dyn.scale {longitudinal}R Documentation

Dynamical Scale, Moments, and Weights

Description

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.

Usage

  time2weights(t)
  dyn.weights(x)
  dyn.moments(x)
  dyn.scale(x, center=TRUE, scale=TRUE, scale.by = c("sd", "mean"))

Arguments

t a vector with time points
x a longitudinal object, or a matrix
center logical value
scale logical value
scale.by determines whether the columns are standardized by the standard errors of the respective variables ("sd", the default) or by the column means ("mean").

Details

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.

Value

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).

Author(s)

Rainer Opgen-Rhein (http://opgen-rhein.de) and Korbinian Strimmer (http://strimmerlab.org).

References

Opgen-Rhein, R., and K. Strimmer. 2006a. Inferring gene dependency networks from genomic longitudinal data: a functional data approach. REVSTAT 4:53-65. (http://http://www.ine.pt/revstat/)

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). (http://www.cs.tut.fi/wcsb06/)

See Also

weighted.scale.

Examples

# 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)


[Package longitudinal version 1.1.3 Index]