Transforms the data X by centring and scaling using \(X_{ij}^{'} = \frac{X_{ij}-\mu_{ij}}{\sigma_{ij}}\) where \(\mu_{ij}\) and \(\sigma_{ij}\) are robust quantile based
sequential estimates for the mean and standard deviation of each variate (column) \(X_{i}\) of X calculated up to time j. The estimates \(\mu_{ij}\) and \(\sigma_{ij}\) are
calculated from sequential estimates for the median and inter-quartile range developed by Tierney et al (1983). This method is the default value for the
transform argument used by the scapa.uv function.
Usage
tierney(X, burnin = 10)
Arguments
X
A numeric matrix containing the data to be transformed. The time series data classes ts, xts, and zoo are also supported.
burnin
Specifies the period used to stabalise the quantile estimates. The default value is 10.