CircularDescriptiveAnalysis Class

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Constructs the Circular Descriptive Analysis.

Gets the source matrix from which the analysis was run.

Gets the source matrix from which the analysis was run.

Gets the column names from the variables in the data.

Gets an array containing the circular concentration for each data column.

Gets the 95% confidence intervals for the Means.

Gets an array containing the sum of cosines for each data column.

Gets the 95% deviance intervals for the Means.

Gets a vector containing the number of distinct elements for each data column.

Gets an array containing the inner fences of each data column.

Gets an array containing the kurtosis for of each data column.

Gets or sets whether the properties of this class should be computed only when necessary. If set to true, a copy of the input data will be maintained inside an instance of this class, using more memory.

Gets a vector containing the length of the circular domain for each data column.

Gets a vector containing the Mean of each data column.

Gets a collection of DescriptiveMeasures objects that can be bound to a DataGridView.

Gets a vector containing the Median of each data column.

Gets a vector containing the Mode of each data column.

Gets an array containing the outer fences of each data column.

Gets or sets the method to be used when computing quantiles (median and quartiles).

Gets an array containing the interquartile range of each data column.

Gets an array containing the Ranges of each data column.

Gets the number of samples (or observations) in the data.

Gets an array containing the sum of sines for each data column.

Gets an array containing the skewness for of each data column.

Gets the source matrix from which the analysis was run.

Gets a vector containing the Standard Deviation of each data column.

Gets a vector containing the Standard Error of the Mean of each data column.

Gets an array containing the sum of each data column. If the analysis has been computed in place, this will contain the sum of the transformed angle values instead.

Gets or sets whether all reported statistics should respect the circular interval. For example, setting this property to false would allow the Confidence, Deviance, InnerFences and OuterFences properties report minimum and maximum values outside the variable's allowed circular range. Default is true.

Gets the number of variables (or features) in the data.

Gets a vector containing the Variance of each data column.

Computes the analysis using given source data and parameters.

Determines whether the specified object is equal to the current object.

Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.

Gets a confidence interval for the Means within the given confidence level percentage.

Gets a deviance interval for the Means within the given confidence level percentage (i.e. uses the standard deviation rather than the standard error to compute the range interval for the variable).

Serves as the default hash function.

Gets the Type of the current instance.

Learns a model that can map the given inputs to the desired outputs.

Creates a shallow copy of the current Object.

Returns a string that represents the current object.

Checks whether an object implements a method with the given name.

Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.