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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 04 Dec 2012 06:37:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/04/t13546210919ry7zj67h9b56kv.htm/, Retrieved Thu, 28 Mar 2024 20:00:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196187, Retrieved Thu, 28 Mar 2024 20:00:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-14 11:54:22] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD    [(Partial) Autocorrelation Function] [WS9, ACF 2] [2012-12-04 11:37:23] [e4c351aee2a0bb2c047702ea90f356fa] [Current]
- R P       [(Partial) Autocorrelation Function] [WS9, ACF D = 1, d...] [2012-12-04 11:52:43] [346d881f0ddec1e86442b342eb3e8104]
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Dataseries X:
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196187&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196187&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.002261-0.01910.492426
2-0.25444-2.1440.017731
30.1626341.37040.087443
4-0.07607-0.6410.2618
5-0.160619-1.35340.090111
6-0.261848-2.20640.015297
7-0.169725-1.43010.078533
8-0.061441-0.51770.303136
90.1235071.04070.150775
10-0.22562-1.90110.030673
110.0171170.14420.442862
120.800546.74550
130.0216140.18210.428001
14-0.210156-1.77080.040443
150.1412121.18990.11903
16-0.066442-0.55990.288671
17-0.125744-1.05950.146474
18-0.210173-1.7710.04043
19-0.148759-1.25350.107075
20-0.037411-0.31520.376755
210.079510.670.252528
22-0.165342-1.39320.083954
23-0.00994-0.08380.466745
240.6200075.22431e-06
250.0679420.57250.284398
26-0.193332-1.6290.053867
270.1107680.93340.176901
28-0.028947-0.24390.404
29-0.106843-0.90030.18551
30-0.165619-1.39550.083603
31-0.104044-0.87670.191806
32-0.043785-0.36890.356634
330.0562180.47370.318584
34-0.103659-0.87340.192682
35-0.043625-0.36760.357136
360.4808984.05216.4e-05
370.0614260.51760.303179
38-0.15105-1.27280.103626
390.0935140.7880.216671
40-0.029716-0.25040.401503
41-0.075866-0.63930.262356
42-0.115605-0.97410.166656
43-0.07218-0.60820.272497
44-0.04772-0.40210.344411
450.043010.36240.359062
46-0.065377-0.55090.291723
47-0.044568-0.37550.35419
480.3313342.79190.003364

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.002261 & -0.0191 & 0.492426 \tabularnewline
2 & -0.25444 & -2.144 & 0.017731 \tabularnewline
3 & 0.162634 & 1.3704 & 0.087443 \tabularnewline
4 & -0.07607 & -0.641 & 0.2618 \tabularnewline
5 & -0.160619 & -1.3534 & 0.090111 \tabularnewline
6 & -0.261848 & -2.2064 & 0.015297 \tabularnewline
7 & -0.169725 & -1.4301 & 0.078533 \tabularnewline
8 & -0.061441 & -0.5177 & 0.303136 \tabularnewline
9 & 0.123507 & 1.0407 & 0.150775 \tabularnewline
10 & -0.22562 & -1.9011 & 0.030673 \tabularnewline
11 & 0.017117 & 0.1442 & 0.442862 \tabularnewline
12 & 0.80054 & 6.7455 & 0 \tabularnewline
13 & 0.021614 & 0.1821 & 0.428001 \tabularnewline
14 & -0.210156 & -1.7708 & 0.040443 \tabularnewline
