Package: tscount 1.4.4

Tobias Liboschik

tscount: Analysis of Count Time Series

Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided, see Liboschik et al. (2017) <doi:10.18637/jss.v082.i05>. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

Authors:Tobias Liboschik [aut, cre], Roland Fried [aut], Konstantinos Fokianos [aut], Philipp Probst [aut], Jonathan Rathjens [ctb], Nicolò Rubattu [ctb]

tscount_1.4.4.tar.gz
tscount_1.4.4.zip(r-4.7)tscount_1.4.4.zip(r-4.6)tscount_1.4.4.zip(r-4.5)
tscount_1.4.4.tgz(r-4.6-any)tscount_1.4.4.tgz(r-4.5-any)
tscount_1.4.4.tar.gz(r-4.7-any)tscount_1.4.4.tar.gz(r-4.6-any)
tscount_1.4.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tscount/json (API)
NEWS

# Install 'tscount' in R:
install.packages('tscount', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://r-forge.r-project.org/projects/tscount

Datasets:
  • campy - Campylobacter Infections Time Series
  • ecoli - E. coli Infections Time Series
  • ehec - EHEC Infections Time Series
  • influenza - Influenza Infections Time Series
  • measles - Measles Infections Time Series

On CRAN:

Conda:

5.70 score 1 packages 120 scripts 2.0k downloads 7 mentions 23 exports 1 dependencies

Last updated from:d4774dc5aa. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK141
source / vignettesOK255
linux-release-x86_64OK131
macos-release-arm64OK130
macos-oldrel-arm64OK123
windows-develOK116
windows-releaseOK126
windows-oldrelOK94
wasm-releaseOK100

Exports:ardistrcheckdistrddistringarch.acfingarch.meaningarch.varinterv_covariateinterv_detectinterv_multipleinterv_testinvertinfomarcalpdistrpitqdistrQICrdistrscoringsddistrsetsglmtsglm.meanfittsglm.sim

Dependencies:ltsa

tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models

Rendered fromtsglm.Rnwusingutils::Sweaveon May 08 2026.

Last update: 2020-09-07
Started: 2015-02-06

Readme and manuals

Help Manual

Help pageTopics
Analysis of Count Time Seriestscount-package tscount
Campylobacter Infections Time Seriescampy
Count Data Distributionsardistr checkdistr countdistr ddistr pdistr qdistr rdistr sddistr
E. coli Infections Time Seriesecoli
EHEC Infections Time Seriesehec
Influenza Infections Time Seriesinfluenza
Analytical Mean, Variance and Autocorrelation of an INGARCH Processingarch.acf ingarch.analytical ingarch.mean ingarch.var
Describing Intervention Effects for Time Series with Deterministic Covariatesinterv_covariate
Detecting an Intervention in Count Time Series Following Generalised Linear Modelsinterv_detect interv_detect.tsglm
Detecting Multiple Interventions in Count Time Series Following Generalised Linear Modelsinterv_multiple interv_multiple.tsglm
Testing for Interventions in Count Time Series Following Generalised Linear Modelsinterv_test interv_test.tsglm
Compute a Covariance Matrix from a Fisher Information Matrixinvertinfo
Predictive Model Assessment with a Marginal Calibration Plotmarcal marcal.default marcal.tsglm
Measles Infections Time Seriesmeasles
Predictive Model Assessment with a Probability Integral Transform Histogrampit pit.default pit.tsglm
Plot Test Statistic of Intervention Detection Procedure for Count Time Series Following Generalised Linear Modelsplot.interv_detect
Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Modelsplot.interv_multiple
Diagnostic Plots for a Fitted GLM-type Model for Time Series of Countsplot.tsglm
Predicts Method for Time Series of Counts Following Generalised Linear Modelspredict.tsglm
Quasi Information Criterion of a Generalised Linear Model for Time Series of CountsQIC QIC.tsglm
Residuals of a Generalised Linear Model for Time Series of Countsresiduals.tsglm
Predictive Model Assessment with Proper Scoring Rulesscoring scoring.default scoring.tsglm
Standard Errors of a Fitted Generalised Linear Model for Time Series of Countsse se.tsglm
Summarising Fits of Count Time Series following Generalised Linear Modelsprint.summary.tsglm summary.tsglm
Count Time Series Following Generalised Linear ModelslogLik.tsglm print.tsglm tsglm tsglm.meanfit vcov.tsglm
Simulate a Time Series Following a Generalised Linear Modeltsglm.sim