oemfit | R Documentation |
These functions have been renamed and deprecated in oem:
oemfit()
(use oem()
), cv.oemfit()
(use cv.oem()
), print.oemfit()
,
plot.oemfit()
, predict.oemfit()
, and
coef.oemfit()
.
oemfit( formula, data = list(), lambda = NULL, nlambda = 100, lambda.min.ratio = NULL, tolerance = 0.001, maxIter = 1000, standardized = TRUE, numGroup = 1, penalty = c("lasso", "scad", "ols", "elastic.net", "ngarrote", "mcp"), alpha = 3, evaluate = 0, condition = -1 ) cv.oemfit( formula, data = list(), lambda = NULL, type.measure = c("mse", "mae"), ..., nfolds = 10, foldid, penalty = c("lasso", "scad", "elastic.net", "ngarrote", "mcp") ) ## S3 method for class 'oemfit' plot( x, xvar = c("norm", "lambda", "loglambda", "dev"), xlab = iname, ylab = "Coefficients", ... ) ## S3 method for class 'oemfit' predict( object, newx, s = NULL, type = c("response", "coefficients", "nonzero"), ... ) ## S3 method for class 'oemfit' print(x, digits = max(3, getOption("digits") - 3), ...)
formula |
an object of 'formula' (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under 'Details' |
data |
an optional data frame, list or environment (or object coercible by 'as.data.frame' to a data frame) containing the variables in the model. If not found in 'data', the variables are taken from 'environment(formula)', typically the environment from which 'oemfit' is called. |
lambda |
A user supplied |
nlambda |
The number of |
lambda.min.ratio |
Smallest value for |
tolerance |
Convergence tolerance for OEM. Each inner
OEM loop continues until the maximum change in the
objective after any coefficient update is less than |
maxIter |
Maximum number of passes over the data for all lambda values; default is 1000. |
standardized |
Logical flag for x variable standardization, prior to
fitting the model sequence. The coefficients are always returned on
the original scale. Default is |
numGroup |
Integer value for the number of groups to use for OEM fitting. Default is 1. |
penalty |
type in lower letters. Different types include 'lasso', 'scad', 'ols' (ordinary least square), 'elastic-net', 'ngarrote' (non-negative garrote) and 'mcp'. |
alpha |
alpha value for scad and mcp. |
evaluate |
debugging argument |
condition |
Debugging for different ways of calculating OEM. |
type.measure |
type.measure measure to evaluate for cross-validation.
|
... |
arguments to be passed to |
nfolds |
number of folds for cross-validation. default is 10. |
foldid |
an optional vector of values between 1 and nfold specifying which fold each observation belongs to. |
x |
fitted |
xvar |
what is on the X-axis. "norm" plots against the L1-norm of the coefficients, "lambda" against the log-lambda sequence, and "dev" against the percent deviance explained. |
xlab |
x-axis label |
ylab |
y-axis label |
object |
fitted |
newx |
matrix of new values for x at which predictions are to be made. Must be a matrix. |
s |
Value(s) of the penalty parameter lambda at which predictions are required. Default is the entire sequence used to create the model. |
type |
not used. |
digits |
significant digits in print out. |
The sequence of models implied by 'lambda' is fit by OEM algorithm.
Bin Dai
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