15 & 0.141212 & 1.1899 & 0.11903 \tabularnewline
16 & -0.066442 & -0.5599 & 0.288671 \tabularnewline
17 & -0.125744 & -1.0595 & 0.146474 \tabularnewline
18 & -0.210173 & -1.771 & 0.04043 \tabularnewline
19 & -0.148759 & -1.2535 & 0.107075 \tabularnewline
20 & -0.037411 & -0.3152 & 0.376755 \tabularnewline
21 & 0.07951 & 0.67 & 0.252528 \tabularnewline
22 & -0.165342 & -1.3932 & 0.083954 \tabularnewline
23 & -0.00994 & -0.0838 & 0.466745 \tabularnewline
24 & 0.620007 & 5.2243 & 1e-06 \tabularnewline
25 & 0.067942 & 0.5725 & 0.284398 \tabularnewline
26 & -0.193332 & -1.629 & 0.053867 \tabularnewline
27 & 0.110768 & 0.9334 & 0.176901 \tabularnewline
28 & -0.028947 & -0.2439 & 0.404 \tabularnewline
29 & -0.106843 & -0.9003 & 0.18551 \tabularnewline
30 & -0.165619 & -1.3955 & 0.083603 \tabularnewline
31 & -0.104044 & -0.8767 & 0.191806 \tabularnewline
32 & -0.043785 & -0.3689 & 0.356634 \tabularnewline
33 & 0.056218 & 0.4737 & 0.318584 \tabularnewline
34 & -0.103659 & -0.8734 & 0.192682 \tabularnewline
35 & -0.043625 & -0.3676 & 0.357136 \tabularnewline
36 & 0.480898 & 4.0521 & 6.4e-05 \tabularnewline
37 & 0.061426 & 0.5176 & 0.303179 \tabularnewline
38 & -0.15105 & -1.2728 & 0.103626 \tabularnewline
39 & 0.093514 & 0.788 & 0.216671 \tabularnewline
40 & -0.029716 & -0.2504 & 0.401503 \tabularnewline
41 & -0.075866 & -0.6393 & 0.262356 \tabularnewline
42 & -0.115605 & -0.9741 & 0.166656 \tabularnewline
43 & -0.07218 & -0.6082 & 0.272497 \tabularnewline
44 & -0.04772 & -0.4021 & 0.344411 \tabularnewline
45 & 0.04301 & 0.3624 & 0.359062 \tabularnewline
46 & -0.065377 & -0.5509 & 0.291723 \tabularnewline
47 & -0.044568 & -0.3755 & 0.35419 \tabularnewline
48 & 0.331334 & 2.7919 & 0.003364 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196187&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]-0.002261[/C][C]-0.0191[/C][C]0.492426[/C][/ROW]
[ROW][C]2[/C][C]-0.25444[/C][C]-2.144[/C][C]0.017731[/C][/ROW]
[ROW][C]3[/C][C]0.162634[/C][C]1.3704[/C][C]0.087443[/C][/ROW]
[ROW][C]4[/C][C]-0.07607[/C][C]-0.641[/C][C]0.2618[/C][/ROW]
[ROW][C]5[/C][C]-0.160619[/C][C]-1.3534[/C][C]0.090111[/C][/ROW]
[ROW][C]6[/C][C]-0.261848[/C][C]-2.2064[/C][C]0.015297[/C][/ROW]
[ROW][C]7[/C][C]-0.169725[/C][C]-1.4301[/C][C]0.078533[/C][/ROW]
[ROW][C]8[/C][C]-0.061441[/C][C]-0.5177[/C][C]0.303136[/C][/ROW]
[ROW][C]9[/C][C]0.123507[/C][C]1.0407[/C][C]0.150775[/C][/ROW]
[ROW][C]10[/C][C]-0.22562[/C][C]-1.9011[/C][C]0.030673[/C][/ROW]
[ROW][C]11[/C][C]0.017117[/C][C]0.1442[/C][C]0.442862[/C][/ROW]
[ROW][C]12[/C][C]0.80054[/C][C]6.7455[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.021614[/C][C]0.1821[/C][C]0.428001[/C][/ROW]
[ROW][C]14[/C][C]-0.210156[/C][C]-1.7708[/C][C]0.040443[/C][/ROW]
[ROW][C]15[/C][C]0.141212[/C][C]1.1899[/C][C]0.11903[/C][/ROW]
[ROW][C]16[/C][C]-0.066442[/C][C]-0.5599[/C][C]0.288671[/C][/ROW]
[ROW][C]17[/C][C]-0.125744[/C][C]-1.0595[/C][C]0.146474[/C][/ROW]
