Module arima::acf

Functions

• acf
  Calculate the auto-correlation function of a time series of length n.
• ar
  Calculate the auto-regressive coefficients of a time series of length n. If you already calculated the auto-correlation coefficients (ACF), consider using ar_rho instead.
• ar_dl_rho_cov
  Calculate the auto-regressive coefficients of a time series of length n, given the auto-correlation coefficients rho and auto covariance at lag 0, cov0. This method uses the Durbin-Levinson algorithm to iteratively estimate the coefficients, and it also returns the standard error for the 1-step look-ahead prediction (i.e. the estimated variance).
• pacf
  Calculate the partial auto-correlation coefficients of a time series of length n. If you already calculated the auto-correlation coefficients (ACF), consider using pacf_rho instead.
• pacf_rho_cov0
  Calculate the partial auto-correlation coefficients of a time series of length n, given the auto-correlation coefficients rho.
• var
  Estimate the variance of a time series of length n via Durbin-Levinson. If you already calculated the AR parameters, auto-correlation coefficients (ACF), and the auto-covariance for lag zero, consider using var_phi_rho_cov instead. Please note that this might yield a different result.
• var_phi_rho_cov
  Estimate the variance of a time series of length n, given the AR parameters, auto-correlation coefficients (ACF), and the auto-covariance for lag zero.