Description Usage Arguments Details Value
View source: R/model_selection_methods.R
Runs through a model selection algorithm to determine the best model in a given set
1 2 3 | rank_models(..., data = NULL, nested = F, bootstrap = F,
model.type = "ssm", alpha = 0.05, robust = F, eff = 0.6,
B = 50, G = 1e+06, freq = 1, seed = 1337)
|
... |
Different |
data |
A |
nested |
A |
bootstrap |
A |
model.type |
A |
alpha |
A |
robust |
A |
eff |
A |
B |
A |
G |
A |
freq |
A |
seed |
A |
The models MUST be nested within each other. If the models are not nested, the algorithm creates the "common denominator" model.
To supply the models, enter them as: AR1()+WN(), AR1(), 3*AR1()
Any parameter that you wish to use must then be specified. e.g. to specify nested, you must use nested = T. Otherwise, it the function will stop.
Due to the structure of rank.models
, you cannot mix and match AR1()
and GM()
objects.
So you must enter either AR1() or GM() objects.
A rank.models
object.
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