View source: R/datacggm_tools.R
ColMeans + ColMeans | R Documentation |
Retrieve column means and column variances of a “datacggm” object.
ColMeans(x) ColVars(x)
x |
an object of class ‘ |
For an R object x
of class ‘datacggm
’, ColMeans
(ColVars
) retrieves the column means (variances) of the matrices obtained by getMatrix(x, "Y")
and getMatrix(x, "X")
. For the response variables, marginal means and variances are estimated using a EM-algorithm under the assumption that the p response variables are marginally normally distributed (see also Details section in datacggm
). For the numeric predictor variables, marginal means and variances are computed by mean
and var
, whereas, for categorical data, ColMeans
(ColVars
) retrieves the statistical mode and the Gini-Simpson Index, respectively.
ColMeans
(ColVars
) returns a named list with the columns means (variances).
Luigi Augugliaro (luigi.augugliaro@unipa.it)
datacggm
, rcggm
, qqcnorm
and hist.datacggm
.
set.seed(123) n <- 1000L p <- 3L b0 <- rep(0, p) Z <- rcggm(n = n, b0 = b0, probl = 0.05, probr = 0.05) ColMeans(Z) ColVars(Z) n <- 1000L p <- 3L q <- 2 b0 <- runif(p) B <- matrix(runif(q * p), nrow = q, ncol = p) X <- matrix(rnorm(n * q), nrow = n, ncol = q) Z <- rcggm(n = n, b0 = b0, X = X, B = B, probl = 0.05, probr = 0.05) ColMeans(Z) ColVars(Z)
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