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OlsEstimate

An ordinary least-squares estimate: the coefficients and how precisely each is known, without the inference table.

public sealed class OlsEstimate

Properties — Coefficients, StandardErrors and TStatistics are parallel lists in the design's own order, intercept first when one was fitted; the standard errors are the non-robust ones. ResidualSumOfSquares is the sum of the squared residuals, which a likelihood or an information criterion is read from. ResidualDegreesOfFreedom is the rows less the parameters estimated. HasIntercept says whether a constant was fitted, and so whether Coefficients starts with it.

Example — without an intercept the slope takes the whole line, and one more degree of freedom is left.

using Lodestar.Stats.Regression;

double[] design = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0];
double[] response = [2.1, 3.9, 6.2, 7.8, 10.1, 12.2, 13.8, 16.1];

OlsEstimate throughOrigin = OrdinaryLeastSquares.Estimate(design, response, featureCount: 1, withIntercept: false);

double slope = Math.Round(throughOrigin.Coefficients[0], 4);  // => 2.0039
int degrees = throughOrigin.ResidualDegreesOfFreedom;         // => 7
bool intercept = throughOrigin.HasIntercept;                  // => False

Remarks — there is no public constructor. An estimate is what OrdinaryLeastSquares.Estimate returns. A class rather than a record, for OlsSummary's reason: a record's equality would compare the lists by reference.

Applies to — net10.0, netstandard2.0.

See also — OrdinaryLeastSquares.Estimate, OlsSummary.