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tscount (version 1.4.3)

Analysis of Count Time Series

Description

Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

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Version

Install

install.packages('tscount')

Monthly Downloads

457

Version

1.4.3

License

GPL-2 | GPL-3

Maintainer

Tobias Liboschik

Last Published

September 8th, 2020

Functions in tscount (1.4.3)

ingarch.analytical

Analytical Mean, Variance and Autocorrelation of an INGARCH Process
countdistr

Count Data Distributions
campy

Campylobacter Infections Time Series
interv_covariate

Describing Intervention Effects for Time Series with Deterministic Covariates
ehec

EHEC Infections Time Series
interv_detect.tsglm

Detecting an Intervention in Count Time Series Following Generalised Linear Models
QIC

Quasi Information Criterion of a Generalised Linear Model for Time Series of Counts
influenza

Influenza Infections Time Series
interv_multiple.tsglm

Detecting Multiple Interventions in Count Time Series Following Generalised Linear Models
ecoli

E. coli Infections Time Series
marcal

Predictive Model Assessment with a Marginal Calibration Plot
measles

Measles Infections Time Series
predict.tsglm

Predicts Method for Time Series of Counts Following Generalised Linear Models
residuals.tsglm

Residuals of a Generalised Linear Model for Time Series of Counts
plot.interv_multiple

Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Models
plot.tsglm

Diagnostic Plots for a Fitted GLM-type Model for Time Series of Counts
tsglm.sim

Simulate a Time Series Following a Generalised Linear Model
tsglm

Count Time Series Following Generalised Linear Models
tscount-package

Analysis of Count Time Series
summary.tsglm

Summarising Fits of Count Time Series following Generalised Linear Models
invertinfo

Compute a Covariance Matrix from a Fisher Information Matrix
pit

Predictive Model Assessment with a Probability Integral Transform Histogram
se.tsglm

Standard Errors of a Fitted Generalised Linear Model for Time Series of Counts
interv_test.tsglm

Testing for Interventions in Count Time Series Following Generalised Linear Models
scoring

Predictive Model Assessment with Proper Scoring Rules
plot.interv_detect

Plot Test Statistic of Intervention Detection Procedure for Count Time Series Following Generalised Linear Models