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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 computationWed, 30 Dec 2009 08:58:59 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/30/t1262188857wi1rh2apr963xhf.htm/, Retrieved Mon, 29 Apr 2024 04:57:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71317, Retrieved Mon, 29 Apr 2024 04:57:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [paper/11] [2009-12-30 15:58:59] [f94f05f163a3ee3ab544c4fef41db0eb] [Current]
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Dataseries X:
10519.20
10414.90
12476.80
12384.60
12266.70
12919.90
11497.30
12142.00
13919.40
12656.80
12034.10
13199.70
10881.30
11301.20
13643.90
12517.00
13981.10
14275.70
13425.00
13565.70
16216.30
12970.00
14079.90
14235.00
12213.40
12581.00
14130.40
14210.80
14378.50
13142.80
13714.70
13621.90
15379.80
13306.30
14391.20
14909.90
14025.40
12951.20
14344.30
16093.40
15413.60
14705.70
15972.80
16241.40
16626.40
17136.20
15622.90
18003.90
16136.10
14423.70
16789.40
16782.20
14133.80
12607.00
12004.50
12175.40
13268.00
12299.30
11800.60
13873.30
12315.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71317&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71317&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71317&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.332441-2.57510.006253
2-0.269029-2.08390.020718
30.317752.46130.008369
4-0.099855-0.77350.22114
5-0.108045-0.83690.202981
60.2709512.09880.020027
7-0.251439-1.94760.028071
80.0324790.25160.401112
90.2452391.89960.031147
10-0.380371-2.94630.002286
11-0.082853-0.64180.26173
120.4972023.85130.000144
13-0.206086-1.59630.057834
14-0.170625-1.32170.09565
150.1213740.94020.175452
160.0076010.05890.476623
17-0.048471-0.37550.354325
180.0534280.41380.34023
19-0.021525-0.16670.43407
200.0102330.07930.468543
21-0.005438-0.04210.483271
22-0.084954-0.65810.25651
23-0.074014-0.57330.284288
240.1711111.32540.095028
250.1436331.11260.135163
26-0.299823-2.32240.01181
270.1007470.78040.219116
280.0965770.74810.228667
29-0.11956-0.92610.17905
300.037370.28950.386612
310.1567071.21390.114781
32-0.159253-1.23360.111087
330.0292710.22670.410702
340.0683570.52950.299208
35-0.216907-1.68020.049064
360.1661821.28720.101477
370.088030.68190.248971
38-0.262742-2.03520.023128
390.1350021.04570.149943
400.0503480.390.348961
41-0.135792-1.05180.148546
420.1269420.98330.164707
430.0715050.55390.290862
44-0.162938-1.26210.105897
450.1163670.90140.185496
46-0.053963-0.4180.338722
47-0.08655-0.67040.252584
480.1313711.01760.156479
49-0.034921-0.27050.393855
50-0.085639-0.66340.254821
510.0409540.31720.376085
52-0.023051-0.17850.429447
53-0.034111-0.26420.396257
540.0519990.40280.344269