[ROW][C]18[/C][C]-0.210173[/C][C]-1.771[/C][C]0.04043[/C][/ROW]
[ROW][C]19[/C][C]-0.148759[/C][C]-1.2535[/C][C]0.107075[/C][/ROW]
[ROW][C]20[/C][C]-0.037411[/C][C]-0.3152[/C][C]0.376755[/C][/ROW]
[ROW][C]21[/C][C]0.07951[/C][C]0.67[/C][C]0.252528[/C][/ROW]
[ROW][C]22[/C][C]-0.165342[/C][C]-1.3932[/C][C]0.083954[/C][/ROW]
[ROW][C]23[/C][C]-0.00994[/C][C]-0.0838[/C][C]0.466745[/C][/ROW]
[ROW][C]24[/C][C]0.620007[/C][C]5.2243[/C][C]1e-06[/C][/ROW]
[ROW][C]25[/C][C]0.067942[/C][C]0.5725[/C][C]0.284398[/C][/ROW]
[ROW][C]26[/C][C]-0.193332[/C][C]-1.629[/C][C]0.053867[/C][/ROW]
[ROW][C]27[/C][C]0.110768[/C][C]0.9334[/C][C]0.176901[/C][/ROW]
[ROW][C]28[/C][C]-0.028947[/C][C]-0.2439[/C][C]0.404[/C][/ROW]
[ROW][C]29[/C][C]-0.106843[/C][C]-0.9003[/C][C]0.18551[/C][/ROW]
[ROW][C]30[/C][C]-0.165619[/C][C]-1.3955[/C][C]0.083603[/C][/ROW]
[ROW][C]31[/C][C]-0.104044[/C][C]-0.8767[/C][C]0.191806[/C][/ROW]
[ROW][C]32[/C][C]-0.043785[/C][C]-0.3689[/C][C]0.356634[/C][/ROW]
[ROW][C]33[/C][C]0.056218[/C][C]0.4737[/C][C]0.318584[/C][/ROW]
[ROW][C]34[/C][C]-0.103659[/C][C]-0.8734[/C][C]0.192682[/C][/ROW]
[ROW][C]35[/C][C]-0.043625[/C][C]-0.3676[/C][C]0.357136[/C][/ROW]
[ROW][C]36[/C][C]0.480898[/C][C]4.0521[/C][C]6.4e-05[/C][/ROW]
[ROW][C]37[/C][C]0.061426[/C][C]0.5176[/C][C]0.303179[/C][/ROW]
[ROW][C]38[/C][C]-0.15105[/C][C]-1.2728[/C][C]0.103626[/C][/ROW]
[ROW][C]39[/C][C]0.093514[/C][C]0.788[/C][C]0.216671[/C][/ROW]
[ROW][C]40[/C][C]-0.029716[/C][C]-0.2504[/C][C]0.401503[/C][/ROW]
[ROW][C]41[/C][C]-0.075866[/C][C]-0.6393[/C][C]0.262356[/C][/ROW]
[ROW][C]42[/C][C]-0.115605[/C][C]-0.9741[/C][C]0.166656[/C][/ROW]
[ROW][C]43[/C][C]-0.07218[/C][C]-0.6082[/C][C]0.272497[/C][/ROW]
[ROW][C]44[/C][C]-0.04772[/C][C]-0.4021[/C][C]0.344411[/C][/ROW]
[ROW][C]45[/C][C]0.04301[/C][C]0.3624[/C][C]0.359062[/C][/ROW]
[ROW][C]46[/C][C]-0.065377[/C][C]-0.5509[/C][C]0.291723[/C][/ROW]
[ROW][C]47[/C][C]-0.044568[/C][C]-0.3755[/C][C]0.35419[/C][/ROW]
[ROW][C]48[/C][C]0.331334[/C][C]2.7919[/C][C]0.003364[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196187&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
1-0.002261-0.01910.492426
2-0.25444-2.1440.017731
30.1626341.37040.087443
4-0.07607-0.6410.2618
5-0.160619-1.35340.090111
6-0.261848-2.20640.015297
7-0.169725-1.43010.078533
8-0.061441-0.51770.303136
90.1235071.04070.150775
10-0.22562-1.90110.030673
110.0171170.14420.442862
120.800546.74550
130.0216140.18210.428001
14-0.210156-1.77080.040443
150.1412121.18990.11903
16-0.066442-0.55990.288671
17-0.125744-1.05950.146474
18-0.210173-1.7710.04043
19-0.148759-1.25350.107075
20-0.037411-0.31520.376755
210.079510.670.252528
22-0.165342-1.39320.083954
23-0.00994-0.08380.466745
240.6200075.22431e-06
250.0679420.57250.284398
26-0.193332-1.6290.053867
270.1107680.93340.176901
28-0.028947-0.24390.404
29-0.106843-0.90030.18551
30-0.165619-1.39550.083603
31-0.104044-0.87670.191806
32-0.043785-0.36890.356634
