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TIMESERIES MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS - STATS COURSE


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TIME SERIS MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS

This course is being delivered by Dr Andrew Parnell and Dr Mike Salter-
Townshend

It will run from 9th - 12th of May 2016 at SCENE (the Scottish Centre for Ec
Ecology and the Natural Environment), Loch Lomond National Park, Glasgow.

Course overview: This course will cover model-based time series analysis
with a particular focus on applications in ecology and climatology. All
methods will be illustrated using the free, open-source software package R.
Time Series data are ubiquitous in the physical sciences, and models for
their behaviour enable scientists to understand temporal dynamics and
predict future values. Participants will be taught a wide range of suitable
time series models for both discrete and continuous time systems. The
course takes a foundational Bayesian approach, which will enable
participants to have a deeper understanding of the models being fitted, and
to estimate all unknown quantities with uncertainty. Participants are
encouraged to bring their own data sets for discussion with the course
tutors.

Curriculum:

Day 1: Basic concepts
Class 1: Introduction; some example time series datasets; prediction vs explanat
explanation
Class 2: An introduction to Bayesian Statistics.
Class 3: The AR(1) model
Practical: revision on using R to load data, create plots and fit stati
statistical models
Round table discussion: understanding the output from a Bayesian model

Day 2: ARIMA modelling
Class 1: ARMA models for real data
Class 2: ARIMA and sARIMA modelling
Practical: An introduction to the Bayesian modelling language JAGS
Round table discussion: understanding and running a JAGS model

Day 3: Continuous time series
Class 1: Brownian Motion and its application to real data sets
Class 2: An introduction to Stochastic Volatility Modelling
Practical: Fitting continuous time models in JAGS
Round table discussion: Issues of continuous vs discrete time

Day 4: Advanced time series models
Class 1: Multivariate models
Class 2: Fractional differencing and models using differential equations
Practical: Running advanced models in JAGS
Round table discussion: Bring your own data set

The cost is £450 including lunches and course materials. An all-inclusive opti
option is also available at £625; this includes breakfast, lunch, dinner, refr
refreshments, accommodation and course materials. Participants will need a lapt
laptop with a recent version of R

This workshop is aimed at research postgraduates, practicing academics in ec
ecology, climatology, evolution, meteorology, conservation and en
environmental management, and environmental professionals in government and in
industry.

The workshop is delivered over 8 half-day sessions (see the detailed
curriculum below). The session will consist of Introductory lectures on the
concepts and refreshers on R usage. Intermediate-level lectures
interspersed with hands-on mini practicals and longer projects. Finally, roun
round-table discussions about the analysis requirements of attendees (opt
(optional - bring your own data

Assumed background: A basic understanding of statistical concepts. Such as re
regression modelling and generalised linear models. Some understanding of Ba
Bayesian Statistics is recommended but will be covered during the in
introductory sessions. Familiarity with R. Ability to import/export data, ma
manipulate data frames, fit basic statistical models & generate simple ex
exploratory and diagnostic plots.

Please send inquiries to oliverhooker@prstatistics.co.uk or visit the website w
website www.prstatistics.co.uk

Please fee free to distribute this information anywhere you think suitable..

http://prstatistics.co.uk/time%20series%20models%20for%20ecologists%20and%20clima
climatologists/index.html

Other upcoming courses - GENETIC DATA ANALYSIS USING SIAR; ; APPLIED BAY
BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS; SPATIAL ANALYSIS OF ECO
ECOLOGICAL DATA USING R; ADVANCING IN STATISTICAL MODELLING USING R; PYTHON FOR
FOR BIOLOGISTS; INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS; ADVANCES IN
IN DNA TAXONOMY; BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS; MUL
MULTIVARIATE ANALYSIS OF SPATIAL DATA; MODEL BASE MULTIVARIATE ANALYSIS OF ABU
ABUNDANCE DATA;

Oliver Hooker
PR~Statistics

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