influenceSSN-class: Class "influenceSSN"

Description Objects from the Class Class Structure Extends Author(s) See Also

Description

A class that extends the results of generalized linear models, glmssn objects, for spatial stream networks by adding influence diagnostics and cross-validation predictions to each observation.

Objects from the Class

Objects can be created by functions in the form residual(x), where x is a glmssn-class object.

Class Structure

Objects of class influenceSSN contain 4 list items and have the exact same structure as glmssn-class objects. A influenceSSN object retains the corresponding SpatialStreamNetwork object as the second list item. When residuals(x) is used for a glmssn object, the data for which the model was fit is stored in point.data data.frame of the observed points. This data.frame contains the response variable for the model, and is appended by the following columns:

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  obsval            ## The response value that was used to fit the model
  _fit_
  _resid_           ## The raw residuals
  _resid.stand_     ## Standardized residuals; calculated by dividing the raw
                    ## residuals by the corresponding standard errors
  _resid.student_   ## Studentized residuals
  _leverage_        ## Leverage
  _CooksD_          ## Cook's D
  _resid.crossv_    ## Cross-validation residuals
  _CrossValPred_    ## Cross-validation predictions
  _CrossValStdErr_  ## Estimated cross-validation standard errors.
  

Extends

Class "glmssn", directly.

Author(s)

Jay Ver Hoef support@SpatialStreamNetworks.com

See Also

residuals,glmssn


SSN documentation built on March 13, 2020, 1:49 a.m.