330.0562180.47370.318584
34-0.103659-0.87340.192682
35-0.043625-0.36760.357136
360.4808984.05216.4e-05
370.0614260.51760.303179
38-0.15105-1.27280.103626
390.0935140.7880.216671
40-0.029716-0.25040.401503
41-0.075866-0.63930.262356
42-0.115605-0.97410.166656
43-0.07218-0.60820.272497
44-0.04772-0.40210.344411
450.043010.36240.359062
46-0.065377-0.55090.291723
47-0.044568-0.37550.35419
480.3313342.79190.003364







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.002261-0.01910.492426
2-0.254447-2.1440.017729
30.1725071.45360.075236
4-0.161969-1.36480.088316
5-0.070348-0.59280.277613
6-0.386675-3.25820.000861
7-0.227307-1.91530.02974
8-0.326419-2.75050.003772
90.0483210.40720.342559
10-0.605849-5.1051e-06
11-0.182236-1.53550.064547
120.4931934.15574.5e-05
130.0556770.46910.320202
140.0052340.04410.482474
15-0.110759-0.93330.176921
16-0.09272-0.78130.21862
17-0.004442-0.03740.485123
180.0472990.39850.345711
190.0843750.7110.239721
200.0233590.19680.422262
21-0.028321-0.23860.406038
220.0697850.5880.279192
23-0.103036-0.86820.194106
24-0.02935-0.24730.402692
250.0411490.34670.364911
26-0.02803-0.23620.406983
27-0.008964-0.07550.470003
280.0348290.29350.385007
29-0.032707-0.27560.391831
300.0049030.04130.483581
310.0420760.35450.361994
32-0.038238-0.32220.374124
330.0186130.15680.437911
340.033190.27970.390273
350.01330.11210.455544
360.0101530.08550.466033
37-0.113488-0.95630.171091
380.0846860.71360.238914
39-0.026527-0.22350.411886
40-0.006527-0.0550.478149
410.0152310.12830.449122
420.0152690.12870.448996
43-0.00204-0.01720.493166
440.0294040.24780.402515
45-0.025799-0.21740.414266
460.017340.14610.442126
470.0422730.35620.361373
48-0.080682-0.67980.249408

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.002261 & -0.0191 & 0.492426 \tabularnewline
2 & -0.254447 & -2.144 & 0.017729 \tabularnewline
3 & 0.172507 & 1.4536 & 0.075236 \tabularnewline
4 & -0.161969 & -1.3648 & 0.088316 \tabularnewline
5 & -0.070348 & -0.5928 & 0.277613 \tabularnewline
6 & -0.386675 & -3.2582 & 0.000861 \tabularnewline
7 & -0.227307 & -1.9153 & 0.02974 \tabularnewline
8 & -0.326419 & -2.7505 & 0.003772 \tabularnewline
9 & 0.048321 & 0.4072 & 0.342559 \tabularnewline
10 & -0.605849 & -5.105 & 1e-06 \tabularnewline
11 & -0.182236 & -1.5355 & 0.064547 \tabularnewline
12 & 0.493193 & 4.1557 & 4.5e-05 \tabularnewline
13 & 0.055677 & 0.4691 & 0.320202 \tabularnewline
14 & 0.005234 & 0.0441 & 0.482474 \tabularnewline
15 & -0.110759 & -0.9333 & 0.176921 \tabularnewline
16 & -0.09272 & -0.7813 & 0.21862 \tabularnewline
17 & -0.004442 & -0.0374 & 0.485123 \tabularnewline
18 & 0.047299 & 0.3985 & 0.345711 \tabularnewline
19 & 0.084375 & 0.711 & 0.239721 \tabularnewline
20 & 0.023359 & 0.1968 & 0.422262 \tabularnewline
21 & -0.028321 & -0.2386 & 0.406038 \tabularnewline
22 & 0.069785 & 0.588 & 0.279192 \tabularnewline
23 & -0.103036 & -0.8682 & 0.194106 \tabularnewline
