| tscount-package | Analysis of Count Time Series |
| campy | Campylobacter Infections Time Series |
| ecoli | E. coli Infections Time Series |
| ehec | EHEC Infections Time Series |
| influenza | Influenza Infections Time Series |
| ingarch.acf | Analytical Mean, Variance and Autocorrelation of an INGARCH Process |
| ingarch.analytical | Analytical Mean, Variance and Autocorrelation of an INGARCH Process |
| ingarch.fit | Count Time Series Following Generalised Linear Models |
| ingarch.mean | Analytical Mean, Variance and Autocorrelation of an INGARCH Process |
| ingarch.var | Analytical Mean, Variance and Autocorrelation of an INGARCH Process |
| interv_covariate | Describing Intervention Effects for Time Series with Deterministic Covariates |
| interv_detect | Detecting an Intervention in Count Time Series Following Generalised Linear Models |
| interv_detect.tsglm | Detecting an Intervention in Count Time Series Following Generalised Linear Models |
| interv_multiple | Detecting Multiple Interventions in Count Time Series Following Generalised Linear Models |
| interv_multiple.tsglm | Detecting Multiple Interventions in Count Time Series Following Generalised Linear Models |
| interv_test | Testing for Interventions in Count Time Series Following Generalised Linear Models |
| interv_test.tsglm | Testing for Interventions in Count Time Series Following Generalised Linear Models |
| invertinfo | Compute a Covariance Matrix from a Fisher Information Matrix |
| logLik.tsglm | Count Time Series Following Generalised Linear Models |
| loglin.fit | Count Time Series Following Generalised Linear Models |
| marcal | Predictive Model Assessment with a Marginal Calibration Plot for Time Series Following Generalised Linear Models |
| marcal.tsglm | Predictive Model Assessment with a Marginal Calibration Plot for Time Series Following Generalised Linear Models |
| measles | Measles Infections Time Series |
| pit | Predictive Model Assessment with a Probability Integral Transform Histogram for Time Series Following Generalised Linear Models |
| pit.tsglm | Predictive Model Assessment with a Probability Integral Transform Histogram for Time Series Following Generalised Linear Models |
| plot.interv_detect | Plot Test Statistic of Intervention Detection Procedure for Count Time Series Following Generalised Linear Models |
| 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 |
| predict.tsglm | Predicts Method for Time Series of Counts Following Generalised Linear Models |
| print.summary.tsglm | Summarising Fits of Count Time Series following Generalised Linear Models |
| print.tsglm | Count Time Series Following Generalised Linear Models |
| residuals.tsglm | Residuals of a Generalised Linear Model for Time Series of Counts |
| scoring | Predictive Model Assessment with Proper Scoring Rules for Time Series Following Generalised Linear Models |
| scoring.tsglm | Predictive Model Assessment with Proper Scoring Rules for Time Series Following Generalised Linear Models |
| se | Standard Errors of a Fitted Generalised Linear Model for Time Series of Counts |
| se.tsglm | Standard Errors of a Fitted Generalised Linear Model for Time Series of Counts |
| summary.tsglm | Summarising Fits of Count Time Series following Generalised Linear Models |
| tscount | Analysis of Count Time Series |
| tsglm | Count Time Series Following Generalised Linear Models |
| tsglm.sim | Simulate a Time Series Following a Generalised Linear Model |
| vcov.tsglm | Count Time Series Following Generalised Linear Models |