| Type: | Package |
| Title: | Sparse Generative Model and Its EM Algorithm |
| Version: | 0.1-0 |
| Date: | 2015-09-05 |
| Author: | Charles Bouveyron, Julien Chiquet, Pierre Latouche, Pierre-Alexandre Mattei |
| Maintainer: | Julien Chiquet <julien.chiquet@gmail.com> |
| Description: | Implements a generative model that uses a spike-and-slab like prior distribution obtained by multiplying a deterministic binary vector. Such a model allows an EM algorithm, optimizing a type-II log-likelihood. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Imports: | methods |
| Repository: | CRAN |
| Repository/R-Forge/Project: | spinyreg |
| Repository/R-Forge/Revision: | 11 |
| Repository/R-Forge/DateTimeStamp: | 2015-09-07 10:50:53 |
| Date/Publication: | 2015-09-07 18:18:03 |
| NeedsCompilation: | no |
| Packaged: | 2015-09-07 11:07:11 UTC; rforge |
spinyReg
Description
Computethe path of solution of a spinyReg fit.
Usage
spinyreg(X, Y, alpha = 0.1, gamma = 1, z = rep(1, ncol(X)),
intercept = TRUE, normalize = TRUE, verbose = 1, recovery = TRUE,
maxit = 1000, eps = 1e-10)
Arguments
X |
matrix of features. Do NOT include intercept. |
Y |
matrix of responses. |
alpha |
numeric scalar; prior value for the alpha parameter (see the model's details). Default is 0.1. |
gamma |
numeric scalar; prior value for the gamma parameter (see the model's details). Default is 1. |
z |
numeric vector; prior support of active variable. Default
is |
intercept |
logical; indicates if a vector of intercepts
should be included in the model. Default is |
normalize |
logical; indicates if predictor variables should
be normalized to have unit L2 norm before fitting. Default is
|
verbose |
integer; activate verbose mode from '0' (nothing) to '2' (detailed output). should be included in the model. Default is |
recovery |
logical; indicates if the full path of models
should be inspected for model selection. Default is |
maxit |
integer; the maximal number of iteration (i.e. number of alternated optimization between each parameter) in the Expectation/Maximization algorithm. |
eps |
a threshold for convergence. Default is |
Value
an object with class spinyreg, see the
documentation page spinyreg for details.
See Also
See also spinyreg.
Examples
## Not run:
data <- read.table(file="http://statweb.stanford.edu/~tibs/ElemStatLearn/datasets/prostate.data")
x <- data[, 1:8]
y <- data[, 9]
out <- spinyreg(x,y,verbose=2)
## End(Not run)
Class "spinyreg"
Description
Class of object returned by the spinyreg function.
Slots
coefficients:numeric vector of coefficients with respect to the original input. Contains the intercept if the model owns any.
alpha:numeric scalar.
gamma:numeric scalar.
normx:Vector (class
"numeric") containing the square root of the sum of squares of each column of the design matrix.residuals:Vector of residuals.
r.squared:scalar giving the coefficient of determination.
fitted:Vector of fitted values.
monitoring:List (class
"list") which contains various indicators dealing with the optimization process.intercept:Logical which indicates if a intercept is included in the model.
Methods
This class comes with the usual predict(object, newx, ...),
fitted(object, ...), residuals(object, ...), coefficients(object, ...),
print(object, ...) and show(object) generic (undocumented) methods.