data.combine {phenmod}

Main function to combine timeseries

Description

This function creates a station net and builds clusters of stations out of it. These clusters are used to create combined timeseries.

Usage

data.combine(dataset, range=5000, alt.range=50, shuffle=TRUE, 
				tries=100, silent=FALSE, out2File=FALSE,
				clusters.tmp.file="tmpcluster.RData")

Arguments

dataset

A dataset created by data.extract containing the information that should be used to generate the combined timeseries.

range

The maximum distance between two stations that should be connected in the station net.

alt.range

The maximum altitude difference between two stations that should be connected in the station net.

shuffle

A boolean value determining wether the stations should be processed in their order (value: FALSE) or if they should be shuffled befor processing (value: TRUE). Shuffled stations produce different results each run.

tries

If value of ‘shuffle’ is true, the integer value ‘tries’ determines how much cluster-lists should be created. The cluster-list with the lowest number of entries will be returned (this will increase the size of the clusters).

silent

A boolean value determining wether the function should generate output messages or not.

out2File

A boolean value determining wether the output will be stored in log-files.

clusters.tmp.file

A file where the clusters are saved for evaluation. If the value is NULL, no file will be created.

Details

This function joins the functions data.combine.stationNet, data.combine.clusters and data.combine.timeseries.

Value

A dataset containing the combined timeseries as a data.frame with same columns like a data.frame created by data.extract.

Author(s)

Daniel Doktor, Maximilian Lange

References

Schaber J., Badeck F. (2002). Evaluation of methods for the combination of phenological time series and outlier detection. Tree Physiology, 22:973-982

See Also

data.combine.clusters,data.combine.stationNet,data.combine.timeseries

Examples

  ## load extracted observations as created by 'data.extract'
  data(extractedObs)
  
  ## combine timeseries
  data.combined <- data.combine(dataset=extractedObs, range=5000, 
				alt.range=50, shuffle=TRUE, tries=3, 
				silent=FALSE, out2File=FALSE, 
				clusters.tmp.file=NULL)