confint.fair.model {fairml} | R Documentation |
Confidence Intervals for Fair Models
Description
Confidence intervals for the parameters of the models in the fairml package.
Usage
## S3 method for class 'fair.model'
confint(object, parm, level = 0.95, method = "boot",
method.args = list(), ...)
## S3 method for class 'fair.confint'
plot(x, support = FALSE, ...)
Arguments
object |
an object of class |
parm |
a character vector, the names of the parameters to compute the confidence intervals for. The default is to do that for all parameters. |
level |
a number between 0 and 1, the coverage of the confidence intervals. |
method |
a character string, the method used to compute the confidence intervals. See below for details. |
method.args |
optional arguments passed to the |
... |
additional arguments (unused). |
x |
an object of class |
support |
a logical value, whether to draw a vertical line at zero. |
Details
The only available method
is "boot"
, which implements
nonparametric bootstrap with observation resampling. It has the following
optional arguments:
-
response
,predictors
,sensitive
: the data the model was fitted from. -
R
: a positive integer number, the number of bootstrap samples. The default value is200
. -
m
: a positive integer number, the size of bootstrap samples. The default value is the size of the original sample.
Value
confint()
returns an object of class fair.confint
which wraps
a two- or three-dimensinal matrix. The upper and lower bounds of the
confidence intervals in the columns, the variables are in the rows.
Author(s)
Marco Scutari
Examples
mgaus = fgrrm(response = vu.test$gaussian, predictors = vu.test$X,
sensitive = vu.test$S, unfairness = 0.05, family = "gaussian")
ci = confint(mgaus, method = "boot",
method.args = list(response = vu.test$gaussian, predictors = vu.test$X,
sensitive = vu.test$S, R = 20))
ci
plot(ci)