55-0.029854-0.23120.408956
56-0.008386-0.0650.474212
570.0387820.30040.382453
58-0.030752-0.23820.406267
590.0018720.01450.494238
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.332441 & -2.5751 & 0.006253 \tabularnewline
2 & -0.269029 & -2.0839 & 0.020718 \tabularnewline
3 & 0.31775 & 2.4613 & 0.008369 \tabularnewline
4 & -0.099855 & -0.7735 & 0.22114 \tabularnewline
5 & -0.108045 & -0.8369 & 0.202981 \tabularnewline
6 & 0.270951 & 2.0988 & 0.020027 \tabularnewline
7 & -0.251439 & -1.9476 & 0.028071 \tabularnewline
8 & 0.032479 & 0.2516 & 0.401112 \tabularnewline
9 & 0.245239 & 1.8996 & 0.031147 \tabularnewline
10 & -0.380371 & -2.9463 & 0.002286 \tabularnewline
11 & -0.082853 & -0.6418 & 0.26173 \tabularnewline
12 & 0.497202 & 3.8513 & 0.000144 \tabularnewline
13 & -0.206086 & -1.5963 & 0.057834 \tabularnewline
14 & -0.170625 & -1.3217 & 0.09565 \tabularnewline
15 & 0.121374 & 0.9402 & 0.175452 \tabularnewline
16 & 0.007601 & 0.0589 & 0.476623 \tabularnewline
17 & -0.048471 & -0.3755 & 0.354325 \tabularnewline
18 & 0.053428 & 0.4138 & 0.34023 \tabularnewline
19 & -0.021525 & -0.1667 & 0.43407 \tabularnewline
20 & 0.010233 & 0.0793 & 0.468543 \tabularnewline
21 & -0.005438 & -0.0421 & 0.483271 \tabularnewline
22 & -0.084954 & -0.6581 & 0.25651 \tabularnewline
23 & -0.074014 & -0.5733 & 0.284288 \tabularnewline
24 & 0.171111 & 1.3254 & 0.095028 \tabularnewline
25 & 0.143633 & 1.1126 & 0.135163 \tabularnewline
26 & -0.299823 & -2.3224 & 0.01181 \tabularnewline
27 & 0.100747 & 0.7804 & 0.219116 \tabularnewline
28 & 0.096577 & 0.7481 & 0.228667 \tabularnewline
29 & -0.11956 & -0.9261 & 0.17905 \tabularnewline
30 & 0.03737 & 0.2895 & 0.386612 \tabularnewline
31 & 0.156707 & 1.2139 & 0.114781 \tabularnewline
32 & -0.159253 & -1.2336 & 0.111087 \tabularnewline
33 & 0.029271 & 0.2267 & 0.410702 \tabularnewline
34 & 0.068357 & 0.5295 & 0.299208 \tabularnewline
35 & -0.216907 & -1.6802 & 0.049064 \tabularnewline
36 & 0.166182 & 1.2872 & 0.101477 \tabularnewline
37 & 0.08803 & 0.6819 & 0.248971 \tabularnewline
38 & -0.262742 & -2.0352 & 0.023128 \tabularnewline
39 & 0.135002 & 1.0457 & 0.149943 \tabularnewline
40 & 0.050348 & 0.39 & 0.348961 \tabularnewline
41 & -0.135792 & -1.0518 & 0.148546 \tabularnewline
42 & 0.126942 & 0.9833 & 0.164707 \tabularnewline
43 & 0.071505 & 0.5539 & 0.290862 \tabularnewline
44 & -0.162938 & -1.2621 & 0.105897 \tabularnewline
45 & 0.116367 & 0.9014 & 0.185496 \tabularnewline
46 & -0.053963 & -0.418 & 0.338722 \tabularnewline
47 & -0.08655 & -0.6704 & 0.252584 \tabularnewline
48 & 0.131371 & 1.0176 & 0.156479 \tabularnewline
49 & -0.034921 & -0.2705 & 0.393855 \tabularnewline
50 & -0.085639 & -0.6634 & 0.254821 \tabularnewline
