R-universe - ee-lib (EE-lib)

hhh4 (spatio-temporal): Endemic-epidemic modeling of areal count time series3 days ago

Model class | Data structure | Modeling and inference | Simulation

surveillance 1.26.0Sebastian Meyer hhh4_spacetime.Rnw

Monitoring count time series in R: Aberration detection in public health surveillance3 days ago

Introduction | Getting to know the basics of the package | Using surveillance in selected contexts | Implementing surveillance in routine monitoring | Discussion

surveillance 1.26.0Sebastian Meyer monitoringCounts.Rnw

twinSIR: Individual-level epidemic modeling for a fixed population with known distances3 days ago

Model class | Data structure | Modeling and inference | Simulation

surveillance 1.26.0Sebastian Meyer twinSIR.Rnw

twinstim: An endemic-epidemic modeling framework for spatio-temporal point patterns3 days ago

Model class | Data structure | Modeling and inference | Simulation

surveillance 1.26.0Sebastian Meyer twinstim.Rnw

Getting started with outbreak detection5 days ago

Introduction | Surveillance Data | Surveillance Algorithms | Discussion and Future Work | Acknowledgements

surveillance 1.26.0Sebastian Meyer surveillance.Rnw

hhh4: An endemic-epidemic modelling framework for infectious disease counts5 days ago

Introduction | Surveillance data | Model formulation | Function call and control settings | Conclusion

surveillance 1.26.0Sebastian Meyer hhh4.Rnw

algo.glrnb: Count data regression charts using the generalized likelihood ratio statistic2 months ago

Introduction | Preliminaries | LR and GLR-charts | Control-settings | Discussion

surveillance 1.26.0Sebastian Meyer glrnb.Rnw

Forecasting age-stratified norovirus gastroenteritis counts using surveillance::hhh43 years ago

Data | Berlin norovirus counts | Age-structured contact matrix | Modelling | One-week-ahead forecasts

HIDDA.forecasting 1.1.3Sebastian MeyerBNV.Rmd

Forecasting Swiss ILI counts using surveillance::hhh43 years ago

Modelling | One-week-ahead forecasts | Long-term forecasts | Example with the first test period | For all test periods

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI_hhh4.Rmd

Forecasting Swiss ILI counts using forecast::auto.arima3 years ago

Modelling | One-week-ahead forecasts | Long-term forecasts

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI_arima.Rmd

Forecasting Swiss ILI counts using glarma::glarma3 years ago

Modelling | One-week-ahead forecasts | Long-term forecasts

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI_glarma.Rmd

Forecasting Swiss ILI counts using prophet::prophet3 years ago

Modelling | One-week-ahead forecasts | Long-term forecasts

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI_prophet.Rmd

hhh4addon: extending the functionality of surveillance:hhh46 years ago

Purpose of the R package hhh4addon | The endemic-epidemic model class and its extension to higher-order lags | Computing predictive and marginal moments | References

hhh4addon 0.0.0.0.9014Johannes Bracher ([email protected]), University of Zurichhhh4addon.Rmd

Forecasting Swiss ILI counts using simple log-normals by calendar week7 years ago

One-week-ahead forecasts | Long-term forecasts

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI_naive.Rmd

Swiss ILI surveillance counts9 years ago

HIDDA.forecasting 1.1.3Sebastian MeyerCHILI.Rmd