;;; 20 point time series from page 287 (first row is X_1, X_2, X_3, X_4; ;;; second row is X_5, X_6, X_7, X_8; etc) 71.0 63.0 70.0 88.0 99.0 90.0 110.0 135.0 128.0 154.0 156.0 141.0 131.0 132.0 141.0 104.0 136.0 146.0 124.0 129.0 sample mean = 117.4 p = 1 \phi_{1,1} = 0.7415951139732189 innovations variance = 352.21671265971565 p = 2 \phi_{1,2} = 0.7557426273700377 \phi_{2,2} = -0.01907713943936502 innovations variance = 352.0885278781919 p = 3 \phi_{1,3} = 0.7564278899100625 \phi_{2,3} = -0.046223877768903764 \phi_{3,3} = 0.03592061284674202 innovations variance = 351.6342314211136 p = 4 \phi_{1,4} = 0.7658252885356229 \phi_{2,4} = -0.058316772933774776 \phi_{3,4} = 0.23381407427807 \phi_{4,4} = -0.2616157654563174 innovations variance = 327.56739697517594 ;;; for the fitted AR(4) model, here are the corresponding estimated ;;; acvs for lags 0 to 20 (note that the values for lags 0 up to 4 ;;; correspond to the usual biased estimates for the acvs) lag 0 Yule-Walker acvs estimate = 782.64 lag 1 Yule-Walker acvs estimate = 580.402 lag 2 Yule-Walker acvs estimate = 423.704 lag 3 Yule-Walker acvs estimate = 321.786 lag 4 Yule-Walker acvs estimate = 152.678 lag 5 Yule-Walker acvs estimate = 45.38479733331212 lag 6 Yule-Walker acvs estimate = -9.756413326328783 lag 7 Yule-Walker acvs estimate = -58.60442844194004 lag 8 Yule-Walker acvs estimate = -73.64315824396786 lag 9 Yule-Walker acvs estimate = -67.13473700910302 lag 10 Yule-Walker acvs estimate = -58.26895664759184 lag 11 Yule-Walker acvs estimate = -42.595723788941825 lag 12 Yule-Walker acvs estimate = -25.65366011821324 lag 13 Yule-Walker acvs estimate = -13.22277305623658 lag 14 Yule-Walker acvs estimate = -3.345697349214449 lag 15 Yule-Walker acvs estimate = 3.3544159078859703 lag 16 Yule-Walker acvs estimate = 6.383738290194124 lag 17 Yule-Walker acvs estimate = 7.370224273239524 lag 18 Yule-Walker acvs estimate = 6.931621937533915 lag 19 Yule-Walker acvs estimate = 5.493643448273032 lag 20 Yule-Walker acvs estimate = 3.8561168426989134