51 & 0.040954 & 0.3172 & 0.376085 \tabularnewline
52 & -0.023051 & -0.1785 & 0.429447 \tabularnewline
53 & -0.034111 & -0.2642 & 0.396257 \tabularnewline
54 & 0.051999 & 0.4028 & 0.344269 \tabularnewline
55 & -0.029854 & -0.2312 & 0.408956 \tabularnewline
56 & -0.008386 & -0.065 & 0.474212 \tabularnewline
57 & 0.038782 & 0.3004 & 0.382453 \tabularnewline
58 & -0.030752 & -0.2382 & 0.406267 \tabularnewline
59 & 0.001872 & 0.0145 & 0.494238 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71317&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]-0.332441[/C][C]-2.5751[/C][C]0.006253[/C][/ROW]
[ROW][C]2[/C][C]-0.269029[/C][C]-2.0839[/C][C]0.020718[/C][/ROW]
[ROW][C]3[/C][C]0.31775[/C][C]2.4613[/C][C]0.008369[/C][/ROW]
[ROW][C]4[/C][C]-0.099855[/C][C]-0.7735[/C][C]0.22114[/C][/ROW]
[ROW][C]5[/C][C]-0.108045[/C][C]-0.8369[/C][C]0.202981[/C][/ROW]
[ROW][C]6[/C][C]0.270951[/C][C]2.0988[/C][C]0.020027[/C][/ROW]
[ROW][C]7[/C][C]-0.251439[/C][C]-1.9476[/C][C]0.028071[/C][/ROW]
[ROW][C]8[/C][C]0.032479[/C][C]0.2516[/C][C]0.401112[/C][/ROW]
[ROW][C]9[/C][C]0.245239[/C][C]1.8996[/C][C]0.031147[/C][/ROW]
[ROW][C]10[/C][C]-0.380371[/C][C]-2.9463[/C][C]0.002286[/C][/ROW]
[ROW][C]11[/C][C]-0.082853[/C][C]-0.6418[/C][C]0.26173[/C][/ROW]
[ROW][C]12[/C][C]0.497202[/C][C]3.8513[/C][C]0.000144[/C][/ROW]
[ROW][C]13[/C][C]-0.206086[/C][C]-1.5963[/C][C]0.057834[/C][/ROW]
[ROW][C]14[/C][C]-0.170625[/C][C]-1.3217[/C][C]0.09565[/C][/ROW]
[ROW][C]15[/C][C]0.121374[/C][C]0.9402[/C][C]0.175452[/C][/ROW]
[ROW][C]16[/C][C]0.007601[/C][C]0.0589[/C][C]0.476623[/C][/ROW]
[ROW][C]17[/C][C]-0.048471[/C][C]-0.3755[/C][C]0.354325[/C][/ROW]
[ROW][C]18[/C][C]0.053428[/C][C]0.4138[/C][C]0.34023[/C][/ROW]
[ROW][C]19[/C][C]-0.021525[/C][C]-0.1667[/C][C]0.43407[/C][/ROW]
[ROW][C]20[/C][C]0.010233[/C][C]0.0793[/C][C]0.468543[/C][/ROW]
[ROW][C]21[/C][C]-0.005438[/C][C]-0.0421[/C][C]0.483271[/C][/ROW]
[ROW][C]22[/C][C]-0.084954[/C][C]-0.6581[/C][C]0.25651[/C][/ROW]
[ROW][C]23[/C][C]-0.074014[/C][C]-0.5733[/C][C]0.284288[/C][/ROW]
[ROW][C]24[/C][C]0.171111[/C][C]1.3254[/C][C]0.095028[/C][/ROW]
[ROW][C]25[/C][C]0.143633[/C][C]1.1126[/C][C]0.135163[/C][/ROW]
[ROW][C]26[/C][C]-0.299823[/C][C]-2.3224[/C][C]0.01181[/C][/ROW]
[ROW][C]27[/C][C]0.100747[/C][C]0.7804[/C][C]0.219116[/C][/ROW]
[ROW][C]28[/C][C]0.096577[/C][C]0.7481[/C][C]0.228667[/C][/ROW]
[ROW][C]29[/C][C]-0.11956[/C][C]-0.9261[/C][C]0.17905[/C][/ROW]
[ROW][C]30[/C][C]0.03737[/C][C]0.2895[/C][C]0.386612[/C][/ROW]
[ROW][C]31[/C][C]0.156707[/C][C]1.2139[/C][C]0.114781[/C][/ROW]
[ROW][C]32[/C][C]-0.159253[/C][C]-1.2336[/C][C]0.111087[/C][/ROW]
[ROW][C]33[/C][C]0.029271[/C][C]0.2267[/C][C]0.410702[/C][/ROW]
[ROW][C]34[/C][C]0.068357[/C][C]0.5295[/C][C]0.299208[/C][/ROW]
