# tscount v1.4.3

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## 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. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

## Functions in tscount

Name | Description | |

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 | |

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## Vignettes of tscount

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## Details

Type | Package |

Date | 2020-09-07 |

License | GPL-2 | GPL-3 |

URL | http://tscount.r-forge.r-project.org |

ByteCompile | true |

NeedsCompilation | no |

LazyData | true |

Encoding | UTF-8 |

Packaged | 2020-09-07 20:29:11 UTC; Tobias |

Repository | CRAN |

Date/Publication | 2020-09-08 07:00:03 UTC |

suggests | gamlss.data , Matrix , surveillance , xtable |

imports | ltsa , parallel |

Contributors | Jonathan Rathjens, Roland Fried, Konstantinos Fokianos, Philipp Probst |

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