Linear time series model estimation

A quick and easy way to estimate and analyze linear time series models

The function estimates:

• Models with exogenous variables only
• Autoregression models (AR)
• Vector autoregression models (VAR)
• Error correction models (ECM)
• Vector error correction models (VECM)

The avalable estimation methods are the Ordinary Least Squares and the Maximum Likelihood Estimation

The output of the function includes:

• 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)