Description Usage Arguments Details Author(s) See Also
Internal camel functions
1 2 3 4 5 6 7 8 9 10 11 12 13 | tiger.likelihood(Sigma, Omega)
tiger.tracel2(Sigma, Omega)
camel.tiger.cv(obj, loss=c("likelihood", "tracel2"), fold=5)
part.cv(n, fold)
camel.tiger.clime.mfista(Sigma, d, maxdf, mu, lambda, shrink, prec, max.ite)
camel.tiger.slasso.mfista(data, n, d, maxdf, mu, lambda, shrink, prec, max.ite)
camel.slim.lad.mfista(Y, X, lambda, nlambda, n, d, maxdf, mu, max.ite, prec,
intercept, verbose)
camel.slim.sqrt.mfista(Y, X, lambda, nlambda, n, d, maxdf, mu, max.ite, prec,
intercept, verbose)
camel.slim.dantzig.mfista(Y, X, lambda, nlambda, n, d, maxdf, mu, max.ite, prec,
intercept, verbose)
camel.cmr.mfista(Y, X, lambda, nlambda, n, d, m, mu, max.ite, prec)
|
Sigma |
Covariance matrix. |
Omega |
Inverse covariance matrix. |
obj |
An object with S3 class returned from |
loss |
Type of loss function for cross validation. |
fold |
The number of fold for cross validatio. |
n |
The number of observations (sample size). |
d |
Dimension of data. |
m |
Columns of parameters in multivariate regression. |
maxdf |
Maximal degree of freedom. |
lambda |
Grid of non-negative values for the regularization parameter lambda. |
nlambda |
The number of the regularization parameter lambda. |
shrink |
Shrinkage of regularization parameter based on precision of estimation. |
mu |
The smooth surrogate parameter. |
prec |
Stopping criterion. |
max.ite |
Maximal value of iterations. |
data |
|
Y |
Dependent variables in linear regression. |
X |
Design matrix in linear regression. |
intercept |
Whether the intercept is included in the model. |
verbose |
Tracing information printing is disabled if |
These are not intended for use by users.
Xingguo Li, Tuo Zhao, and Han Liu
Maintainer: Xingguo Li <xingguo.leo@gmail.com>
camel.tiger
, camel.slim
, camel.cmr
and camel-package
.
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