sVARMA function

Seasonal VARMA Model Estimation

Performs conditional maximum likelihood estimation of a seasonal VARMA model

sVARMA(da, order, sorder, s, include.mean = T, fixed = NULL, details = F, switch = F)

Arguments

• da: A T-by-k data matrix of a k-dimensional seasonal time series
• order: Regular order (p,d,q) of the model
• sorder: Seasonal order (P,D,Q) of the model
• s: Seasonality. s=4 for quarterly data and s=12 for monthly series
• include.mean: A logical switch to include the mean vector. Default is to include the mean
• fixed: A logical matrix to set zero parameter constraints
• details: A logical switch for output
• switch: A logical switch to exchange the ordering of the regular and seasonal VMA factors. Default is theta(B)*Theta(B).

Details

Estimation of a seasonal VARMA model

Returns

• data: The data matrix of the observed k-dimensional time series

• order: The regular order (p,d,q)

• sorder: The seasonal order (P,D,Q)

• period: Seasonality

• cnst: A logical switch for the constant term

• ceof: Parameter estimates for use in model simplification

• secoef: Standard errors of the parameter estimates

• residuals: Residual series

• Sigma: Residual covariance matrix

• aic,bic: Information criteria of the fitted model

• regPhi: Regular AR coefficients, if any

• seaPhi: Seasonal AR coefficients

• regTheta: Regular MA coefficients

• seaTheta: Seasonal MA coefficients

• Ph0: The constant vector, if any

• switch: The logical switch to change the ordering of matrix product

References

Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Author(s)

Ruey S. Tsay