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portes  

Portmanteau Tests for Time Series Models
View on CRAN: Click here


Download and install portes package within the R console
Install from CRAN:
install.packages("portes")

Install from Github:
library("remotes")
install_github("cran/portes")

Install by package version:
library("remotes")
install_version("portes", "6.0")



Attach the package and use:
library("portes")
Maintained by
Esam Mahdi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-09-09
Latest Update: 2023-06-18
Description:
Contains common univariate and multivariate portmanteau test statistics for time series models. These tests are based on using asymptotic distributions such as chi-square distribution and based on using the Monte Carlo significance tests. Also, it can be used to simulate from univariate and multivariate seasonal time series models.
How to cite:
Esam Mahdi (2010). portes: Portmanteau Tests for Time Series Models. R package version 6.0, https://cran.r-project.org/web/packages/portes. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:43), 1.04 (2010-09-09 13:04), 1.07 (2011-03-29 20:21), 1.08 (2013-04-11 07:00), 2-1 (2013-04-17 07:30), 2.1-1 (2013-10-17 07:55), 2.1-3 (2014-08-08 07:36), 2.1-4 (2017-05-06 00:09), 3.0 (2018-07-19 13:10), 5.0 (2020-12-15 13:40)
Other packages that cited portes R package
View portes citation profile
Other R packages that portes depends, imports, suggests or enhances
Complete documentation for portes
Functions, R codes and Examples using the portes R package
Some associated functions: BoxPierce . CRSP . DEXCAUS . EconomicUK . GNPDEF . GetResiduals . Hosking . IbmSp500 . ImpulseVMA . InvertQ . LiMcLeod . LjungBox . MahdiMcLeod . ToeplitzBlock . WestGerman . monthintel . portes-package . portest . varima.sim . vma.sim . 
Some associated R codes: BoxPierce.R . GetResiduals.R . Hosking.R . ImpulseVMA.R . InvertQ.R . LiMcLeod.R . LjungBox.R . ToeplitzBlock.R . portest.R . varima.sim.R . vma.sim.R .  Full portes package functions and examples
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