msefun.normal: Prediction means squared errors for hold out data in cross...
In nnlasso: Non-Negative Lasso and Elastic Net Penalized Generalized Linear Models
Description
Usage
Arguments
Details
Value
Author(s)
Description
The function computes Prediction means squared errors for hold out data of ith fold
Usage
1
msefun.normal(lambda1,f1,xi,yi)
Arguments
lambda1
value of lambda
f1
A fitted ‘nnlasso’ object
xi
Hold out data of predictor variables
yi
Hold out data of response variables
Details
This function is internal and used by cross validation routines.
Value
A value of prediction mean squared error
Author(s)
Baidya Nath Mandal and Jun Ma
nnlasso documentation built on May 2, 2019, 8:19 a.m.
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Description Usage Arguments Details Value Author(s)
Description
The function computes Prediction means squared errors for hold out data of ith fold
Usage
1 | msefun.normal(lambda1,f1,xi,yi)
|
Arguments
lambda1 |
value of lambda |
f1 |
A fitted ‘nnlasso’ object |
xi |
Hold out data of predictor variables |
yi |
Hold out data of response variables |
Details
This function is internal and used by cross validation routines.
Value
A value of prediction mean squared error
Author(s)
Baidya Nath Mandal and Jun Ma
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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