blasso_map: Bayesian LASSO maximum a posteriori estimator
In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities
Description
Usage
Arguments
Value
Description
Bayesian LASSO maximum a posteriori estimator
Usage
1
blasso_map(formula, data, penalty = NULL)
Arguments
formula
model formula
data
a data frame
lambda
either a sequence of numbers, a single number, or NULL to generate a sequence of length equal to nval.
nval
the length of the sequence of candidate lambda values to try.
opt.crit
the criterion to maximize for finding the optimal lambda when a sequence is provided. defaults to the log posterior ("logPost") to act as a MAP estimator, but final prediction error ("fpe") is also an option.
Value
a penreg object
abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.
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Description Usage Arguments Value
Description
Bayesian LASSO maximum a posteriori estimator
Usage
1 | blasso_map(formula, data, penalty = NULL)
|
Arguments
formula |
model formula |
data |
a data frame |
lambda |
either a sequence of numbers, a single number, or NULL to generate a sequence of length equal to nval. |
nval |
the length of the sequence of candidate lambda values to try. |
opt.crit |
the criterion to maximize for finding the optimal lambda when a sequence is provided. defaults to the log posterior ("logPost") to act as a MAP estimator, but final prediction error ("fpe") is also an option. |
Value
a penreg object
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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