[ROW][C]35[/C][C]-0.216907[/C][C]-1.6802[/C][C]0.049064[/C][/ROW]
[ROW][C]36[/C][C]0.166182[/C][C]1.2872[/C][C]0.101477[/C][/ROW]
[ROW][C]37[/C][C]0.08803[/C][C]0.6819[/C][C]0.248971[/C][/ROW]
[ROW][C]38[/C][C]-0.262742[/C][C]-2.0352[/C][C]0.023128[/C][/ROW]
[ROW][C]39[/C][C]0.135002[/C][C]1.0457[/C][C]0.149943[/C][/ROW]
[ROW][C]40[/C][C]0.050348[/C][C]0.39[/C][C]0.348961[/C][/ROW]
[ROW][C]41[/C][C]-0.135792[/C][C]-1.0518[/C][C]0.148546[/C][/ROW]
[ROW][C]42[/C][C]0.126942[/C][C]0.9833[/C][C]0.164707[/C][/ROW]
[ROW][C]43[/C][C]0.071505[/C][C]0.5539[/C][C]0.290862[/C][/ROW]
[ROW][C]44[/C][C]-0.162938[/C][C]-1.2621[/C][C]0.105897[/C][/ROW]
[ROW][C]45[/C][C]0.116367[/C][C]0.9014[/C][C]0.185496[/C][/ROW]
[ROW][C]46[/C][C]-0.053963[/C][C]-0.418[/C][C]0.338722[/C][/ROW]
[ROW][C]47[/C][C]-0.08655[/C][C]-0.6704[/C][C]0.252584[/C][/ROW]
[ROW][C]48[/C][C]0.131371[/C][C]1.0176[/C][C]0.156479[/C][/ROW]
[ROW][C]49[/C][C]-0.034921[/C][C]-0.2705[/C][C]0.393855[/C][/ROW]
[ROW][C]50[/C][C]-0.085639[/C][C]-0.6634[/C][C]0.254821[/C][/ROW]
[ROW][C]51[/C][C]0.040954[/C][C]0.3172[/C][C]0.376085[/C][/ROW]
[ROW][C]52[/C][C]-0.023051[/C][C]-0.1785[/C][C]0.429447[/C][/ROW]
[ROW][C]53[/C][C]-0.034111[/C][C]-0.2642[/C][C]0.396257[/C][/ROW]
[ROW][C]54[/C][C]0.051999[/C][C]0.4028[/C][C]0.344269[/C][/ROW]
[ROW][C]55[/C][C]-0.029854[/C][C]-0.2312[/C][C]0.408956[/C][/ROW]
[ROW][C]56[/C][C]-0.008386[/C][C]-0.065[/C][C]0.474212[/C][/ROW]
[ROW][C]57[/C][C]0.038782[/C][C]0.3004[/C][C]0.382453[/C][/ROW]
[ROW][C]58[/C][C]-0.030752[/C][C]-0.2382[/C][C]0.406267[/C][/ROW]
[ROW][C]59[/C][C]0.001872[/C][C]0.0145[/C][C]0.494238[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71317&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71317&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
1-0.332441-2.57510.006253
2-0.269029-2.08390.020718
30.317752.46130.008369
4-0.099855-0.77350.22114
5-0.108045-0.83690.202981
60.2709512.09880.020027
7-0.251439-1.94760.028071
80.0324790.25160.401112
90.2452391.89960.031147
10-0.380371-2.94630.002286
11-0.082853-0.64180.26173
120.4972023.85130.000144
13-0.206086-1.59630.057834
14-0.170625-1.32170.09565
150.1213740.94020.175452
160.0076010.05890.476623
17-0.048471-0.37550.354325
180.0534280.41380.34023
19-0.021525-0.16670.43407
200.0102330.07930.468543
21-0.005438-0.04210.483271
22-0.084954-0.65810.25651
23-0.074014-0.57330.284288
240.1711111.32540.095028
250.1436331.11260.135163
26-0.299823-2.32240.01181
270.1007470.78040.219116
280.0965770.74810.228667
29-0.11956-0.92610.17905
300.037370.28950.386612
310.1567071.21390.114781
32-0.159253-1.23360.111087
330.0292710.22670.410702
340.0683570.52950.299208
35-0.216907-1.68020.049064
360.1661821.28720.101477
