Time Series Models for Ecologists and Climatologists

[Melanie Colón]

"Time Series Models for Ecologists and Climatologists"

 

http://prstatistics.com/course/time-series-models-for-ecologists-and-

climatologist/

 

There are still some places left on this new course suited to many types

of Ecology, Evolutionary and Climatology data

 

Delivered by Dr. Andrew Parnell and Dr. Doug McNeall

 

This course will run from 10th – 13th May 2016 at SCENE Field Station,

Loch Lomond national park, Scotland

 

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.

 

Course content is as follows

 

Day 1 Basic concepts

Class 1: Introduction; some example time series datasets; prediction vs

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

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 Modelling

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 Times 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

 

Please email any inquiries to oliverhooker@prstatistics.com or visit our

website www.prstatistics.com

 

Please feel free to distribute this material anywhere you feel is

suitable

 

Upcoming courses - email for details oliverhooker@prstatistics.com

SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (April)

ADVANCING IN STATISTICAL MODELLING USING R (May)

INTRODUCTION TO PYTHON FOR BIOLOGISTS (May)

ADVANCES IN SPATIAL ANALYSIS OF MULTIVARIATE ECOLOGICAL DATA (July)

ADVANCES IN DNA TAXONOMY USING R (August)

GENETIC DATA ANALYSIS USING R (August)

INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August)

MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (October)

LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October)

APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October)

 

Dates still to be confirmed - email for details

oliverhooker@prstatistics.com

STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R

INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS

PHYLOGENETIC DATA ANALYSIS USING R

BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS

 

Oliver Hooker

PR Statistics