The GAMPL Procedure
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Overview
- Getting Started
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Syntax
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DetailsMissing ValuesThin-Plate Regression SplinesGeneralized Additive ModelsModel Evaluation CriteriaFitting AlgorithmsDegrees of FreedomModel InferenceDispersion ParameterTests for Smoothing ComponentsComputational Method: MultithreadingChoosing an Optimization TechniqueDisplayed OutputODS Table NamesODS Graphics
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Examples
- References
Missing Values
Any observation that has missing values for the response, frequency, weight, offset, or explanatory variables is excluded from the analysis; however, missing values are valid for response and explanatory variables if you specify the MISSING option in the CLASS statement. Observations that have a nonpositive weight or a frequency less than 1 are also excluded. For Poisson and negative binomial distributions, observations that have a negative response value are excluded. For gamma and inverse Gaussian distributions, observations that have a nonpositive response value are excluded.
The estimated linear predictor and the fitted means are not computed for any observation that has missing offset or explanatory variable values. However, if only the response value is missing, the linear predictor and the fitted means can be computed and output to a data set by using the OUTPUT statement.