24 & -0.02935 & -0.2473 & 0.402692 \tabularnewline
25 & 0.041149 & 0.3467 & 0.364911 \tabularnewline
26 & -0.02803 & -0.2362 & 0.406983 \tabularnewline
27 & -0.008964 & -0.0755 & 0.470003 \tabularnewline
28 & 0.034829 & 0.2935 & 0.385007 \tabularnewline
29 & -0.032707 & -0.2756 & 0.391831 \tabularnewline
30 & 0.004903 & 0.0413 & 0.483581 \tabularnewline
31 & 0.042076 & 0.3545 & 0.361994 \tabularnewline
32 & -0.038238 & -0.3222 & 0.374124 \tabularnewline
33 & 0.018613 & 0.1568 & 0.437911 \tabularnewline
34 & 0.03319 & 0.2797 & 0.390273 \tabularnewline
35 & 0.0133 & 0.1121 & 0.455544 \tabularnewline
36 & 0.010153 & 0.0855 & 0.466033 \tabularnewline
37 & -0.113488 & -0.9563 & 0.171091 \tabularnewline
38 & 0.084686 & 0.7136 & 0.238914 \tabularnewline
39 & -0.026527 & -0.2235 & 0.411886 \tabularnewline
40 & -0.006527 & -0.055 & 0.478149 \tabularnewline
41 & 0.015231 & 0.1283 & 0.449122 \tabularnewline
42 & 0.015269 & 0.1287 & 0.448996 \tabularnewline
43 & -0.00204 & -0.0172 & 0.493166 \tabularnewline
44 & 0.029404 & 0.2478 & 0.402515 \tabularnewline
45 & -0.025799 & -0.2174 & 0.414266 \tabularnewline
46 & 0.01734 & 0.1461 & 0.442126 \tabularnewline
47 & 0.042273 & 0.3562 & 0.361373 \tabularnewline
48 & -0.080682 & -0.6798 & 0.249408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196187&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]-0.002261[/C][C]-0.0191[/C][C]0.492426[/C][/ROW]
[ROW][C]2[/C][C]-0.254447[/C][C]-2.144[/C][C]0.017729[/C][/ROW]
[ROW][C]3[/C][C]0.172507[/C][C]1.4536[/C][C]0.075236[/C][/ROW]
[ROW][C]4[/C][C]-0.161969[/C][C]-1.3648[/C][C]0.088316[/C][/ROW]
[ROW][C]5[/C][C]-0.070348[/C][C]-0.5928[/C][C]0.277613[/C][/ROW]
[ROW][C]6[/C][C]-0.386675[/C][C]-3.2582[/C][C]0.000861[/C][/ROW]
[ROW][C]7[/C][C]-0.227307[/C][C]-1.9153[/C][C]0.02974[/C][/ROW]
[ROW][C]8[/C][C]-0.326419[/C][C]-2.7505[/C][C]0.003772[/C][/ROW]
[ROW][C]9[/C][C]0.048321[/C][C]0.4072[/C][C]0.342559[/C][/ROW]
[ROW][C]10[/C][C]-0.605849[/C][C]-5.105[/C][C]1e-06[/C][/ROW]
[ROW][C]11[/C][C]-0.182236[/C][C]-1.5355[/C][C]0.064547[/C][/ROW]
[ROW][C]12[/C][C]0.493193[/C][C]4.1557[/C][C]4.5e-05[/C][/ROW]
[ROW][C]13[/C][C]0.055677[/C][C]0.4691[/C][C]0.320202[/C][/ROW]
[ROW][C]14[/C][C]0.005234[/C][C]0.0441[/C][C]0.482474[/C][/ROW]
[ROW][C]15[/C][C]-0.110759[/C][C]-0.9333[/C][C]0.176921[/C][/ROW]
[ROW][C]16[/C][C]-0.09272[/C][C]-0.7813[/C][C]0.21862[/C][/ROW]
[ROW][C]17[/C][C]-0.004442[/C][C]-0.0374[/C][C]0.485123[/C][/ROW]
[ROW][C]18[/C][C]0.047299[/C][C]0.3985[/C][C]0.345711[/C][/ROW]
[ROW][C]19[/C][C]0.084375[/C][C]0.711[/C][C]0.239721[/C][/ROW]
[ROW][C]20[/C][C]0.023359[/C][C]0.1968[/C][C]0.422262[/C][/ROW]
[ROW][C]21[/C][C]-0.028321[/C][C]-0.2386[/C][C]0.406038[/C][/ROW]
[ROW][C]22[/C][C]0.069785[/C][C]0.588[/C][C]0.279192[/C][/ROW]
[ROW][C]23[/C][C]-0.103036[/C][C]-0.8682[/C][C]0.194106[/C][/ROW]
[ROW][C]24[/C][C]-0.02935[/C][C]-0.2473[/C][C]0.402692[/C][/ROW]
