VarianceEstimatorFunction
is an option for LinearModelFit and NonlinearModelFit which specifies the variance estimator to use.
Details
- VarianceEstimatorFunction defines the function for estimating the error variance scale for linear and nonlinear models with assumed normally distributed errors.
- With the setting VarianceEstimatorFunction->f, the variance scale is estimated by f[res,w] where res={y1-,y2-,…} is the list of residuals and w is the list of weights, as specified by the setting for the Weights option.
- The default setting Automatic estimates the variance scale by where is the weight for the th data point, is the th residual, is the number of data elements, and is the number of parameters in the model.
- With VarianceEstimatorFunction->(1&) and Weights->{1/Δy12,1/Δy22,…}, Δyi is treated as the known uncertainty of measurement yi and parameter standard errors are effectively computed only from the weights. »
Examples
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Wolfram Research (2008), VarianceEstimatorFunction, Wolfram Language function, https://reference.wolfram.com/language/ref/VarianceEstimatorFunction.html.
Text
Wolfram Research (2008), VarianceEstimatorFunction, Wolfram Language function, https://reference.wolfram.com/language/ref/VarianceEstimatorFunction.html.
CMS
Wolfram Language. 2008. "VarianceEstimatorFunction." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/VarianceEstimatorFunction.html.
APA
Wolfram Language. (2008). VarianceEstimatorFunction. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/VarianceEstimatorFunction.html