private void init(double[,] matrix, double[][] array, string[] columnNames)
{
this.sourceMatrix = matrix;
this.sourceArray = array;
this.columnNames = columnNames;
if (matrix != null)
{
this.samples = matrix.GetLength(0);
this.variables = matrix.GetLength(1);
}
else
{
this.samples = array.Length;
this.variables = array[0].Length;
}
// Create object-oriented structure to access data
DescriptiveMeasures[] measures = new DescriptiveMeasures[variables];
for (int i = 0; i < measures.Length; i++)
{
measures[i] = new DescriptiveMeasures(this, i);
}
this.measuresCollection = new DescriptiveMeasureCollection(measures);
}
private void Compute(double[,] data, string[] columnNames)
{
if (columnNames == null)
{
// Generate column names as Column 1, Column 2, ...
columnNames = new string[data.GetLength(1)];
for (int i = 0; i < columnNames.Length; i++)
{
columnNames[i] = "Column " + i;
}
}
this.sourceMatrix = data;
this.columnNames = columnNames;
this.samples = data.GetLength(0);
this.variables = data.GetLength(1);
// Create object-oriented structure to access data
DescriptiveMeasures[] measures = new DescriptiveMeasures[variables];
for (int i = 0; i < measures.Length; i++)
{
measures[i] = new DescriptiveMeasures(this, i);
}
this.measuresCollection = new DescriptiveMeasureCollection(measures);
}
/// <summary>
/// Constructs the Descriptive Analysis.
/// </summary>
///
/// <param name="data">The source data to perform analysis.</param>
/// <param name="columnNames">Names for the analyzed variables.</param>
///
public DescriptiveAnalysis(double[,] data, string[] columnNames)
{
// Initial argument checking
if (data == null)
{
throw new ArgumentNullException("data");
}
if (columnNames == null)
{
// Generate column names as Column 1, Column 2, ...
columnNames = new string[data.GetLength(0)];
for (int i = 0; i < columnNames.Length; i++)
{
columnNames[i] = "Column " + i;
}
}
this.sourceMatrix = data;
this.columnNames = columnNames;
this.samples = data.GetLength(0);
this.variables = data.GetLength(1);
// Create object-oriented structure to access data
DescriptiveMeasures[] measures = new DescriptiveMeasures[variables];
for (int i = 0; i < measures.Length; i++)
{
measures[i] = new DescriptiveMeasures(this, i);
}
this.measuresCollection = new DescriptiveMeasureCollection(measures);
}
/// <summary>Constructs the Descriptive Analysis.</summary>
/// <param name="data">The source data to perform analysis.</param>
public DescriptiveAnalysis(double[,] data, string[] columnNames)
{
this.sourceMatrix = data;
this.columnNames = columnNames;
this.samples = data.GetLength(0);
this.variables = data.GetLength(1);
// Run analysis
this.sums = Statistics.Tools.Sum(data);
this.means = Statistics.Tools.Mean(data, sums);
this.standardDeviations = Statistics.Tools.StandardDeviation(data, means);
this.ranges = Statistics.Tools.Range(data);
this.kurtosis = Statistics.Tools.Kurtosis(data, means, standardDeviations);
this.skewness = Statistics.Tools.Skewness(data, means, standardDeviations);
this.medians = Statistics.Tools.Median(data);
this.modes = Statistics.Tools.Mode(data);
this.variances = Statistics.Tools.Variance(data, means);
this.standardErrors = Statistics.Tools.StandardError(samples, standardDeviations);
// Mean centered data
this.dScores = (double[, ])data.Clone();
Statistics.Tools.Center(dScores, means);
// Mean centered and standardized data
this.zScores = Statistics.Tools.ZScores(data, means, standardDeviations);
// Covariance and correlation
this.covarianceMatrix = Statistics.Tools.Covariance(data, means);
this.correlationMatrix = Statistics.Tools.Covariance(zScores);
// Create object-oriented structure to access data
DescriptiveMeasures[] measures = new DescriptiveMeasures[sourceMatrix.GetLength(1)];
for (int i = 0; i < measures.Length; i++)
{
measures[i] = new DescriptiveMeasures(this, i);
}
this.measuresCollection = new DescriptiveMeasureCollection(measures);
}
