expectation-methods {coin} | R Documentation |

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

## S4 method for signature 'IndependenceLinearStatistic' expectation(object, partial = FALSE, ...) ## S4 method for signature 'IndependenceTest' expectation(object, partial = FALSE, ...) ## S4 method for signature 'Variance' variance(object, ...) ## S4 method for signature 'CovarianceMatrix' variance(object, ...) ## S4 method for signature 'IndependenceLinearStatistic' variance(object, partial = FALSE, ...) ## S4 method for signature 'IndependenceTest' variance(object, partial = FALSE, ...) ## S4 method for signature 'CovarianceMatrix' covariance(object, ...) ## S4 method for signature 'IndependenceLinearStatistic' covariance(object, invert = FALSE, partial = FALSE, ...) ## S4 method for signature 'QuadTypeIndependenceTestStatistic' covariance(object, invert = FALSE, partial = FALSE, ...) ## S4 method for signature 'IndependenceTest' covariance(object, invert = FALSE, partial = FALSE, ...)

`object` |
an object from which the expectation, variance or covariance of the linear statistic can be extracted. |

`partial` |
a logical indicating that the partial result for each block should be
extracted. Defaults to |

`invert` |
a logical indicating that the Moore-Penrose inverse of the covariance should
be extracted. Defaults to |

`...` |
further arguments (currently ignored). |

The methods `expectation`

, `variance`

and `covariance`

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

For tests of conditional independence within blocks, the partial result for
each block is obtained by setting `partial = TRUE`

.

The expectation, variance or covariance of the linear statistic extracted from
`object`

. A matrix or array.

## 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... (T <- statistic(ct, type = "linear")) ## ...and its expectation... (mu <- expectation(ct)) ## ...and variance... (sigma <- variance(ct)) ## ...and covariance... (Sigma <- covariance(ct)) ## ...and its inverse (SigmaPlus <- covariance(ct, invert = TRUE)) ## The standardized contingency table... (T - mu) / sqrt(sigma) ## ...is identical to the standardized linear statistic statistic(ct, type = "standardized") ## The quadratic form... U <- as.vector(T - mu) U %*% SigmaPlus %*% U ## ...is identical to the test statistic statistic(ct, type = "test")

[Package *coin* version 1.4-1 Index]