Fishery Population Analysis (FPA)

The first lecture will be given on May 13, 2020

Overview of this class

Time: Wed 10:30 - 12am

Location: Online until informed

Objectives:

  • Students will learn statistical methods used in fisheries stock assessment and management.
  • The course will also cover the basics of programming in R, TMB and stan.

Grading:

Grading is based on the level of the understanding, reports and presentation in the class.

Schedule (subject to change):

Lecture Date Time Subject Report Due
1 13-May-20 AM1030-AM1200 Course introduction
2 20-May-20 AM1030-AM1115 R basics (R, Rstudio, Rmarkdown)
3 20-May-20 AM1115-AM1200 Expression of stochastic events and data using probabilistic and statistical models Rep1
4 27-May-20 AM1030-AM1115 Maximum likelihood theory (1) construction of likelihood for point estimation
5 27-May-20 AM1115-AM1200 Maximum likelihood theory (2) evaluation of uncertainty in estimation
6 3-Jun-20 AM1030-AM1200 Maximum likelihood theory (3) likelihood ratio test and model selection Rep1 Rep1 by Jun 9
7 10-Jun-20 AM1030-AM1200 Maximum likelihood theory (4) Laplace approximation and TMB basics
8 17-Jun-20 AM1000-AM1100 Continued 30-Jun-20
9 1-Aug-20 AM0900-PM0500 Bayesian theory (1) estimation and inference Rep2
10 1-Aug-20 AM0900-PM0500 Bayesian theory (2) MCMC and Stan basics
11 1-Aug-20 AM0900-PM0500 Advanced models (1) time series and state-space models
11 1-Aug-20 AM0900-PM0500 Advanced models (2) hierarchical models
12 15-Jul-20 AM1000-AM1100 Regression models (1) linear, nonlinear, GLM and GAM
13 15-Jul-20 AM1100-AM1200 Regression models (2) sparse and other superivised regression models
14 TBD Project using R/TMB/Stan
15 TBD Project presentation

Information:

The course is basically conducted in English (this is because of the instruction from the university, not for my training…), but additional illustration in Japanese will be available upon request. We will use the software “R” etc.. Beginners of “R” are welcomed.

The course website: https://toshihidekitakado.github.io/FPA2020/

Placeholder:

  • start = c(“2016-01-10”, “2016-01-11”, “2016-01-20”, “2016-02-14 15:00:00”),
  • end = c(NA, NA, “2016-02-04”, NA)