ml.ic: Multicore l.ic for heavy tasks
In anthonyyazdani/OOS: GLM's out of sample (OOS) performances
Description
Usage
Arguments
Value
Description
Multicore l.ic for heavy tasks
Usage
1
ml.ic(exprs, df, family, penalty = 2, cl = detectCores())
Arguments
exprs
List of GLM formulas.
df
Data.frame.
family
Object : a description of the error distribution.
penalty
numeric specifying the ‘weight’ of the equivalent degrees of freedom. (penalty = 2 is the AIC and penalty = log(n) is the BIC)
cl
Number of CPU cores on the current host.
Value
The Information Criterion for all formulas in 'exprs'.
anthonyyazdani/OOS documentation built on Sept. 5, 2020, 12:54 a.m.
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Description Usage Arguments Value
Description
Multicore l.ic for heavy tasks
Usage
1 | ml.ic(exprs, df, family, penalty = 2, cl = detectCores())
|
Arguments
exprs |
List of GLM formulas. |
df |
Data.frame. |
family |
Object : a description of the error distribution. |
penalty |
numeric specifying the ‘weight’ of the equivalent degrees of freedom. (penalty = 2 is the AIC and penalty = log(n) is the BIC) |
cl |
Number of CPU cores on the current host. |
Value
The Information Criterion for all formulas in 'exprs'.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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