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pastecs (version 1.0-2)

Package for Analysis of Space-Time Ecological Series

Description

Regulation, decomposition and analysis of space-time series. The pastecs library is a PNEC-Art4 and IFREMER (Benoit Beliaeff ) initiative to translate PASSTEC 2000 (http://www.obs-vlfr.fr/~enseigne/anado/passtec/passtec.htm).

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Version

Install

install.packages('pastecs')

Monthly Downloads

11,770

Version

1.0-2

License

GNU Public Licence 2.0 or above at your convenience

Maintainer

Philippe Grosjean

Last Published

February 1st, 2024

Functions in pastecs (1.0-2)

Time series decomposition using differences (trend elimination)

Determine matching observation with a tolerance in time-scale

Time series decomposition using eigenvector filtering (EVF)

Is this object a time series?

Calculate Pennington statistics

Calculate and plot a turnogram for a regular time series

Descriptive statistics on a data frame or time series

Collect parameters ("specifications") from one object to use them in another analysis

Decomposition of one or several regular time series using various methods

Convert a 'regul' or a 'tsd' object into a time series

Pennington statistics on a data frame or time series

Adjust regulation parameters

Time series decomposition by the LOESS method

Sliding statistics

Compute and plot a distogram

Choose variables using the Escoufier's equivalent vectors method

Complete disjoined coded data (binary coding)

Format a nice time units for labels in graphs

Get the last element of a vector

Regulation of a series using a linear interpolation

Convert time units from "days" to "years" or back

AutoD2, CrossD2 or CenterD2 analysis of a multiple time-series

Test if an increasing or decreasing trend exists in a time series

Sort variables by abundance

Gleissberg distribution probability

Regulate a series using the area method

Regulation of one or several time series using various methods

Compute and plot a semi-variogram

Get the first element of a vector

Calculate local trends using cumsum

Test various regulation parameters

Buys-Ballot table

Regulate a series using the constant value method

Extract a subset of the original dataset

Time series decomposition using a moving average

Time series decomposition using a running median

Time series decomposition using a regression model

Regulation of a time series using splines

Analyze turning points (peaks or pits)

A data frame of 163 benthic species measured across a transect

.gleissberg.table

Table of probabilities according to the Gleissberg distribution

A data frame of six phytoplankton taxa followed in time at one station

Several zooplankton taxa measured across a transect

Physico-chemical records at the same stations as for marbio