TIme series of Grouped ERrors

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Documentation for package ‘tiger’ version 0.2.3.1

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tiger-package TIme series of Grouped ERrors
box.plots Evaluation plots for temporal dynamics of model performance
change.order.clusters Change numbering of clusters
color.factor Create colors with intensity according to the magnitude of a value
correl Calculate correlation structure
correlated Calculate correlation structure
count.diff.direction.error Compare sign of derivatives
d.dates Example data for TIGER package
diagnostic_dawson Calculate a number of objectives to compare time series
diagnostic_series Calculate a number of objectives to compare time series
diagnostic_window Calculate a number of objectives to compare time series
eD Euclidean Distance
errors.in.time Evaluation plots for temporal dynamics of model performance
example.peaks Synthetic peak errors
include.others Internal Function: evaluate box plot
k_hyd Hydrological recession constant
k_rel Mean ratio of hydrological recession constants of two discharge time series
lagtime Lagtime between two time series
nashS Calculates the (weighted) Nash Suttcliffe Efficiency coefficient
nashS_HF Calculates the (weighted) Nash Suttcliffe Efficiency coefficient
p.synth.peak.error Generate synthetic peaks and peak errors
p.validityIndex Evaluation plots for temporal dynamics of model performance
peaks.in.clusters Evaluation plots for temporal dynamics of model performance
peaks.measures Evaluation plots for temporal dynamics of model performance
peaks.on.som Evaluation plots for temporal dynamics of model performance
reference.peak Synthetic peak errors
scatterplot Evaluation plots for temporal dynamics of model performance
synth.peak Generate synthetic peaks and peak errors
synth.peak.error Generate synthetic peaks and peak errors
tiger Calculate temporal dynamics of model performance
tiger.example Example data for TIGER package
tiger.multi Example data for TIGER package
tiger.peaks Calculate temporal dynamics of model performance
tiger.single Example data for TIGER package
to.uniform Transform data to uniform distribution
validityIndex Validity Index for fuzzy clustering