Description Usage Arguments Details Value Side Effects Note Author(s) See Also Examples
A function to set options for stability-based biomarker selection in the BioMark package, or to return the current options.
1 | biom.options(..., reset = FALSE)
|
... |
a single list, a single character vector, or any number of named arguments (name = value). |
reset |
logical: if TRUE all options are set to their factory defaults. |
If called with no arguments, or with an empty list as the single
argument, biom.options
returns the current options.
If called with a character vector as the single argument, a list with the arguments named in the vector are returned.
If called with a non-empty list as the single arguments, the list elements should be named, and are treated as named arguments to the function.
Otherwise, biom.options
should be called with one or more named
arguments name = value. For each argument, the option named
name will be given the value value.
The options are saved in an envirtonment variable
.biom.Options
, and remain in effect until the end of the
session. If the environment is saved upon exit, they will be
remembered in the next session.
The recognised options are:
Maximal number of jackknife iterations. Default: 100.
Size of the out-of-bag fraction, either given as an absolute number (oob.size) or as a fraction. Default is to leave out ten percent. If oob.size is given explicitly, it takes precedence over oob.fraction. Default: oob.fraction = .1.
Use 1 to always include all variables - use a smaller fraction to have a different random subset of all variables in each iteration (stability-based identification). Default: .7.
The number of "top" coefficients taken into account in
stability-based biomarker identification. If a variable appears
consistently among the ntop
biggest coefficients, it is said
to be stable. If ntop is a number between 0 and 1, it is taken to
indicate the fraction of variables to be included in the model.
Default: 10.
The minimal fraction of times a variable should be in the top list to be considered as a potential biomarker (stability-based identification). Setting this argument to 0 will lead to a list containing all coefficients that were present in the top list at least once - a value of 1 only returns those variables that are selected in every iteration. Default: .1.
The number of permutations to establish null distributions for PCR, PLS and VIP statistics in the Higher-Criticism approach. Default: 10,000.
All biomarker selection methods available within
BioMark. Currently equal to c("studentt", "shrinkt", "pcr",
"pls", "vip", "lasso"
.
The names of the univariate biomarker selection
methods currently known to BioMark. Currently equal to
c("studentt", "shrinkt")
The default of the alpha parameter in the HC method. Value: 0.1.
a list of arguments passed to the underlying
glmnet
function, such as family
, nlambda
,
alpha
, lambda
, or lambda.min.ratio
. For
binary classification, the "binomial" family is the default, but
the most similar setting compared to the other methods in the package
is family = "gaussian"
. For choices other than the default,
a warning is printed to the screen.
A list with the (possibly changed) options. If any named argument (or list element) was provided, the list is returned invisibly.
If any named argument (or list element) was provided,
biom.options
updates the elements of the option list
.biom.Options$options
.
This function is based on the pls.options
function in package pls.
Ron Wehrens
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## Return current options:
biom.options()
biom.options("max.seg")
## Set options:
biom.options(max.seg = 100, oob.fraction = .2)
biom.options(lasso = list(alpha = .75, nlambda = 50))
biom.options()
## the next line removes some options - for these, glmnet defaults will be used
biom.options(lasso = list(alpha = .9, family = "binomial"))
## Restore factory settings:
biom.options(reset = TRUE)
|
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