Combine two or more model selection tables.
## S3 method for class 'model.selection' merge(x, y, suffixes = c(".x", ".y"), ...) ## S3 method for class 'model.selection' rbind(..., deparse.level = 1, make.row.names = TRUE)
a character vector with two elements that are appended respectively to row names of the combined tables.
logical indicating if unique and valid
"model.selection" object containing
models (rows) from all provided tables.
Both Δ_IC values and Akaike weights are recalculated in the resulting tables.
Models in the combined model selection tables must be comparable, i.e. fitted to the same data, however only very basic checking is done to verify that. The models must also be ranked by the same information criterion.
merge method for
data.frame, this method appends
second table to the first (similarly to
## Not run: require(mgcv) ms1 <- dredge(glm(Prop ~ dose + I(dose^2) + log(dose) + I(log(dose)^2), data = Beetle, family = binomial, na.action = na.fail)) fm2 <- gam(Prop ~ s(dose, k = 3), data = Beetle, family = binomial) merge(ms1, model.sel(fm2)) ## End(Not run)
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