Calculates the covariance matrix of the normally standardized variables obtained from the columns of x
x
covariance(x, data = x, cpf = NULL, mean = 0, sd = 1, step = NULL, prec = 10^-4, use = "pairwise.complete.obs", type = 3, extremes = TRUE, sample = NULL, origin_x = NULL, origin_data = origin_x)
x
: variabledata
: a sample of data on which a non-parametric pghjjrobability distribution is estimatedcpf
: cumulative probability distribution. If NULL
(default) is calculated as ecdf(data)
mean
: mean (expected value) of the normalized random variable. Default is 0.sd
: standard deviation of the normalized random variable. Default is 1.step
: vector of values in which step discontinuities of the cumulative probability function occur. Default is NULL
prec
: amplitude of the neighbourhood of the step discontinuities where cumulative probability function is treated as non continuous.use
: see cov
type
: see quantile
extremes
: logical variable. If TRUE
(default) the probability or frequency is multiplied bywhere is the length of data
sample
: information about sample or probability distribution. Default is NULL
origin_x
: date corresponding to the first row of x
origin_data
: date corresponding to the first row of data
a matrix with the normalized variable or its inverse
normalizeGaussian_severalstations
,normalizeGaussian
@note It applies normalizeGaussian_severalstations
to x
and data
and then calculates the covariances among the column. See the R code for further details
Emanuele Cordano, Emanuele Eccel
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