Package: tsoutliers 0.6-10

tsoutliers: Detection of Outliers in Time Series

Detection of outliers in time series following the Chen and Liu (1993) <doi:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.

Authors:Javier López-de-Lacalle <[email protected]>

tsoutliers_0.6-10.tar.gz
tsoutliers_0.6-10.zip(r-4.7-any)tsoutliers_0.6-10.zip(r-4.6-any)tsoutliers_0.6-10.zip(r-4.5-any)
tsoutliers_0.6-10.tgz(r-4.6-any)tsoutliers_0.6-10.tgz(r-4.5-any)
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tsoutliers_0.6-10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tsoutliers/json (API)

# Install 'tsoutliers' in R:

install.packages('tsoutliers', repos = c('https://javlacalle.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

bde9915 - Data Set: Working Paper 'bde9915'
hicp - Data Set: Harmonised Indices of Consumer Prices
ipi - Data Set: Industrial Production Indices

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.98 score 6 stars 6 packages 267 scripts 1.1k downloads 3 mentions 17 exports 31 dependencies

Last updated from:130b6315f4. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	117
source / vignettes	OK	192
linux-release	OK	123
macos-release	OK	133
macos-oldrel	OK	125
windows-devel	OK	93
windows-release	OK	76
windows-oldrel	OK	95
wasm-release	OK	81

Exports:calendar.effects coefs2poly discard.outliers find.consecutive.outliers JarqueBera.test locate.outliers locate.outliers.iloop locate.outliers.oloop outliers outliers.effects outliers.regressors outliers.tstatistics plot.tsoutliers print.tsoutliers remove.outliers tso tso0

Dependencies:cli colorspace cpp11 farver forecast fracdiff generics ggplot2 glue gtable isoband labeling lattice lifecycle lmtest magrittr nlme nnet R6 RColorBrewer Rcpp RcppArmadillo rlang S7 scales timeDate urca vctrs viridisLite withr zoo

tsoutliers-intro

Introduction

Rendered fromtsoutliers-intro.Rnwusingutils::Sweave

Last update: 2019-02-24
Started: 2015-01-25

Citation

Readme and manuals

Help Manual

Help page	Topics
Automatic Detection of Outliers in Time Series	_PACKAGE
Data Set: Working Paper 'bde9915'	bde9915
Calendar Effects	calendar.effects
Product of the Polynomials in an ARIMA Model	coefs2poly
Stage II of the Procedure: Discard Outliers	discard.outliers
Find outliers at consecutive time points	find.consecutive.outliers
Data Set: Harmonised Indices of Consumer Prices	hicp
Data Set: Industrial Production Indices	ipi
Jarque-Bera Test for Normality	JarqueBera.test print.mhtest
Stage I of the Procedure: Locate Outliers (Baseline Function)	locate.outliers
Stage I of the Procedure: Locate Outliers (Loop Around Functions)	locate.outliers.iloop locate.outliers.oloop
Define Outliers in a Data Frame	outliers
Create the Pattern of Different Types of Outliers	outliers.effects
Regressor Variables for the Detection of Outliers	outliers.regressors
Test Statistics for the Significance of Outliers	outliers.tstatistics
Display Outlier Effects Detected by 'tsoutliers'	plot.tsoutliers
Print 'tsoutliers' object	print.tsoutliers
Stage II of the Procedure: Discard Outliers	remove.outliers
Automatic Procedure for Detection of Outliers	tso tso0

Package: tsoutliers 0.6-10

tsoutliers: Detection of Outliers in Time Series

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)