Autoregressive model
Main article: Autoregressive model

The notation AR(p) refers to the autoregressive model of order p. The AR(p) model is written

    X_t = c + \sum_{i=1}^p \varphi_i X_{t-i}+ \varepsilon_t .\,

where \varphi_1, \ldots, \varphi_p are the parameters of the model, c is a constant and \varepsilon_t is white noise. The constant term is omitted by many authors for simplicity.

An autoregressive model is essentially an all-pole infinite impulse response filter with some additional interpretation placed on it.

Some constraints are necessary on the values of the parameters of this model in order that the model remains stationary. For example, processes in the AR(1) model with |φ1| ≥ 1 are not stationary.

X(t)=c+phi_1 X(t-1)+epsilon_t

？？不懂你的意思，ar(1)是残差之后回归的的系数，即e=ar(1)e(-1)

Variable        Coefficient        Std. Error        t-Statistic        Prob.  
                                                               
GDP        0.325022        0.015490        20.98297        0.0000
C        -368.5110        51.70328        -7.127420        0.0000
AR(1)        0.565028        0.149691        3.774638        0.0031


请问这个用方程式表示怎么表示

继续求助

同问啊！！！