Learn R Programming

⚠️There's a newer version (1.4.2) of this package.Take me there.

pastecs (version 1.0-3)

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).

Copy Link

Version

Install

install.packages('pastecs')

Monthly Downloads

11,770

Version

1.0-3

License

GNU Public Licence 2.0 or above at your convenience

Maintainer

Philippe Grosjean

Last Published

February 1st, 2024

Functions in pastecs (1.0-3)

Complete disjoined coded data (binary coding)

Descriptive statistics on a data frame or time series

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

Gleissberg distribution probability

Calculate Pennington statistics

Time series decomposition using a moving average

Analyze turning points (peaks or pits)

Adjust regulation parameters

Format a nice time units for labels in graphs

Calculate and plot a turnogram for a regular time series

Time series decomposition using a regression model

Is this object a time series?

Regulation of a series using a linear interpolation

Decomposition of one or several regular time series using various methods

Pennington statistics on a data frame or time series

Regulation of a time series using splines

Get the first element of a vector

Determine matching observation with a tolerance in time-scale

Regulate a series using the area method

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

Test various regulation parameters

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

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

Regulation of one or several time series using various methods

Time series decomposition using a running median

Regulate a series using the constant value method

Choose variables using the Escoufier's equivalent vectors method

Sliding statistics

Time series decomposition by the LOESS method

Calculate local trends using cumsum

Sort variables by abundance

Extract a subset of the original dataset

Compute and plot a semi-variogram

Get the last element of a vector

Time series decomposition using eigenvector filtering (EVF)

Buys-Ballot table

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

Time series decomposition using differences (trend elimination)

Compute and plot a distogram

A data frame of 163 benthic species measured across a transect

Physico-chemical records at the same stations as for marbio

Several zooplankton taxa 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