likelihood.qmd

---
title: "Likelihood-based inference for POMP models"
author: Qianying (Ruby) Lin, Spencer J. Fox, Zian (Larry) Zhuang
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        - _slides/_includes/license.html
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| &nbsp;                            | &nbsp;                                                                                     |
|-----------------------------------|--------------------------------------------------------------------------------------------|
| Lecture slides | [PDF](slides/pfilter/main.pdf) |
| Reference Recording (2020,2021) | [Video (112 min)](https://www.youtube.com/playlist?list=PLluGwj6FGt2RRi-TRckg7Lud87ZKIJTZ8) |
| Quiz | [PDF](slides/pfilter/quiz.pdf) |
| **Data** for the lesson | [data](slides/pfilter/Measles_Consett_1948.csv)|
| **R** script for the Measles SIR model | [**R**](slides/pfilter/model_measSIR.R)|
| **R** script for the lesson | [**R**](slides/pfilter/main.R) |
| Supplement: Deterministic latent process models and their role in benchmarking POMP models | [HTML](slides/pfilter/deterministic.html) |
| Supplement: Monte Carlo Methods | [PDF](slides/pfilter/monteCarlo.pdf) |
| Supplement: Likelihood by direct simulation: Consett measles example | [HTML](slides/pfilter/directSimulation.html) |
| Supplement: Standard errors via the observed Fisher information | [HTML](slides/pfilter/fisherSE.html) |
| Supplement: Bootstrap methods | [HTML](slides/pfilter/bootstrap.html) |
| Supplement: Direct maximization of the particle filter likelihood | [HTML](slides/pfilter/pf-in-Nelder-Mead.html) |
| Worked solution to Exercise 3.1 | [HTML](slides/pfilter/Q_slice.html) |
| Worked solution to Exercise 3.2 | [HTML](slides/pfilter/expense.html) |
| Worked solution to Exercise 3.3 | [HTML](slides/pfilter/loglikest.html) |


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