/// <summary>
/// Computes the best-fit linear logistic regression from the data.
/// </summary>
/// <returns>The fit result.</returns>
/// <remarks>
/// <para>Linear logistic regression is a way to fit binary outcome data to a linear model.</para>
/// <para>The method assumes that binary outcomes are encoded as 0 and 1. If any y-values other than
/// 0 and 1 are encountered, it throws an <see cref="InvalidOperationException"/>.</para>
/// <para>The fit result is two-dimensional. The first parameter is a, the second b.</para>
/// </remarks>
/// <exception cref="InsufficientDataException">There are fewer than three data points.</exception>
/// <exception cref="InvalidOperationException">There is a y-value other than 0 or 1.</exception>
public LinearLogisticRegressionResult LinearLogisticRegression()
{
List <bool> y = yData.Select(v => { if (v == 0.0)
{
return(false);
}
else if (v == 1.0)
{
return(true);
}
else
{
throw new InvalidOperationException();
} }).ToList();
return(Bivariate.LinearLogisticRegression(y, xData));
}
