MOdist function

Markov Operator distance for clustering diffusion processes.

Markov Operator distance for clustering diffusion processes.

MOdist(x, M=50, rangeval=range(x, na.rm=TRUE, finite = TRUE))

Arguments

  • x: one or multi-dimensional time series.
  • M: number of splines bases used to approximate the Markov Operator.
  • rangeval: a vector containing lower and upper limit. Default is the range of x.

Details

This function return a lower triangular dist object to be further used in cluster analysis (see examples below).

If x is a one-dimensional time series, the output is the scalar 0, not a dist object.

If x has less than 2 observations, NA is returned.

If time series x contains missing data, then x is converted to a zoo object and missing data are imputed by interpolation.

Returns

  • X: a dist object

Author(s)

Stefano Maria Iacus

References

De Gregorio, A. Iacus, S.M. (2008) Clustering of discretely observed diffusion processes, Computational Statistics and Data Analysis, 54(12), 598-606, tools:::Rd_expr_doi("10.1016/j.csda.2009.10.005") .

Examples

## Not run: data(quotes) plot(quotes) d <- MOdist(quotes) cl <- hclust( d ) groups <- cutree(cl, k=4) cmd <- cmdscale(d) plot( cmd, col=groups) text( cmd, labels(d) , col=groups) plot(quotes, col=groups) plot(quotes, col=groups,ylim=range(quotes)) ## End(Not run)
  • Maintainer: Stefano Maria Iacus
  • License: GPL (>= 2)
  • Last published: 2022-08-09

Useful links