43.5 Parameter Estimates (.NET, C#, CSharp, VB, Visual Basic, F#)
The ParameterEstimates property on LogisticRegression gets an array of LogisticRegressionParameter estimate objects. This class tests statistical hypotheses about estimated parameters in logistic regressions:
● Value gets the value of the parameter.
● StandardError gets the standard error of the parameter.
● ParameterIndex gets the index of the parameter in the linear regresssion.
● Beta gets the standardized beta coefficient. Beta coefficients are weighted by the ratio of the standard deviation of the independent variable over the standard deviation of the dependent variable.
● ConfidenceInterval() returns the 1 - alpha confidence interval for the parameter.
● TStatistic() returns the t-statistic for the null hypothesis that the parameter is equal to a given test value.
● TStatisticPValue() returns the p-value for a t-test with the null hypothesis that the parameter is equal to a given test value versus the alternative hypothesis that it is not.
● TStatisticCriticalValue() gets the critical value of the t-statistic for the specified alpha level.
For instance, this code prints out the model parameter estimates and standard error.
Code Example – C# logistic regression
var parameterEstimates = lr.ParameterEstimates;
for ( int i = 0; i < parameterEstimates.Length; i++ )
{
var estimate = parameterEstimates[i];
if ( i == 0 )
{
Console.WriteLine( "Constant term = {0}, SE = {1}",
estimate.Value, estimate.StandardError);
}
else
{
Console.WriteLine( "Coefficient for {0} = {1}, SE = {2}",
df[i].Name, estimate.Value, estimate.StandardError);
}
}
Code Example – VB logistic regression
Dim ParameterEstimates = LR.ParameterEstimates
For I As Integer = 0 To ParameterEstimates.Length - 1
Dim Estimate = ParameterEstimates(I)
If (I = 0) Then
Console.WriteLine("Constant term = {0}, SE = {1}",
Estimate.Value, Estimate.StandardError)
Else
Console.WriteLine("Coefficient for {0} = {1}, SE = {2}",
DF(I).Name, Estimate.Value, Estimate.StandardError)
End If
Next