370.088030.68190.248971
38-0.262742-2.03520.023128
390.1350021.04570.149943
400.0503480.390.348961
41-0.135792-1.05180.148546
420.1269420.98330.164707
430.0715050.55390.290862
44-0.162938-1.26210.105897
450.1163670.90140.185496
46-0.053963-0.4180.338722
47-0.08655-0.67040.252584
480.1313711.01760.156479
49-0.034921-0.27050.393855
50-0.085639-0.66340.254821
510.0409540.31720.376085
52-0.023051-0.17850.429447
53-0.034111-0.26420.396257
540.0519990.40280.344269
55-0.029854-0.23120.408956
56-0.008386-0.0650.474212
570.0387820.30040.382453
58-0.030752-0.23820.406267
590.0018720.01450.494238
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.332441-2.57510.006253
2-0.426704-3.30520.000802
30.0663850.51420.304496
4-0.058544-0.45350.325919
5-0.038629-0.29920.382905
60.1948961.50970.06819
7-0.142303-1.10230.137372
80.0457340.35430.362194
90.1264160.97920.165704
10-0.247424-1.91650.030032
11-0.300965-2.33130.011558
120.2092381.62070.055158
130.1835661.42190.080117
14-0.007141-0.05530.478036
15-0.199775-1.54740.063507
160.0954920.73970.231191
170.0006720.00520.497932
18-0.154835-1.19930.117555
190.1450611.12360.132822
200.0401020.31060.378579
21-0.259596-2.01080.024422
22-0.004451-0.03450.486305
230.0752110.58260.281179
24-0.13304-1.03050.153451
250.1595981.23620.110594
260.035340.27370.392611
270.110660.85720.197381
28-0.200447-1.55270.062883
290.0584730.45290.326116
300.1081880.8380.202674
31-0.041746-0.32340.373773
32-0.023068-0.17870.429393
330.0780910.60490.273766
340.0512410.39690.346422
35-0.166461-1.28940.101103
360.0104640.08110.467833
37-0.063428-0.49130.3125
38-0.091105-0.70570.241554
391.7e-051e-040.499949
400.1471211.13960.129493
410.0217120.16820.433502
42-0.004633-0.03590.485747
430.0773640.59930.275627
44-0.010036-0.07770.469147
45-0.024939-0.19320.423738
46-0.102093-0.79080.216085
470.0301070.23320.408196
48-0.029119-0.22560.411158
49-0.087398-0.6770.25051
50-0.019796-0.15330.439323
510.0012420.00960.496178
52-0.045498-0.35240.362877
530.0014370.01110.495577
54-0.058606-0.4540.325747
55-0.059186-0.45850.32414
56-0.104748-0.81140.210179
570.0496850.38490.350853
580.0817320.63310.26454
59-0.088605-0.68630.247573
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.332441 & -2.5751 & 0.006253 \tabularnewline
2 & -0.426704 & -3.3052 & 0.000802 \tabularnewline
3 & 0.066385 & 0.5142 & 0.304496 \tabularnewline
4 & -0.058544 & -0.4535 & 0.325919 \tabularnewline
5 & -0.038629 & -0.2992 & 0.382905 \tabularnewline
6 & 0.194896 & 1.5097 & 0.06819 \tabularnewline
7 & -0.142303 & -1.1023 & 0.137372 \tabularnewline
8 & 0.045734 & 0.3543 & 0.362194 \tabularnewline
9 & 0.126416 & 0.9792 & 0.165704 \tabularnewline
10 & -0.247424 & -1.9165 & 0.030032 \tabularnewline
