Sequential Monte Carlo
6
Putting it together
SMC and epidemic renewal models
Welcome
Introduction
1
The renewal model
2
Background of
\(R_t\)
estimation
3
Hidden-state models
Sequential Monte Carlo
4
The bootstrap filter
5
Parameter estimation
6
Putting it together
7
Other resources
Models
8
A simple model
9
Modelling observation noise
10
Temporally aggregated data
11
Imported cases
12
Multiple sources of data
Prediction
Inference
Evaluation
13
Precision and calibration
14
Scoring rules
15
Additional notes on model evaluation
Other methods
16
EpiEstim
17
EpiFilter
18
EpiNow2
References
Appendices
A
Notation
B
Simulated data
C
Smoothing methods
D
Structure of pre-built functions
Sequential Monte Carlo
6
Putting it together
6
Putting it together
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5
Parameter estimation
7
Other resources