Thursday, January 31, 2013

Week 4: Applied Time-Series Analysis for Fisheries and Environmental Data

Class material: webpage

Week 4: Introduction to univariate autoregressive state-space models
Topics:
  • State-space models
  • Process versus observation error
  • Model Selection


Lecture 4
Click the big arrow to start the show. You can also find just the ppt of lecture 3 on the class webpage.

Tuesday, January 22, 2013

Week 3: Applied Time-Series Analysis for Fisheries and Environmental Data

Class material: webpage

Week 3: Estimation, model selection, and forecasting for time series models
Topics:
  • Summarizing ARIMA models
  • Estimation
  • Model Selection
  • Prediction & forecasting
  • Evaluating forecasts
  • Functions: arima(), lm(), Arima()
Lecture 3
This is our second attempt at recording a lecture. Still much to be learned but we are getting better.  Click the big arrow to start the show. You can also find just the ppt of lecture 3 on the class webpage.

Tuesday, January 15, 2013

Week 2: Applied Time-Series Analysis for Fisheries and Environmental Data

Class material: webpage

Week 2: Correlation, stationarity & stationary time-series models
The lecture introduces the ACF, PACF, and basic properties of AR, MA and ARMA models. The computer code section shows R code to analyze simulated time-series data so that participants get a feel for ACF and PACF and get a feel for AR and MA processes. The participants then move to analyzing some real time-series data using the 30+ year time-series of Lake Washington plankton.

Lecture 2
This is our first attempt at recording a lecture. Ahem, there is clearly much to be learned to improve the process...Click the big arrow to start the show. You can also find just the ppt of lecture 2 on the class webpage.