11 & -0.300965 & -2.3313 & 0.011558 \tabularnewline
12 & 0.209238 & 1.6207 & 0.055158 \tabularnewline
13 & 0.183566 & 1.4219 & 0.080117 \tabularnewline
14 & -0.007141 & -0.0553 & 0.478036 \tabularnewline
15 & -0.199775 & -1.5474 & 0.063507 \tabularnewline
16 & 0.095492 & 0.7397 & 0.231191 \tabularnewline
17 & 0.000672 & 0.0052 & 0.497932 \tabularnewline
18 & -0.154835 & -1.1993 & 0.117555 \tabularnewline
19 & 0.145061 & 1.1236 & 0.132822 \tabularnewline
20 & 0.040102 & 0.3106 & 0.378579 \tabularnewline
21 & -0.259596 & -2.0108 & 0.024422 \tabularnewline
22 & -0.004451 & -0.0345 & 0.486305 \tabularnewline
23 & 0.075211 & 0.5826 & 0.281179 \tabularnewline
24 & -0.13304 & -1.0305 & 0.153451 \tabularnewline
25 & 0.159598 & 1.2362 & 0.110594 \tabularnewline
26 & 0.03534 & 0.2737 & 0.392611 \tabularnewline
27 & 0.11066 & 0.8572 & 0.197381 \tabularnewline
28 & -0.200447 & -1.5527 & 0.062883 \tabularnewline
29 & 0.058473 & 0.4529 & 0.326116 \tabularnewline
30 & 0.108188 & 0.838 & 0.202674 \tabularnewline
31 & -0.041746 & -0.3234 & 0.373773 \tabularnewline
32 & -0.023068 & -0.1787 & 0.429393 \tabularnewline
33 & 0.078091 & 0.6049 & 0.273766 \tabularnewline
34 & 0.051241 & 0.3969 & 0.346422 \tabularnewline
35 & -0.166461 & -1.2894 & 0.101103 \tabularnewline
36 & 0.010464 & 0.0811 & 0.467833 \tabularnewline
37 & -0.063428 & -0.4913 & 0.3125 \tabularnewline
38 & -0.091105 & -0.7057 & 0.241554 \tabularnewline
39 & 1.7e-05 & 1e-04 & 0.499949 \tabularnewline
40 & 0.147121 & 1.1396 & 0.129493 \tabularnewline
41 & 0.021712 & 0.1682 & 0.433502 \tabularnewline
42 & -0.004633 & -0.0359 & 0.485747 \tabularnewline
43 & 0.077364 & 0.5993 & 0.275627 \tabularnewline
44 & -0.010036 & -0.0777 & 0.469147 \tabularnewline
45 & -0.024939 & -0.1932 & 0.423738 \tabularnewline
46 & -0.102093 & -0.7908 & 0.216085 \tabularnewline
47 & 0.030107 & 0.2332 & 0.408196 \tabularnewline
48 & -0.029119 & -0.2256 & 0.411158 \tabularnewline
49 & -0.087398 & -0.677 & 0.25051 \tabularnewline
50 & -0.019796 & -0.1533 & 0.439323 \tabularnewline
51 & 0.001242 & 0.0096 & 0.496178 \tabularnewline
52 & -0.045498 & -0.3524 & 0.362877 \tabularnewline
53 & 0.001437 & 0.0111 & 0.495577 \tabularnewline
54 & -0.058606 & -0.454 & 0.325747 \tabularnewline
55 & -0.059186 & -0.4585 & 0.32414 \tabularnewline
56 & -0.104748 & -0.8114 & 0.210179 \tabularnewline
57 & 0.049685 & 0.3849 & 0.350853 \tabularnewline
58 & 0.081732 & 0.6331 & 0.26454 \tabularnewline
59 & -0.088605 & -0.6863 & 0.247573 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71317&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]-0.332441[/C][C]-2.5751[/C][C]0.006253[/C][/ROW]
[ROW][C]2[/C][C]-0.426704[/C][C]-3.3052[/C][C]0.000802[/C][/ROW]
