Package index • pastecs

All functions
`AutoD2()` `CrossD2()` `CenterD2()`	AutoD2, CrossD2 or CenterD2 analysis of a multiple time-series
`GetUnitText()`	Format a nice time units for labels in graphs
`abund()` `extract(<abund>)` `identify(<abund>)` `lines(<abund>)` `plot(<abund>)` `print(<abund>)` `print(<summary.abund>)` `summary(<abund>)`	Sort variables by abundance
`bnr`	A data frame of 163 benthic species measured across a transect
`buysbal()`	Buys-Ballot table
`daystoyears()` `yearstodays()`	Convert time units from "days" to "years" or back
`decaverage()`	Time series decomposition using a moving average
`deccensus()`	Time decomposition using the CENSUS II method
`decdiff()`	Time series decomposition using differences (trend elimination)
`decevf()`	Time series decomposition using eigenvector filtering (EVF)
`decloess()`	Time series decomposition by the LOESS method
`decmedian()`	Time series decomposition using a running median
`decreg()`	Time series decomposition using a regression model
`disjoin()`	Complete disjoined coded data (binary coding)
`disto()`	Compute and plot a distogram
`escouf()` `print(<escouf>)` `summary(<escouf>)` `print(<summary.escouf>)` `plot(<escouf>)` `lines(<escouf>)` `identify(<escouf>)` `extract(<escouf>)`	Choose variables using the Escoufier's equivalent vectors method
`extract()`	Extract a subset of the original dataset
`first()`	Get the first element of a vector
`.gleissberg.table`	Table of probabilities according to the Gleissberg distribution
`is.tseries()`	Is this object a time series?
`last()`	Get the last element of a vector
`local.trend()` `identify(<local.trend>)`	Calculate local trends using cumsum
`marbio`	Several zooplankton taxa measured across a transect
`marphy`	Physico-chemical records at the same stations as for marbio
`match.tol()`	Determine matching observation with a tolerance in time-scale
`pennington()`	Calculate Pennington statistics
`pgleissberg()`	Gleissberg distribution probability
`regarea()`	Regulate a series using the area method
`regconst()`	Regulate a series using the constant value method
`reglin()`	Regulation of a series using a linear interpolation
`regspline()`	Regulation of a time series using splines
`regul()` `print(<regul>)` `summary(<regul>)` `print(<summary.regul>)` `plot(<regul>)` `lines(<regul>)` `identify(<regul>)` `hist(<regul>)` `extract(<regul>)` `specs(<regul>)` `print(<specs.regul>)`	Regulation of one or several time series using various methods
`regul.adj()`	Adjust regulation parameters
`regul.screen()`	Test various regulation parameters
`releve`	A data frame of six phytoplankton taxa followed in time at one station
`specs()`	Collect parameters ("specifications") from one object to use them in another analysis
`stat.desc()`	Descriptive statistics on a data frame or time series
`stat.pen()`	Pennington statistics on a data frame or time series
`stat.slide()` `print(<stat.slide>)` `plot(<stat.slide>)` `lines(<stat.slide>)`	Sliding statistics
`trend.test()`	Test if an increasing or decreasing trend exists in a time series
`tsd()` `print(<tsd>)` `summary(<tsd>)` `print(<summary.tsd>)` `plot(<tsd>)` `extract(<tsd>)` `specs(<tsd>)` `print(<specs.tsd>)`	Decomposition of one or several regular time series using various methods
`tseries()`	Convert a 'regul' or a 'tsd' object into a time series
`turnogram()` `print(<turnogram>)` `summary(<turnogram>)` `print(<summary.turnogram>)` `plot(<turnogram>)` `identify(<turnogram>)` `extract(<turnogram>)`	Calculate and plot a turnogram for a regular time series
`turnpoints()` `print(<turnpoints>)` `summary(<turnpoints>)` `print(<summary.turnpoints>)` `plot(<turnpoints>)` `lines(<turnpoints>)` `extract(<turnpoints>)`	Analyze turning points (peaks or pits)
`vario()`	Compute and plot a semi-variogram

Reference

All functions