covariance function

Calculates the covariance matrix of the normally standardized variables obtained from the columns of 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)

Arguments

• x: variable
• data: a sample of data on which a non-parametric pghjjrobability distribution is estimated
• cpf: 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 by

where $N$ 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

Returns

a matrix with the normalized variable or its inverse

See Also

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

Author(s)

Emanuele Cordano, Emanuele Eccel