/// <summary>
/// Add two Gaussian Statistics.
/// </summary>
/// <param name="x">GaussianStatistics x.</param>
/// <param name="y">GaussianStatistics y.</param>
/// <returns>Returns added result of two Gaussian Statistics.</returns>
public static GaussianStatistics Add(GaussianStatistics x, GaussianStatistics y)
{
if (x == null)
{
throw new ArgumentNullException("x");
}
if (y == null)
{
throw new ArgumentNullException("y");
}
int rN = x.SampleSize + y.SampleSize;
double rMean = (x.SampleSize * x.Mean + y.SampleSize * y.Mean) / rN;
double rVar = (x.SumOfSquares + y.SumOfSquares) / rN - rMean * rMean;
if (rVar < 0)
{
Helper.CheckCondition(rVar > -1e-10, "Computed negative variance! " + rVar);
rVar = 0;
}
GaussianStatistics result = GaussianStatistics.GetInstance(rMean, rVar, rN);
return(result);
}
/// <summary>
/// Try Parse the value.
/// </summary>
/// <param name="val">The Value.</param>
/// <param name="result">Sufficient Statistics result.</param>
/// <returns>Returns true if parsed properly.</returns>
new public static bool TryParse(string val, out SufficientStatistics result)
{
result = null;
if (string.IsNullOrEmpty(val))
{
result = GetMissingInstance;
return(false);
}
else
{
string[] fields = val.Split(',');
if (!(fields.Length == 3))
{
return(false);
}
double mean, variance;
int sampleSize;
if (double.TryParse(fields[0], out mean) &&
double.TryParse(fields[1], out variance) &&
int.TryParse(fields[2], out sampleSize))
{
result = GaussianStatistics.GetInstance(mean, variance, sampleSize);
return(true);
}
return(false);
}
}
/// <summary>
/// Try converting the given string into SufficientStatistics object.
/// </summary>
/// <param name="val">string to be converted.</param>
/// <param name="result">SufficentStatistics object which corresponding to the given string.</param>
/// <returns>Whether string was successfully converted.</returns>
public static bool TryParse(string val, out SufficientStatistics result)
{
return
(MissingStatistics.TryParse(val, out result) ||
GaussianStatistics.TryParse(val, out result) ||
BooleanStatistics.TryParse(val, out result) ||
DiscreteStatistics.TryParse(val, out result) ||
ContinuousStatistics.TryParse(val, out result) ||
StatisticsList.TryParse(val, out result));
}
/// <summary>
/// Compares Sufficient Statistics.
/// </summary>
/// <param name="stats">Sufficient Statistics.</param>
/// <returns>Returns true if equal.</returns>
public override bool Equals(SufficientStatistics stats)
{
if (stats == null)
{
return(false);
}
if (IsMissing() && stats.IsMissing())
{
return(true);
}
GaussianStatistics gaussStats = stats.AsGaussianStatistics();
return(_mean == gaussStats._mean && _variance == gaussStats._variance && _sampleSize == gaussStats._sampleSize);
}
/// <summary>
/// Converts current object As Gaussian Statistics.
/// </summary>
/// <returns>Gaussian Statistics.</returns>
public override GaussianStatistics AsGaussianStatistics()
{
return(IsMissing() ? GaussianStatistics.GetMissingInstance : GaussianStatistics.GetInstance(Value, 0, 1));
}
/// <summary>
/// Add two Gaussian Statistics.
/// </summary>
/// <param name="x">GaussianStatistics x.</param>
/// <param name="y">GaussianStatistics y.</param>
/// <returns>Returns added result of two Gaussian Statistics.</returns>
public static GaussianStatistics Add(GaussianStatistics x, GaussianStatistics y)
{
if (x == null)
{
throw new ArgumentNullException("x");
}
if (y == null)
{
throw new ArgumentNullException("y");
}
int rN = x.SampleSize + y.SampleSize;
double rMean = (x.SampleSize * x.Mean + y.SampleSize * y.Mean) / rN;
double rVar = (x.SumOfSquares + y.SumOfSquares) / rN - rMean * rMean;
if (rVar < 0)
{
Helper.CheckCondition(rVar > -1e-10, "Computed negative variance! " + rVar);
rVar = 0;
}
GaussianStatistics result = GaussianStatistics.GetInstance(rMean, rVar, rN);
return result;
}