DismalPy
  • Examples
    • Durbin and Koopman: Box-Jenkins Examples
    • SARIMAX: Introduction
      • ARIMA Example 1: Arima
      • ARIMA Example 2: Arima with additive seasonal effects
      • ARIMA Example 3: Airline Model
      • ARIMA Example 4: ARMAX (Friedman)
      • ARIMA Postestimation: Example 1 - Dynamic Forecasting
    • State space modeling: Local Linear Trends
      • References
    • Detrending, Stylized Facts and the Business Cycle
      • Unobserved Components
        • Trend
        • Seasonal
        • Cycle
        • Irregular
        • Regression effects
      • Data
      • Model
    • Dynamic factors and coincident indices
      • Macroeconomic data
      • Dynamic factors
      • Model specification
      • Parameter estimation
      • Estimates
        • Parameters
        • Estimated factors
      • Post-estimation
      • Coincident Index
      • Appendix 1: Extending the dynamic factor model
    • VARMAX models
      • Model specification
      • Example 1: VAR
      • Example 2: VMA
      • Caution: VARMA(p,q) specifications
  • DismalPy User Guide
    • State Space Models
      • Topics
        • State space models
        • Representation in Python
        • Maximum Likelihood Estimation
        • Posterior Simulation
        • Out-of-the-box models
        • References
      • Examples
        • Durbin and Koopman: Box-Jenkins Examples
        • SARIMAX: Introduction
        • State space modeling: Local Linear Trends
        • Detrending, Stylized Facts and the Business Cycle
        • Dynamic factors and coincident indices
        • VARMAX models
  • DismalPy Reference
    • State Space Models
      • Built-in models
        • SARIMAX
        • Unobserved Components
        • VARMAX
        • Dynamic Factors
      • Extension starting point
        • MLEModel
      • Base classes
        • Representation
        • Kalman filter
        • Kalman smoother
        • Simulation Smoother
        • Model
        • Tools
  • Installation
    • Dependencies
    • Procedure
    • Installing from source
  • Release Notes
    • DismalPy 0.2.0 Release Notes
      • Highlights
    • DismalPy 0.1.0 Release Notes
      • Highlights
      • Dropped Support
      • Future Changes
      • Compatibility notes
      • New Features
      • Improvements
      • Changes
      • Deprecations
  • About DismalPy
  • About this documentation
    • Conventions
  • Reporting bugs
  • DismalPy License
  • Glossary
    • Jargon
 
DismalPy
  • Docs »
  • DismalPy User Guide
  • View page source

DismalPy User GuideΒΆ

This guide is intended as an introduction to the use of DismalPy. For detailed reference documentation of the functions and classes contained in the package, see the DismalPy Reference.

  • State Space Models
    • Topics
      • State space models
      • Representation in Python
      • Maximum Likelihood Estimation
      • Posterior Simulation
      • Out-of-the-box models
      • References
    • Examples
      • Durbin and Koopman: Box-Jenkins Examples
      • SARIMAX: Introduction
      • State space modeling: Local Linear Trends
      • Detrending, Stylized Facts and the Business Cycle
      • Dynamic factors and coincident indices
      • VARMAX models
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© Copyright 2014, Chad Fulton.

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