coin (version 1.3-1)

expectation-methods: Extraction of the Expectation, Variance and Covariance of the Linear Statistic

Description

Methods for extraction of the expectation, variance and covariance of the linear statistic.

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).

Value

The expectation, variance or covariance of the linear statistic extracted from object. A numeric vector or matrix.

Details

The methods expectation, variance and covariance extract the expectation, variance and covariance, respectively, of the linear statistic.

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")
# }

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