result.GibbsSampler: a summary of partial results
In Kaukol/IBGS: Variable selection in ultrahigh dimensions using Gibbs sampler
result.GibbsSampler R Documentation
a summary of partial results
Description
a summary of partial results
Usage
result.GibbsSampler(m.matrix, y, x, k, gamma, p0, n.models, info, family)
Arguments
m.matrix
a matrix of generated samples
y
the response variable
x
the predictors
k
the tuning parameter
gamma
the tuning parameter to control the penalty
p0
the number of total predictors
n.models
the number of top selected models
info
the selected model selection criterion from AIC, AICc, BIC and exBIC
family
the type of model from linear, logistic, poisson
Value
a list containing partial results
Kaukol/IBGS documentation built on June 17, 2024, 2:37 p.m.
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| result.GibbsSampler | R Documentation |
a summary of partial results
Description
a summary of partial results
Usage
result.GibbsSampler(m.matrix, y, x, k, gamma, p0, n.models, info, family)
Arguments
m.matrix |
a matrix of generated samples |
y |
the response variable |
x |
the predictors |
k |
the tuning parameter |
gamma |
the tuning parameter to control the penalty |
p0 |
the number of total predictors |
n.models |
the number of top selected models |
info |
the selected model selection criterion from AIC, AICc, BIC and exBIC |
family |
the type of model from linear, logistic, poisson |
Value
a list containing partial results
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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