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# scikits.statsmodels.sandbox.tsa.ARIMA.fit

`ARIMA.``fit`(x, p, q, rhoy0=None, rhoe0=None)

  estimate lag coefficients of ARMA orocess by least squares

  Parameters: | x : array, 1d time series data p : int number of AR lags to estimate q : int number of MA lags to estimate rhoy0, rhoe0 : array_like (optional) starting values for estimation
  Returns: | rh, cov_x, infodict, mesg, ier : output of scipy.optimize.leastsq rh : estimate of lag parameters, concatenated [rhoy, rhoe] cov_x : unscaled (!) covariance matrix of coefficient estimates

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