[ROW][C]3[/C][C]0.066385[/C][C]0.5142[/C][C]0.304496[/C][/ROW]
[ROW][C]4[/C][C]-0.058544[/C][C]-0.4535[/C][C]0.325919[/C][/ROW]
[ROW][C]5[/C][C]-0.038629[/C][C]-0.2992[/C][C]0.382905[/C][/ROW]
[ROW][C]6[/C][C]0.194896[/C][C]1.5097[/C][C]0.06819[/C][/ROW]
[ROW][C]7[/C][C]-0.142303[/C][C]-1.1023[/C][C]0.137372[/C][/ROW]
[ROW][C]8[/C][C]0.045734[/C][C]0.3543[/C][C]0.362194[/C][/ROW]
[ROW][C]9[/C][C]0.126416[/C][C]0.9792[/C][C]0.165704[/C][/ROW]
[ROW][C]10[/C][C]-0.247424[/C][C]-1.9165[/C][C]0.030032[/C][/ROW]
[ROW][C]11[/C][C]-0.300965[/C][C]-2.3313[/C][C]0.011558[/C][/ROW]
[ROW][C]12[/C][C]0.209238[/C][C]1.6207[/C][C]0.055158[/C][/ROW]
[ROW][C]13[/C][C]0.183566[/C][C]1.4219[/C][C]0.080117[/C][/ROW]
[ROW][C]14[/C][C]-0.007141[/C][C]-0.0553[/C][C]0.478036[/C][/ROW]
[ROW][C]15[/C][C]-0.199775[/C][C]-1.5474[/C][C]0.063507[/C][/ROW]
[ROW][C]16[/C][C]0.095492[/C][C]0.7397[/C][C]0.231191[/C][/ROW]
[ROW][C]17[/C][C]0.000672[/C][C]0.0052[/C][C]0.497932[/C][/ROW]
[ROW][C]18[/C][C]-0.154835[/C][C]-1.1993[/C][C]0.117555[/C][/ROW]
[ROW][C]19[/C][C]0.145061[/C][C]1.1236[/C][C]0.132822[/C][/ROW]
[ROW][C]20[/C][C]0.040102[/C][C]0.3106[/C][C]0.378579[/C][/ROW]
[ROW][C]21[/C][C]-0.259596[/C][C]-2.0108[/C][C]0.024422[/C][/ROW]
[ROW][C]22[/C][C]-0.004451[/C][C]-0.0345[/C][C]0.486305[/C][/ROW]
[ROW][C]23[/C][C]0.075211[/C][C]0.5826[/C][C]0.281179[/C][/ROW]
[ROW][C]24[/C][C]-0.13304[/C][C]-1.0305[/C][C]0.153451[/C][/ROW]
[ROW][C]25[/C][C]0.159598[/C][C]1.2362[/C][C]0.110594[/C][/ROW]
[ROW][C]26[/C][C]0.03534[/C][C]0.2737[/C][C]0.392611[/C][/ROW]
[ROW][C]27[/C][C]0.11066[/C][C]0.8572[/C][C]0.197381[/C][/ROW]
[ROW][C]28[/C][C]-0.200447[/C][C]-1.5527[/C][C]0.062883[/C][/ROW]
[ROW][C]29[/C][C]0.058473[/C][C]0.4529[/C][C]0.326116[/C][/ROW]
[ROW][C]30[/C][C]0.108188[/C][C]0.838[/C][C]0.202674[/C][/ROW]
[ROW][C]31[/C][C]-0.041746[/C][C]-0.3234[/C][C]0.373773[/C][/ROW]
[ROW][C]32[/C][C]-0.023068[/C][C]-0.1787[/C][C]0.429393[/C][/ROW]
[ROW][C]33[/C][C]0.078091[/C][C]0.6049[/C][C]0.273766[/C][/ROW]
[ROW][C]34[/C][C]0.051241[/C][C]0.3969[/C][C]0.346422[/C][/ROW]
[ROW][C]35[/C][C]-0.166461[/C][C]-1.2894[/C][C]0.101103[/C][/ROW]
[ROW][C]36[/C][C]0.010464[/C][C]0.0811[/C][C]0.467833[/C][/ROW]
[ROW][C]37[/C][C]-0.063428[/C][C]-0.4913[/C][C]0.3125[/C][/ROW]
[ROW][C]38[/C][C]-0.091105[/C][C]-0.7057[/C][C]0.241554[/C][/ROW]
[ROW][C]39[/C][C]1.7e-05[/C][C]1e-04[/C][C]0.499949[/C][/ROW]
[ROW][C]40[/C][C]0.147121[/C][C]1.1396[/C][C]0.129493[/C][/ROW]
[ROW][C]41[/C][C]0.021712[/C][C]0.1682[/C][C]0.433502[/C][/ROW]
[ROW][C]42[/C][C]-0.004633[/C][C]-0.0359[/C][C]0.485747[/C][/ROW]
[ROW][C]43[/C][C]0.077364[/C][C]0.5993[/C][C]0.275627[/C][/ROW]
[ROW][C]44[/C][C]-0.010036[/C][C]-0.0777[/C][C]0.469147[/C][/ROW]
