"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 [email protected] or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details [email protected] 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 [email protected] 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
