by Malcolm Haddon (Author)
Using R for Modelling and Quantitative Methods in Fisheries
has evolved and been adapted from an earlier book by the same author
and provides a detailed introduction to analytical methods commonly used
by fishery scientists, ecologists, and advanced students using the
open-source software R as a programming tool. Some knowledge of R is
assumed, as this is a book about using R, but an introduction to the
development and working of functions, and how one can explore the
contents of R functions and packages, is provided.
The example
analyses proceed step-by-step using code listed in the book and from the
book’s companion R package, MQMF, available from GitHub and the
standard archive, CRAN. The examples are designed to be simple to modify
so the reader can quickly adapt the methods described to use with their
own data. A primary aim of the book is to be a useful resource to
natural resource practitioners and students.
Featured Chapters:
- Model Parameter Estimation
provides a detailed explanation of the requirements and steps involved
in fitting models to data, using R and, mainly, maximum likelihood
methods.
- On Uncertainty uses R
to implement bootstrapping, likelihood profiles, asymptotic errors, and
Bayesian posteriors to characterize any uncertainty in an analysis. The
use of the Monte Carlo Markov Chain methodology is examined in some
detail.
Surplus Production Models applies
all the methods examined in the earlier parts of the book to conducting
a stock assessment. This included fitting alternative models to the
available data, characterizing the uncertainty in different ways, and
projecting the optimum models forward in time as the basis for providing
useful management advice.
