SSN (version 1.1.4)

InfoCritCompare: Compare glmssn Information Criteria

Description

InfoCritCompare displays important model criteria for each object of class glmssn object in the model list.

Usage

InfoCritCompare(model.list)

Arguments

model.list

a list of fitted glmssn-class model objects in the form list(model1, model2, ...)

Value

• InfoCritCompare returns a data.frame of the model criteria for each specified glmssn-class object. These are useful for comparing and selecting models. The columns in the data.frame are described below. In the description below 'obs' is an observed data value, 'pred' is its prediction using cross-validation, and 'predSE' is the prediction standard error using cross-validation. [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Details

InfoCritCompare displays important model criteria that can be used to compare and select spatial statistical models. For instance, spatial models can be compared with non-spatial models, other spatial models, or both.

See Also

glmssn, summary.glmssn, AIC, CrossValidationStatsSSN

Examples

library(SSN)
	data(modelFits)

  compare.models <- InfoCritCompare(list(fitNS, fitRE, fitSp, fitSpRE1, fitSpRE2))
  
  # Examine the model criteria
  compare.models

  # Compare the AIC values for all models with random effects
  compare.models[c(2,4,5),c("Variance_Components","AIC")]
  
  # Compare the RMSPE for the spatial models
  compare.models[c(3,4,5),c("Variance_Components","RMSPE")]
  
  # Compare the RMSPE between spatial and non-spatial models
  compare.models[c(1,3),c("formula","Variance_Components", "RMSPE")]