index.Rmd

---
title: "Forecasting Catch Time Series"
---

```{r echo=FALSE, warnings=FALSE, include=FALSE}
# devtools::install_github("rstudio/fontawesome")
library(fontawesome)
knitr::opts_chunk$set(cache = TRUE)
```

This course will teach a number of standard approaches for forecasting from catch time series using the data and methods discussed in Stergiou and Christou (1996) *Modelling and forecasting annual fisheries catches: comparison of regression, univariate and multivariate time series methods.* Fisheries Research 25: 105-136.

# Course Syllabus

<img style="float: right" src="https://rverse-tutorials.github.io/Fish-Forecast-Training-Course/images/fish-forecast.jpg" width=20%>

- Time-varying regression
- Box-Jenkins (ARMA) Models
- Exponential smoothing
- Modelling time series with seasonality
- Forecast diagnostics and accuracy metrics

# e-Text and other courses

An online book of the material is [Fisheries Catch Forecasting](https://fish-forecast.github.io/Fish-Forecast-Bookdown/).  Links to our other workshops and courses on similar material can be found at the [Applied Time Series Analysis](https://nwfsc-timeseries.github.io/) website.

# References

You can download the reference papers [here](https://github.com/Fish-Forecast/Fish-Forecast-Webpage/tree/master/references).  We are replicating (part of) the work in Stergio and Christou (1996) in the references.

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