This course provides experience with stochastic modeling and time series analysis tools available in the Wolfram Language. Topics include random processes, Markov models, time series analysis and model fitting. Course topics are presented in sessions of lectures, exercises and instructor-led coding sessions with real-world examples. Online classes have small class sizes and ample opportunity for Q&A. The course is for those who have a basic working knowledge of the Wolfram Language and statistical data analysis.
Featured Products & Technologies: Wolfram Language, Mathematica
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- Random Processes
Simulation, properties, classification, estimation and applications of parametric and derived stochastic processes.
- Markov Processes
Simulation, properties, estimation and applications of continuous, discrete and hidden Markov models.
- Time Series Processing
Time series construction, dealing with missing data and irregularity, operations on time series.
- Time Series Modeling
Various time series models, fitting time series models, model selection, forecasting, prediction limits.