dyn.scale: Dynamical Scale, Moments, and Weights
In longitudinal: Analysis of Multiple Time Course Data

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/dyn.scale.R

time2weights computes weights corresponding to time points

dyn.weights computes these weights for a given longitudinal matrix.

dyn.moments computes means and variances for the variables in a longitudinal object.

dyn.scale centers and standardizes a longitudinal matrix.

  time2weights(t)
  dyn.weights(x)
  dyn.moments(x)
  dyn.scale(x, center=TRUE, scale=TRUE)

`t`	a vector with time points
`x`	a `longitudinal` object, or a matrix
`center`	logical value
`scale`	logical value

The dynamical weights are computed assuming a linear spline - see Opgen-Rhein and Strimmer (2006a,b). The dynamical mean and variance etc. are then simply weighted versions of the usual empirical estimators.

A vector with weights (time2weights and dyn.weights), a list containing the column means and variances (dyn.moments), or a rescaled longitudinal matrix (dyn.scale).

Rainer Opgen-Rhein and Korbinian Strimmer (https://strimmerlab.github.io).

Opgen-Rhein, R., and K. Strimmer. 2006a. Inferring gene dependency networks from genomic longitudinal data: a functional data approach. REVSTAT 4:53-65.

Opgen-Rhein, R., and K. Strimmer. 2006b. Using regularized dynamic correlation to infer gene dependency networks from time-series microarray data. The 4th International Workshop on Computational Systems Biology, WCSB 2006 (June 12-13, 2006, Tampere, Finland).

wt.scale.

# load "longitudinal" library
library("longitudinal")

# weights of for the data points in tcell data
data(tcell)
dyn.weights(tcell.34)

# dynamical moments
dyn.moments(tcell.34)