BUILT-IN MATHEMATICA SYMBOL

Weights

Weights
is an option for various fitting and other functions which specifies weights to associate with data elements.

Using VarianceEstimatorFunction and Weights, is treated as the known uncertainty of measurement and parameter standard errors are effectively computed only from the weights. »

Fit a model using equal weights:

Give explicit weights to the data points:

Compute weights from

values:

Compute weights from the response values:

Fit a model using equal weights:

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Give explicit weights to the data points:

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Compute weights from

values:

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Compute weights from the response values:

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Use weights in a nonlinear model:

Give explicit weights to the data points:

A generalized linear model:

Logit model:

Probit model:

Weight by a function of multiple variables:

Use default equal weights:

Compute weights from the response values:

Fit a nonlinear model using measurement errors as weights:

Obtain standard errors for the parameters:

Compare to estimates with weights not assumed to be from measurement errors:

Weights impact the relative importance of data points on the fitting:

Scaling by a constant does not change the parameter estimates:

Obtain parameter estimates from a weighted linear fitting:

LeastSquares gives the equivalent result when weights are incorporated: