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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 16 Jul 2008 03:23:32 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Jul/16/t1216200263vfu8od4cl2cvonu.htm/, Retrieved Sat, 01 Aug 2026 11:20:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13843, Retrieved Sat, 01 Aug 2026 11:20:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact618
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [non-seasonal trend] [2008-07-16 09:23:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
385.34

438.82

317.22

505.15

513.57

515.48

519.31

524.42

430.38

527.86

467.25

547.68

428.10

519.38

404.74

377.95

439.90

434.65

472.25

434.87

468.36

486.00

476.66

422.87

321.15

360.79

435.66

493.59

472.93

469.13

608.37

562.38

525.81

415.59

398.06

436.89

434.64

432.37

436.46

454.18

353.71

486.32

397.47

340.25

427.57

472.29

466.95

463.79

332.87

396.88

400.09

513.36

559.07

602.50

436.19

309.19

443.44

429.61

669.12

441.38

440.42

471.11

372.26

308.55

330.52

439.67

442.34

434.54

490.87

343.64

343.52

338.43

424.45

358.84

341.53

330.08

497.54

333.63

362.37

398.84

471.53

289.33

351.94

510.98

461.96

347.99

436.01

499.40

516.88

421.33

291.39

374.25

398.23

365.47

399.48

356.31

355.06

389.09

285.71

392.00

456.03

421.94

403.81

396.69

502.69

358.37

521.93

463.62

426.42

485.72

401.01

531.99

430.61

343.58

315.35

307.93

443.44

424.78

409.02

396.94

337.55

403.86

393.54

330.80

269.71

297.89

416.37

532.98

427.62

260.76

299.12

339.37

409.16

416.12

388.47

374.89

430.87

494.00

477.09

458.11

404.04

327.33

308.86

354.60

345.44

490.86

558.26

372.58

380.16

367.25

321.93

303.80

411.05

501.10

376.05

593.39

378.92

544.44

436.73

325.05

350.66

366.97

316.25

332.28

354.60

567.46

464.75

418.27

370.65

500.30

435.10

414.71

470.80

475.48

589.40

769.36

437.62

337.55

383.22

328.85

330.94

370.53

536.53

484.39

410.36

429.90

420.29

487.75

542.87

478.49

393.81

332.17

437.82

433.74

473.94

492.12

429.77

486.14

523.94

400.85

365.03

309.43

340.65

400.06

407.61

427.46

512.95

457.17

438.17

339.29

326.90

405.07

518.25

512.58

606.84

551.57

460.45

410.94

478.40

516.75

460.18

434.73

425.87

416.21

400.46

408.78

450.60

352.62

519.44

294.28

344.59

438.06

350.12

437.82

428.98

446.66

409.37

463.74

560.29

572.95

477.94

394.91

370.99

446.05

448.95

341.22

235.96

334.07

457.87

614.63

414.79

403.80

501.73

386.21

448.13

374.19

423.79

454.79

390.30

358.65

335.02

321.85

329.94

342.15

584.59

451.13

423.44

442.77

370.56

383.49

428.35

432.89

508.39

554.24

415.83

383.48

287.35

280.27

424.89

376.05

421.94

382.62

508.37

290.79

206.38

308.37

505.04

511.66

596.84

330.39

293.53

560.72

482.61

563.69

295.73

295.19

338.19

407.33

477.14

428.89

614.89

628.98

786.59

472.22

319.54

331.44

317.86

300.61

373.81

401.00

569.96

349.32

417.30

495.64

465.46

431.26

415.03

466.93

506.33

478.20

486.57

450.41

713.47

754.51

375.60

343.75

551.51

447.13

396.40

474.09

525.82

591.87

654.39

668.46

732.83

531.97

471.77

525.22

415.67

483.73

533.49

534.96

479.64

573.62

599.54

768.71

566.73

570.12

574.29

617.31

638.50

507.23

493.42

642.42

697.01

535.03

432.21

446.66

631.22

703.81

561.97

652.98

709.05

539.00

458.89

523.21

573.84

766.18

571.81

677.80

580.64

565.14

611.92

569.39

547.63

525.80

523.33

607.71

526.63

515.49

514.28

493.10

495.36

629.82

657.57

669.76

632.46

636.75

610.52

474.27

376.10

330.56

480.97

491.44

582.88

670.05

616.88

645.68

854.13

559.46

603.91

511.72

480.74

397.82

441.76

558.62

484.92

527.55

520.59

550.67

797.42

697.64

504.57

470.89

711.13

757.07

563.30

600.92

546.61

532.03

571.56

683.56

415.58

542.94

458.98

454.34

498.52

470.67

633.98

791.30

905.45

523.65

707.17

720.68

835.48

741.77

671.46

540.95

459.91

512.47

693.51

526.15

389.69

462.10

516.48

798.05

1006.19

588.32

713.47

641.86

838.13

528.20

776.93

707.60

663.77

455.82

546.17

557.09

495.37

570.79

525.78

658.06

659.04

543.52

791.38

750.78

561.69

540.96

451.16

476.54

495.21

617.02

673.62

510.93

503.34

525.76

642.56

820.75

475.15

392.97

381.11

385.35

497.83

549.93

506.81

525.68

497.76

541.69

663.20

678.64

651.17

497.86

583.47

808.68

701.64

551.62

522.52

537.05

537.05

539.26

656.62

651.66

632.86

835.90

841.35

741.25

618.01

777.69

764.89

756.84

801.02

755.34

590.96

744.05

633.14

534.92

572.22

685.11

727.19

720.30

684.20

614.93

575.72

620.94

655.86

772.21

756.25

687.71

603.68

653.91

658.03

875.81

874.00

622.04

599.86

738.64

919.68

897.71

687.41

645.95

662.24

822.04

736.15

693.71

682.87

786.37

880.52

791.95

914.20

773.57

609.17

588.11

781.70

878.29

761.48

664.59

717.18

691.07

610.89

713.66

787.88

719.53

652.11

695.46

739.78

819.39

824.47

774.19

739.28

710.02

671.53

562.67

625.09

702.37

806.92

822.81

758.54

753.24

725.16

715.06

732.43

692.81

716.50

860.77

714.09

645.90

581.26

555.99

576.22

669.32

854.82

889.11

823.62

653.60

565.62

549.91

639.70

670.66

665.73

528.24

474.14

502.55

594.40

767.06

765.84

589.06

578.99

680.74

644.80

652.78

658.08

552.37

569.73

700.34

605.86

589.14

573.16

597.47

600.00

553.42

499.14

489.79

472.83

501.34

491.06

453.77

484.71

566.38

457.66

403.04

365.00

379.49

426.48

479.02

523.12

406.11

399.38

403.81

425.48

399.38

416.23

437.43

410.49

438.55

468.95

531.23

449.37

444.73

470.40

422.93

475.12

578.56

555.82

583.90

494.33

455.60

441.78

430.74

354.89

326.81

382.20

402.06

419.86

399.31

350.37

348.73

294.49

226.73

238.97

221.57

199.37

210.14

283.55

352.49

251.66

180.66

323.39

429.25

435.36

424.63

389.79

362.98

365.56

388.13

447.39

481.22

519.89

525.06

497.16

508.05

451.48

352.42

371.14

302.85

296.23

284.45

286.10

266.88

271.51

256.11

259.78

243.45

236.43

232.80

226.41

222.40

241.52

205.09

227.62

360.59

378.85

289.30

321.45

298.97

296.12

291.20

246.31

247.13

237.60

249.05

218.01

201.32

192.78

184.83

166.84

154.30

147.24

139.44

124.68

113.20

119.97

128.81

128.21




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13843&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13843&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13843&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.79892121.630
20.66392417.97510
30.6047516.3730
40.6129316.59440
50.61923816.76520
60.60204616.29980
70.58386915.80770
80.57408615.54280
90.57613515.59830
100.59131816.00930
110.58791615.91720
120.58674215.88540
130.57370215.53240
140.56252115.22970
150.56339615.25340
160.57257515.50190
170.55748315.09330
180.54623614.78880
190.53593314.50980
200.54234314.68340
210.53398414.45710
220.53003214.35010
230.52529314.22180
240.52376414.18040
250.51016113.81210
260.50282813.61360
270.51017913.81260
280.51054413.82250

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.798921 & 21.63 & 0 \tabularnewline
2 & 0.663924 & 17.9751 & 0 \tabularnewline
3 & 0.60475 & 16.373 & 0 \tabularnewline
4 & 0.61293 & 16.5944 & 0 \tabularnewline
5 & 0.619238 & 16.7652 & 0 \tabularnewline
6 & 0.602046 & 16.2998 & 0 \tabularnewline
7 & 0.583869 & 15.8077 & 0 \tabularnewline
8 & 0.574086 & 15.5428 & 0 \tabularnewline
9 & 0.576135 & 15.5983 & 0 \tabularnewline
10 & 0.591318 & 16.0093 & 0 \tabularnewline
11 & 0.587916 & 15.9172 & 0 \tabularnewline
12 & 0.586742 & 15.8854 & 0 \tabularnewline
13 & 0.573702 & 15.5324 & 0 \tabularnewline
14 & 0.562521 & 15.2297 & 0 \tabularnewline
15 & 0.563396 & 15.2534 & 0 \tabularnewline
16 & 0.572575 & 15.5019 & 0 \tabularnewline
17 & 0.557483 & 15.0933 & 0 \tabularnewline
18 & 0.546236 & 14.7888 & 0 \tabularnewline
19 & 0.535933 & 14.5098 & 0 \tabularnewline
20 & 0.542343 & 14.6834 & 0 \tabularnewline
21 & 0.533984 & 14.4571 & 0 \tabularnewline
22 & 0.530032 & 14.3501 & 0 \tabularnewline
23 & 0.525293 & 14.2218 & 0 \tabularnewline
24 & 0.523764 & 14.1804 & 0 \tabularnewline
25 & 0.510161 & 13.8121 & 0 \tabularnewline
26 & 0.502828 & 13.6136 & 0 \tabularnewline
27 & 0.510179 & 13.8126 & 0 \tabularnewline
28 & 0.510544 & 13.8225 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13843&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.798921[/C][C]21.63[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.663924[/C][C]17.9751[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.60475[/C][C]16.373[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.61293[/C][C]16.5944[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.619238[/C][C]16.7652[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.602046[/C][C]16.2998[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.583869[/C][C]15.8077[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.574086[/C][C]15.5428[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.576135[/C][C]15.5983[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.591318[/C][C]16.0093[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.587916[/C][C]15.9172[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.586742[/C][C]15.8854[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.573702[/C][C]15.5324[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.562521[/C][C]15.2297[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.563396[/C][C]15.2534[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.572575[/C][C]15.5019[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.557483[/C][C]15.0933[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.546236[/C][C]14.7888[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.535933[/C][C]14.5098[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.542343[/C][C]14.6834[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.533984[/C][C]14.4571[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.530032[/C][C]14.3501[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.525293[/C][C]14.2218[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.523764[/C][C]14.1804[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.510161[/C][C]13.8121[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.502828[/C][C]13.6136[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.510179[/C][C]13.8126[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.510544[/C][C]13.8225[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13843&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13843&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.79892121.630
20.66392417.97510
30.6047516.3730
40.6129316.59440
50.61923816.76520
60.60204616.29980
70.58386915.80770
80.57408615.54280
90.57613515.59830
100.59131816.00930
110.58791615.91720
120.58674215.88540
130.57370215.53240
140.56252115.22970
150.56339615.25340
160.57257515.50190
170.55748315.09330
180.54623614.78880
190.53593314.50980
200.54234314.68340
210.53398414.45710
220.53003214.35010
230.52529314.22180
240.52376414.18040
250.51016113.81210
260.50282813.61360
270.51017913.81260
280.51054413.82250







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.79892121.630
20.0709061.91970.027641
30.153624.15911.8e-05
40.217775.89590
50.124363.36694e-04
60.0650771.76190.039252
70.077242.09120.018428
80.0696041.88450.02995
90.0771042.08750.018593
100.1072222.90290.001904
110.0431641.16860.121469
120.074872.0270.02151
130.025290.68470.246874
140.0251150.680.248372
150.0523471.41730.078417
160.0608881.64850.049842
17-0.017024-0.46090.322499
180.0289210.7830.21694
190.0092420.25020.401243
200.0405671.09830.136214
21-0.013075-0.3540.361726
220.0226440.61310.270015
230.0141430.38290.350946
240.0168940.45740.323764
25-0.024713-0.66910.251829
260.0057780.15640.437863
270.0418341.13260.128875
28-0.001852-0.05010.480016

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.798921 & 21.63 & 0 \tabularnewline
2 & 0.070906 & 1.9197 & 0.027641 \tabularnewline
3 & 0.15362 & 4.1591 & 1.8e-05 \tabularnewline
4 & 0.21777 & 5.8959 & 0 \tabularnewline
5 & 0.12436 & 3.3669 & 4e-04 \tabularnewline
6 & 0.065077 & 1.7619 & 0.039252 \tabularnewline
7 & 0.07724 & 2.0912 & 0.018428 \tabularnewline
8 & 0.069604 & 1.8845 & 0.02995 \tabularnewline
9 & 0.077104 & 2.0875 & 0.018593 \tabularnewline
10 & 0.107222 & 2.9029 & 0.001904 \tabularnewline
11 & 0.043164 & 1.1686 & 0.121469 \tabularnewline
12 & 0.07487 & 2.027 & 0.02151 \tabularnewline
13 & 0.02529 & 0.6847 & 0.246874 \tabularnewline
14 & 0.025115 & 0.68 & 0.248372 \tabularnewline
15 & 0.052347 & 1.4173 & 0.078417 \tabularnewline
16 & 0.060888 & 1.6485 & 0.049842 \tabularnewline
17 & -0.017024 & -0.4609 & 0.322499 \tabularnewline
18 & 0.028921 & 0.783 & 0.21694 \tabularnewline
19 & 0.009242 & 0.2502 & 0.401243 \tabularnewline
20 & 0.040567 & 1.0983 & 0.136214 \tabularnewline
21 & -0.013075 & -0.354 & 0.361726 \tabularnewline
22 & 0.022644 & 0.6131 & 0.270015 \tabularnewline
23 & 0.014143 & 0.3829 & 0.350946 \tabularnewline
24 & 0.016894 & 0.4574 & 0.323764 \tabularnewline
25 & -0.024713 & -0.6691 & 0.251829 \tabularnewline
26 & 0.005778 & 0.1564 & 0.437863 \tabularnewline
27 & 0.041834 & 1.1326 & 0.128875 \tabularnewline
28 & -0.001852 & -0.0501 & 0.480016 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13843&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.798921[/C][C]21.63[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.070906[/C][C]1.9197[/C][C]0.027641[/C][/ROW]
[ROW][C]3[/C][C]0.15362[/C][C]4.1591[/C][C]1.8e-05[/C][/ROW]
[ROW][C]4[/C][C]0.21777[/C][C]5.8959[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.12436[/C][C]3.3669[/C][C]4e-04[/C][/ROW]
[ROW][C]6[/C][C]0.065077[/C][C]1.7619[/C][C]0.039252[/C][/ROW]
[ROW][C]7[/C][C]0.07724[/C][C]2.0912[/C][C]0.018428[/C][/ROW]
[ROW][C]8[/C][C]0.069604[/C][C]1.8845[/C][C]0.02995[/C][/ROW]
[ROW][C]9[/C][C]0.077104[/C][C]2.0875[/C][C]0.018593[/C][/ROW]
[ROW][C]10[/C][C]0.107222[/C][C]2.9029[/C][C]0.001904[/C][/ROW]
[ROW][C]11[/C][C]0.043164[/C][C]1.1686[/C][C]0.121469[/C][/ROW]
[ROW][C]12[/C][C]0.07487[/C][C]2.027[/C][C]0.02151[/C][/ROW]
[ROW][C]13[/C][C]0.02529[/C][C]0.6847[/C][C]0.246874[/C][/ROW]
[ROW][C]14[/C][C]0.025115[/C][C]0.68[/C][C]0.248372[/C][/ROW]
[ROW][C]15[/C][C]0.052347[/C][C]1.4173[/C][C]0.078417[/C][/ROW]
[ROW][C]16[/C][C]0.060888[/C][C]1.6485[/C][C]0.049842[/C][/ROW]
[ROW][C]17[/C][C]-0.017024[/C][C]-0.4609[/C][C]0.322499[/C][/ROW]
[ROW][C]18[/C][C]0.028921[/C][C]0.783[/C][C]0.21694[/C][/ROW]
[ROW][C]19[/C][C]0.009242[/C][C]0.2502[/C][C]0.401243[/C][/ROW]
[ROW][C]20[/C][C]0.040567[/C][C]1.0983[/C][C]0.136214[/C][/ROW]
[ROW][C]21[/C][C]-0.013075[/C][C]-0.354[/C][C]0.361726[/C][/ROW]
[ROW][C]22[/C][C]0.022644[/C][C]0.6131[/C][C]0.270015[/C][/ROW]
[ROW][C]23[/C][C]0.014143[/C][C]0.3829[/C][C]0.350946[/C][/ROW]
[ROW][C]24[/C][C]0.016894[/C][C]0.4574[/C][C]0.323764[/C][/ROW]
[ROW][C]25[/C][C]-0.024713[/C][C]-0.6691[/C][C]0.251829[/C][/ROW]
[ROW][C]26[/C][C]0.005778[/C][C]0.1564[/C][C]0.437863[/C][/ROW]
[ROW][C]27[/C][C]0.041834[/C][C]1.1326[/C][C]0.128875[/C][/ROW]
[ROW][C]28[/C][C]-0.001852[/C][C]-0.0501[/C][C]0.480016[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13843&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13843&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.79892121.630
20.0709061.91970.027641
30.153624.15911.8e-05
40.217775.89590
50.124363.36694e-04
60.0650771.76190.039252
70.077242.09120.018428
80.0696041.88450.02995
90.0771042.08750.018593
100.1072222.90290.001904
110.0431641.16860.121469
120.074872.0270.02151
130.025290.68470.246874
140.0251150.680.248372
150.0523471.41730.078417
160.0608881.64850.049842
17-0.017024-0.46090.322499
180.0289210.7830.21694
190.0092420.25020.401243
200.0405671.09830.136214
21-0.013075-0.3540.361726
220.0226440.61310.270015
230.0141430.38290.350946
240.0168940.45740.323764
25-0.024713-0.66910.251829
260.0057780.15640.437863
270.0418341.13260.128875
28-0.001852-0.05010.480016



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 1 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 1 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')