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phenopix (version 2.4.5)

summarizePhases: An evolution of greenProcess for the combination of uncertainty after processing

Description

The combineUncertainty uses greenProcess to fit all available double logistic equations in the phenopix package and extracts thresholds with all available methods. Then uncertainties can be combined and returned by using summarizePhases and plotted with plotSum. See greenProcess.

Usage

summarizePhases(list, quantiles=c(0.25, 0.75), across.methods=FALSE)

Value

A named list with dataframes for each phenophase method with all replication for each of the included fitting methods. These data can then be combined with the companion functions summarizePhases and plotSum. See examples for details.

Arguments

list

An object in output from combineUncertainty

quantiles

The envelope used for the uncertainty

across.methods

If TRUE, gu and klosterman phenophase methods are combined in a single phenophase estimation, and the same happens for derivatives and trs.

Author

Gianluca Filippa <gian.filippa@gmail.com>

Details

This function uses greenProcess to fit all available double logistic equations in the phenopix package and extracts thresholds with all available methods. Then uncertainties can be combined and returned by using summarizePhases and plotted with plotSum. See greenProcess, summarizePhases, plotSum. This function uses a modellistic approach to combine all uncertainties from all available phenopix fittings, as to get an ensemble of phases with different methods, without necessarily choosing any of them.

Examples

Run this code
if (FALSE) {
  require(zoo) 
  data(bartlett2009.filtered)
  combined.fit <- combineUncertainty(na.approx(filtered.tmp$max.filtered), nrep=100)
# 100 replications for each fitting
  names(combined.fit) # a dataframe for each phenoMethod + a list with all fittings
  fit.summary <- summarizePhases(combined.fit, across.methods=TRUE)
## again a list with one element for each fitting method + two additional items 
## if across.methods is TRUE, which combines gu + klosterman phenophase methods 
## in a single method, and the same happens for trs and derivatives
  plotSum(bartlett2009.filtered, fit.summary, which='klosterman')
## a plot with original timeseries + phenophases and their uncertainty
  }
  

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