Estimation of a general transfer function model with two input variables. The model can handle one output and up-to 2 input variables. The time series noise can assume multiplicative seasonal ARMA models.
tfm2(y,x,x2=NULL,ct=NULL,wt=NULL,orderN=c(1,0,0),orderS=c(0,0,0),
sea=12,order1=c(0,1,0),order2=c(0,-1,0))Data vector of dependent variable
Data vector of the first input (or independent) variable
Data vector of the second input variable if any
Data vector of a given deterministic variable such as time trend, if any
Data vector of co-integrated series between input and output variables if any
Order (p,d,q) of the regular ARMA part of the disturbance component
Order (P,D,Q) of the seasonal ARMA part of the disturbance component
Seasonality, default is 12 for monthly data
Order (r,s,b) of the transfer function model of the first input variable, where r and s are the degrees of denominator and numerator polynomials and b is the delay
Order (r2,s2,b2) of the transfer function model of the second input variable, where 2r and s2 are the degrees of denominator and numerator polynomials and b2 is the delay
Coefficient estimates
Residual variance sigma-square
Residual series
Variance of the estimates
The disturbance series
Regular AR coefficients
Regular MA coefficients
Seasonal AR coefficients
Seasonal MA coefficients
Numerator coefficients of the first transfer function
Denominator coefficients of the first transfer function
Numerator coefficients of the 2nd transfer function
Denominator coefficients of the 2nd transfer function
Perform estimation of a general transfer function model with two input variables
Box, G. E. P., Jenkins, G. M., and Reinsel, G. C. (1994). Time Series Analysis: Forecasting and Control, 3rd edition, Prentice Hall, Englewood Cliffs, NJ.
tfm, tfm1