expectation-methods
Extraction of the Expectation, Variance and Covariance of the Linear Statistic
Methods for extraction of the expectation, variance and covariance of the linear statistic.
- Keywords
- methods
Usage
# S4 method for IndependenceLinearStatistic
expectation(object, …)
# S4 method for IndependenceTest
expectation(object, …)# S4 method for Variance
variance(object, …)
# S4 method for CovarianceMatrix
variance(object, …)
# S4 method for IndependenceLinearStatistic
variance(object, …)
# S4 method for IndependenceTest
variance(object, …)
# S4 method for CovarianceMatrix
covariance(object, …)
# S4 method for IndependenceLinearStatistic
covariance(object, …)
# S4 method for IndependenceTest
covariance(object, …)
Arguments
- object
an object from which the expectation, variance or covariance of the linear statistic can be extracted.
- …
further arguments (currently ignored).
Details
The methods expectation
, variance
and covariance
extract
the expectation, variance and covariance, respectively, of the linear
statistic.
Value
The expectation, variance or covariance of the linear statistic extracted from
object
. A numeric vector or matrix.
Examples
# NOT RUN {
## Example data
dta <- data.frame(
y = gl(3, 2),
x = sample(gl(3, 2))
)
## Asymptotic Cochran-Mantel-Haenszel Test
ct <- cmh_test(y ~ x, data = dta)
## The linear statistic, i.e., the contingency table...
(l <- statistic(ct, type = "linear"))
## ...and its expectation...
(El <- expectation(ct))
## ...and covariance
(Vl <- covariance(ct))
## The standardized contingency table...
(l - El) / sqrt(variance(ct))
## ...is identical to the standardized linear statistic
statistic(ct, type = "standardized")
# }