model selection table
Build a model selection table.
model.sel(object, ...)
## Default S3 method:
model.sel(object, ..., rank = NULL, rank.args = NULL,
beta = c("none", "sd", "partial.sd"), extra)
## S3 method for class 'model.selection'
model.sel(object, rank = NULL, rank.args = NULL, fit = NA,
..., beta = c("none", "sd", "partial.sd"), extra)object |
a fitted model object, a list of such objects, or a
|
... |
more fitted model objects. |
rank |
optional, custom rank function (returning an information
criterion) to use instead of the default |
rank.args |
optional |
fit |
logical, stating whether the model objects should be re-fitted if
they are not stored in the |
beta |
indicates whether and how the component models' coefficients
should be standardized. See the argument's description in
|
extra |
optional additional statistics to include in the result,
provided as functions, function names or a list of such (best if named
or quoted). See |
model.sel used with "model.selection" object will re-fit model
objects, unless they are stored in object (in attribute "modelList"),
if argument extra is provided, or the requested beta is different
than object's "beta" attribute, or the new rank function
cannot be applied directly to logLik objects, or new rank.args
are given (unless argument fit = FALSE).
An object of class c("model.selection", "data.frame"), being a
data.frame, where each row represents one model and columns contain
useful information about each model: the coefficients, df, log-likelihood, the
value of the information criterion used,
Δ_IC and ‘Akaike
weight’.
If any arguments differ between the modelling function calls, the
result will include additional columns showing them (except for formulas and
some other arguments).
See model.selection.object for its structure.
Kamil Bartoń
Cement$X1 <- cut(Cement$X1, 3) Cement$X2 <- cut(Cement$X2, 2) fm1 <- glm(formula = y ~ X1 + X2 * X3, data = Cement) fm2 <- update(fm1, . ~ . - X1 - X2) fm3 <- update(fm1, . ~ . - X2 - X3) ## ranked with AICc by default (msAICc <- model.sel(fm1, fm2, fm3)) ## ranked with BIC model.sel(fm1, fm2, fm3, rank = AIC, rank.args = alist(k = log(nobs(x)))) # or # model.sel(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x)))) # or # update(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x))))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.