Table of contents | Normal case | Normal outcome with known variance | Univariated Normal outcome with unknown variance | Correlation | Poisson case | Gamma case | Multinomial case | Some comments on the usage of an offset | Handling multiple outcomes | Special case: Conditional modelling | References

Table of contents | A structure for polynomial trend models | A structure for dynamic regression models | A structure for harmonic trend models | A structure for autoregresive models | Some comments about autoregressive models in the Normal family | A structure for overdispersed models | Handling multiple structural blocks | Handling multiple linear predictors | Handling unknown components in the planning matrix $F_t$ | Special priors | References

Table of contents | Filtering and smoothing | Extracting components | Forecasting | Updating a fitted model | Intervention and monitoring | Tools for sensitivity analysis | Sampling and hyper parameter estimation | References

Table of contents | Notation | Single outcome models | References

Data requirements and conventions | Package functions used in this vignette | Fitting the models with fit.surr() | What fit.surr() stores | Summaries and inference | Printing a summary | Plotting LPTE, CPTE, and treatment effects | Testing time-homogeneity | Practical tips and common pitfalls | Session info