pguIMP::pgu.model)
Method finalize()
Clears the heap and
indicates that instance of pgu.model is removed from heap.
Usage
pgu.model$finalize()
Method print()
Prints instance variables of a pgu.model object.
Usage
pgu.model$print()
Returns
string
Method resetModelParameter()
Resets instance variable modelParameter
Usage
pgu.model$resetModelParameter(data = "tbl_df")
Arguments
dataDataframe to be analyzed. (tibble::tibble)
Method resetModelList()
Resets instance variable modelList
Usage
pgu.model$resetModelList(data = "tbl_df")
Arguments
dataDataframe to be analyzed. (tibble::tibble)
Method resetModel()
Resets instance variable modelList.
Resets instance variable modelParameter.
Displays progress if shiny is loaded.
Usage
pgu.model$resetModel(data = "tbl_df", progress = "Progress")
Arguments
dataDataframe to be analyzed. (tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored in this instance of the shiny Progress class. (shiny::Progress)
Method setNormDist()
Stores the information of a pgu.norDist object in an
entry of the instance variable modelList
Usage
pgu.model$setNormDist(data = "pgu.normDist", feature = "character")
Arguments
dataInstance of pgu.normDist (pguIMP::pgu.normDist)
featureAttribute corresponding to the pgu.normDist object data. (character)
Method featureIdx()
Returns the index of a pgu.normDist object wihtin the instance variable modelParameter.
Usage
pgu.model$featureIdx(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Index of attribute entry in dataframe (numeric)
Method fitFeature()
Runs the fit function of a pgu.normDist object at a user denied position within the instance variable modelList.
Usage
pgu.model$fitFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Method fitData()
Loops through all attributes and calls the object's ftiFeature function. Displays progress if shiny is loaded.
Usage
pgu.model$fitData(progress = "Progress")
Arguments
progressIf shiny is loaded, the analysis' progress is stored in this instance of the shiny Progress class. (shiny::Progress)
Method logFitResultsFeature()
Stores results from fitting procedure of a user defined attribute
into the corrsponding attribute of instance variable modelParameter.
Usage
pgu.model$logFitResultsFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Method logFailedFitResultsFeature()
Stores results from fitting procedure of a user defined attribute
into the corrsponding attribute of instance variable modelParameter
in case of a failed fitting routine.
Usage
pgu.model$logFailedFitResultsFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Method scaleNumeric()
Scales numeric data based upon the model of a user defined attribute.
Usage
pgu.model$scaleNumeric(value = "numeric", feature = "character")
Arguments
valueNumeric vector (numeric)
featureAttribute's name. (character)
Returns
scaled version of the given vector (numeric)
Method scaleData()
Scales a dataframe based upon a list of models stored in the instance variable modelList..
Usage
pgu.model$scaleData(data = "tbl_df")
Arguments
dataDataframe to be analyzed. (tibble::tibble)
Returns
scaled version of the given dataframe (tibble::tibble)
Method rescaleNumeric()
Re-scales numeric data based upon the model of a user defined attribute.
Usage
pgu.model$rescaleNumeric(value = "numeric", feature = "character")
Arguments
valueNumeric vector (numeric)
featureAttribute's name. (character)
Returns
Re-scaled version of the given vector (numeric)
Method rescaleData()
Re-scales a dataframe based upon a list of models stored in the instance variable modelList..
Usage
pgu.model$rescaleData(data = "tbl_df")
Arguments
dataDataframe to be analyzed. (tibble::tibble)
Returns
Re-scaled version of the given dataframe (tibble::tibble)
Method modelParameterData()
Returns the model parameter (expectation value, standard deviation).
Usage
pgu.model$modelParameterData()
Returns
Dataframe comprising model parameter. (tibble::tibble)
Method modelParameterFeature()
Returns the model parameter (expectation value, standard deviation) for a user deined attribute.
Usage
pgu.model$modelParameterFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Dataframe comprising model parameter. (tibble::tibble)
Method modelQualityData()
Returns the model parameters connected to model quality.
Usage
pgu.model$modelQualityData()
Returns
Dataframe comprising model parameter. (tibble::tibble)
Method modelQualityFeature()
Returns the model parameters connected to model quality for a user deined attribute.
Usage
pgu.model$modelQualityFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Dataframe comprising model parameter. (tibble::tibble)
Method fitResultData()
Returns the model fit results.
Usage
pgu.model$fitResultData()
Returns
Dataframe comprising model fit results. (tibble::tibble)
Method fitResultFeature()
Returns the model fit results for a user deined attribute.
Usage
pgu.model$fitResultFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Dataframe comprising model fit results. (tibble::tibble)
Method testResultData()
Returns the hypothesis test results.
Usage
pgu.model$testResultData()
Returns
Dataframe comprising the hypothesis test results. (tibble::tibble)
Method testResultFeature()
Returns the hypothesis test results. for a user deined attribute.
Usage
pgu.model$testResultFeature(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Dataframe comprising the hypothesis test results. (tibble::tibble)
Method plotModel()
Creates and returns a composite graphical analysis of the modeling procedure of a user defined attribute.
Usage
pgu.model$plotModel(feature = "character")
Arguments
featureAttribute's name. (character)
Returns
Composite result plot. (ggplot2::ggplot)
Method clone()
The objects of this class are cloneable with this method.
Usage
pgu.model$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Author(s)
Sebastian Malkusch, malkusch@med.uni-frankfurt.de
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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