[ROW][C]25[/C][C]0.041149[/C][C]0.3467[/C][C]0.364911[/C][/ROW]
[ROW][C]26[/C][C]-0.02803[/C][C]-0.2362[/C][C]0.406983[/C][/ROW]
[ROW][C]27[/C][C]-0.008964[/C][C]-0.0755[/C][C]0.470003[/C][/ROW]
[ROW][C]28[/C][C]0.034829[/C][C]0.2935[/C][C]0.385007[/C][/ROW]
[ROW][C]29[/C][C]-0.032707[/C][C]-0.2756[/C][C]0.391831[/C][/ROW]
[ROW][C]30[/C][C]0.004903[/C][C]0.0413[/C][C]0.483581[/C][/ROW]
[ROW][C]31[/C][C]0.042076[/C][C]0.3545[/C][C]0.361994[/C][/ROW]
[ROW][C]32[/C][C]-0.038238[/C][C]-0.3222[/C][C]0.374124[/C][/ROW]
[ROW][C]33[/C][C]0.018613[/C][C]0.1568[/C][C]0.437911[/C][/ROW]
[ROW][C]34[/C][C]0.03319[/C][C]0.2797[/C][C]0.390273[/C][/ROW]
[ROW][C]35[/C][C]0.0133[/C][C]0.1121[/C][C]0.455544[/C][/ROW]
[ROW][C]36[/C][C]0.010153[/C][C]0.0855[/C][C]0.466033[/C][/ROW]
[ROW][C]37[/C][C]-0.113488[/C][C]-0.9563[/C][C]0.171091[/C][/ROW]
[ROW][C]38[/C][C]0.084686[/C][C]0.7136[/C][C]0.238914[/C][/ROW]
[ROW][C]39[/C][C]-0.026527[/C][C]-0.2235[/C][C]0.411886[/C][/ROW]
[ROW][C]40[/C][C]-0.006527[/C][C]-0.055[/C][C]0.478149[/C][/ROW]
[ROW][C]41[/C][C]0.015231[/C][C]0.1283[/C][C]0.449122[/C][/ROW]
[ROW][C]42[/C][C]0.015269[/C][C]0.1287[/C][C]0.448996[/C][/ROW]
[ROW][C]43[/C][C]-0.00204[/C][C]-0.0172[/C][C]0.493166[/C][/ROW]
[ROW][C]44[/C][C]0.029404[/C][C]0.2478[/C][C]0.402515[/C][/ROW]
[ROW][C]45[/C][C]-0.025799[/C][C]-0.2174[/C][C]0.414266[/C][/ROW]
[ROW][C]46[/C][C]0.01734[/C][C]0.1461[/C][C]0.442126[/C][/ROW]
[ROW][C]47[/C][C]0.042273[/C][C]0.3562[/C][C]0.361373[/C][/ROW]
[ROW][C]48[/C][C]-0.080682[/C][C]-0.6798[/C][C]0.249408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196187&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
1-0.002261-0.01910.492426
2-0.254447-2.1440.017729
30.1725071.45360.075236
4-0.161969-1.36480.088316
5-0.070348-0.59280.277613
6-0.386675-3.25820.000861
7-0.227307-1.91530.02974
8-0.326419-2.75050.003772
90.0483210.40720.342559
10-0.605849-5.1051e-06
11-0.182236-1.53550.064547
120.4931934.15574.5e-05
130.0556770.46910.320202
140.0052340.04410.482474
15-0.110759-0.93330.176921
16-0.09272-0.78130.21862
17-0.004442-0.03740.485123
180.0472990.39850.345711
190.0843750.7110.239721
200.0233590.19680.422262
21-0.028321-0.23860.406038
220.0697850.5880.279192
23-0.103036-0.86820.194106
24-0.02935-0.24730.402692
250.0411490.34670.364911
26-0.02803-0.23620.406983
27-0.008964-0.07550.470003
280.0348290.29350.385007
29-0.032707-0.27560.391831
300.0049030.04130.483581
310.0420760.35450.361994
32-0.038238-0.32220.374124
330.0186130.15680.437911
340.033190.27970.390273
350.01330.11210.455544
360.0101530.08550.466033
37-0.113488-0.95630.171091
380.0846860.71360.238914
39-0.026527-0.22350.411886
40-0.006527-0.0550.478149
410.0152310.12830.449122
420.0152690.12870.448996
43-0.00204-0.01720.493166
440.0294040.24780.402515
45-0.025799-0.21740.414266
460.017340.14610.442126
470.0422730.35620.361373
48-0.080682-0.67980.249408



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')