[ROW][C]45[/C][C]-0.024939[/C][C]-0.1932[/C][C]0.423738[/C][/ROW]
[ROW][C]46[/C][C]-0.102093[/C][C]-0.7908[/C][C]0.216085[/C][/ROW]
[ROW][C]47[/C][C]0.030107[/C][C]0.2332[/C][C]0.408196[/C][/ROW]
[ROW][C]48[/C][C]-0.029119[/C][C]-0.2256[/C][C]0.411158[/C][/ROW]
[ROW][C]49[/C][C]-0.087398[/C][C]-0.677[/C][C]0.25051[/C][/ROW]
[ROW][C]50[/C][C]-0.019796[/C][C]-0.1533[/C][C]0.439323[/C][/ROW]
[ROW][C]51[/C][C]0.001242[/C][C]0.0096[/C][C]0.496178[/C][/ROW]
[ROW][C]52[/C][C]-0.045498[/C][C]-0.3524[/C][C]0.362877[/C][/ROW]
[ROW][C]53[/C][C]0.001437[/C][C]0.0111[/C][C]0.495577[/C][/ROW]
[ROW][C]54[/C][C]-0.058606[/C][C]-0.454[/C][C]0.325747[/C][/ROW]
[ROW][C]55[/C][C]-0.059186[/C][C]-0.4585[/C][C]0.32414[/C][/ROW]
[ROW][C]56[/C][C]-0.104748[/C][C]-0.8114[/C][C]0.210179[/C][/ROW]
[ROW][C]57[/C][C]0.049685[/C][C]0.3849[/C][C]0.350853[/C][/ROW]
[ROW][C]58[/C][C]0.081732[/C][C]0.6331[/C][C]0.26454[/C][/ROW]
[ROW][C]59[/C][C]-0.088605[/C][C]-0.6863[/C][C]0.247573[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71317&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71317&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
1-0.332441-2.57510.006253
2-0.426704-3.30520.000802
30.0663850.51420.304496
4-0.058544-0.45350.325919
5-0.038629-0.29920.382905
60.1948961.50970.06819
7-0.142303-1.10230.137372
80.0457340.35430.362194
90.1264160.97920.165704
10-0.247424-1.91650.030032
11-0.300965-2.33130.011558
120.2092381.62070.055158
130.1835661.42190.080117
14-0.007141-0.05530.478036
15-0.199775-1.54740.063507
160.0954920.73970.231191
170.0006720.00520.497932
18-0.154835-1.19930.117555
190.1450611.12360.132822
200.0401020.31060.378579
21-0.259596-2.01080.024422
22-0.004451-0.03450.486305
230.0752110.58260.281179
24-0.13304-1.03050.153451
250.1595981.23620.110594
260.035340.27370.392611
270.110660.85720.197381
28-0.200447-1.55270.062883
290.0584730.45290.326116
300.1081880.8380.202674
31-0.041746-0.32340.373773
32-0.023068-0.17870.429393
330.0780910.60490.273766
340.0512410.39690.346422
35-0.166461-1.28940.101103
360.0104640.08110.467833
37-0.063428-0.49130.3125
38-0.091105-0.70570.241554
391.7e-051e-040.499949
400.1471211.13960.129493
410.0217120.16820.433502
42-0.004633-0.03590.485747
430.0773640.59930.275627
44-0.010036-0.07770.469147
45-0.024939-0.19320.423738
46-0.102093-0.79080.216085
470.0301070.23320.408196
48-0.029119-0.22560.411158
49-0.087398-0.6770.25051
50-0.019796-0.15330.439323
510.0012420.00960.496178
52-0.045498-0.35240.362877
530.0014370.01110.495577
54-0.058606-0.4540.325747
55-0.059186-0.45850.32414
56-0.104748-0.81140.210179
570.0496850.38490.350853
580.0817320.63310.26454
59-0.088605-0.68630.247573
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')