Media Summary: This video provides an introduction into the topic based on Stochastic dynamic systems observed with noise. Latent process models; the Markov property; measurement models. Prediction, filtering, smoothing and likelihood calculation for POMP models.
Time Series Analysis Chapter 10 - Detailed Analysis & Overview
This video provides an introduction into the topic based on Stochastic dynamic systems observed with noise. Latent process models; the Markov property; measurement models. Prediction, filtering, smoothing and likelihood calculation for POMP models. Linear Gaussian POMP models. ARMA models as LG-POMPs; the basic structural model. In this video, we will be learning how to work with DateTime and Linear Gaussian POMP models, continued. Spline smoothing as an LG-POMP; the Kalman filter.
