By Mic
More than a year ago I wrote a short post on how to fit a copula model in R. The post showed how to make a very raw and basic fitting of a test dataset to a two dimensional normal copula (or a gaussian copula if you wish) using the copula package. The content of the post was not much, but that was a big part of what I knew about how to use copulas in R at that time and there was not much documentation available other than the official copula package documentation which is quite technical in my opinion (as it should be) and may not be that easy for a beginner copula user.
The main two reasons as for why I wanted to write a revised post are the following:
- I wanted to provide a better introduction to copulas in R than the one I wrote back then.
- By looking at my blog analytics I found out that a significant chunk of the people that visit my blog are looking for how to fit a copula model (or at least how to get started with it I guess) and I feel now I can offer better information to anyone interested in starting to use copulas.
This post is splitted in two parts:
- Part 1: This part introduces the beginner to the basic tools and functions you may need to work with copulas in R.
- Part 2: The second part addresses the selection of the copula, the fitting process, the evaluation of the fitting, some considerations and a practical example.
Since this post aims to be an introduction to copulas in R I assume you are somewhat familiar with at least elliptical and Archimedean copulas. In case you are not, but would like to be, I highly suggest this book on the topic. In my …read more
Source:: r-bloggers.com