[Open Workshops] - Statistical models with R | - CCMAR -
 

[Open Workshops] - Statistical models with R

 

Background
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical tools, including the fit of statistical models such as linear models and generalized linear models. Furthermore, R is an environment within which statistical techniques can be (easily) extended via packages and those include, for example, generalized additive models and mixed effects models (and much more).

Objective
This workshop will be focused on statistical model fitting using R. The main objective is to demonstrate how to fit different statistical models in R, and how to perform variable selection, model validation and goodness-of-fit analysis.

Methodology
We will start with a simple linear model (LM) example, and then move to generalized linear models (GLM). Examples of models for discrete/count data (e.g. Poisson and Negative Binomial) and for continuous data (e.g. Gamma and log-Normal) will be provided. A (very) brief presentation on fitting other model types such as generalized additive models (GAM) and mixed effects models (GLMM) will be made.
For the fitted models we will discuss and provide examples on variable selection techniques (e.g. stepwise methods, likelihood ratio tests), model validation (e.g. residual analysis, outliers and leverage values), and assessing goodness-of-fit (e.g. R2, AIC, cross-validation).

Recommended background
Background knowledge (basic level) on statistical modeling and on the general use of R is recommended.

About the Instructor
Rui Coelho has a Postdoctoral fellowship with time divided between the Fisheries, Biodiversity and Conservation group of Centro de Ciências do Mar and the Instituto Português do Mar e da Atmosfera. His current research interests are related with biology, ecology, and fisheries impacts of longline fisheries on bycatch species, particularly pelagic elasmobranchs, with the aim of producing scientific-based advice for fisheries management.

Date
Wednesday, April 24; one day session

Time
14:00-18:00 h

Room
Computer Room 2.56, building C7 - Gambelas Campus

 

 

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16.04.2013