Linear time series model estimation
- Models with exogenous variables only
- Autoregression models (AR)
- Vector autoregression models (VAR)
- Error correction models (ECM)
- Vector error correction models (VECM)
- Coefficients: estimation, standard errors, significance, lower and upper levels
- Coefficients variance-covariance matrix
- Residuals
- Residuals variance-covariance matrix
- ANOVA
- Information criteria (AIC, AICc, BIC)
- log-likelihood
- R squared
- Residuals tests: 1) One-sample Kolmogorov-Smirnov test, 2) Augmented Dickey-Fuller test, 3) Kwiatkowski, Phillips, Schmidt, and Shin test, 4) Durbin-Watson test, 5) Ljung-Box Q-test, 6) Engle’s ARCH test, and 7) Cross-sectional correlation (VAR and VECM only).
- Variance inflation factor (VIF)
Cite As
Apostolos Panagiotopoulos (2024). Linear time series model estimation (https://www.mathworks.com/matlabcentral/fileexchange/98254-linear-time-series-model-estimation), MATLAB Central File Exchange. Retrieved .
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Version | Published | Release Notes | |
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2.1.1 | Small correction |
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2.1.0 | Addition of the variance inflation factor (VIF) in the outputs and small correction in MLE |
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2.0.6 | Updated output |
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2.0.5 | Correction in the code |
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2.0.4 | Update for better functionality |
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2.0.3 | Small correction in the code |
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2.0.2 | Addition of simulated annealing |
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2.0.1 | Constant of VECM |
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2.0.0 | Addition of the Johansen procedure |
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1.3.0 | Introduction of Maximum Likelihood Estimation option |
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1.2.6 | Correction in the information criteria |
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1.2.5 | Correction in the information criteria formula |
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1.2.4 | Correction in the description |
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1.2.3 | Correction in the notes |
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1.2.2 | Update in ECM |
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1.2.1 | Bug correction |
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1.2.0 | Fixing a bug in VECM |
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1.1.4 | Correction in ECM |
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1.1.3 | Fixing a bug |
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1.1.2 | Addition of residuals covariance and the Durbin-Watson test |
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1.1.1 | small correction in the output |
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1.1.0 | Residuals tests in the output |
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1.0.5 | Small correction in the code |
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1.0.4 | Correction in the comments |
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1.0.3 | Change in the name |
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1.0.2 | Option to use the lag of independent variables |
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1.0.1 | Option to use the lag of independent variables |
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1.0.0 |