Free Statistics

of Irreproducible Research!

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 computationThu, 31 Dec 2009 02:13:40 -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/31/t1262250894gi34us6eezid9lg.htm/, Retrieved Thu, 02 May 2024 06:20:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71422, Retrieved Thu, 02 May 2024 06:20:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF d=1 D=0] [2008-12-19 14:55:56] [7458e879e85b911182071700fff19fbd]
-       [(Partial) Autocorrelation Function] [ACF d=1 D=0] [2008-12-19 15:23:58] [7458e879e85b911182071700fff19fbd]
- RMPD      [(Partial) Autocorrelation Function] [PACF d=1 D=0] [2009-12-31 09:13:40] [461be1b9ba57453336a7ea3097b7d5b5] [Current]
Feedback Forum

Post a new message
Dataseries X:
40.22
44.23
45.85
53.38
53.26
51.8
55.3
57.81
63.96
63.77
59.15
56.12
57.42
63.52
61.71
63.01
68.18
72.03
69.75
74.41
74.33
64.24
60.03
59.44
62.5
55.04
58.34
61.92
67.65
67.68
70.3
75.26
71.44
76.36
81.71
92.6
90.6
92.23
94.09
102.79
109.65
124.05
132.69
135.81
116.07
101.42
75.73
55.48
43.8
45.29
44.01
47.48
51.07
57.84
69.04
65.61
72.87
68.41
73.25
77.43




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=71422&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=71422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71422&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
10.4332693.3280.000755
20.3143832.41480.009431
30.070040.5380.296305
4-0.001932-0.01480.494105
5-0.166499-1.27890.102969
6-0.335677-2.57840.006221
7-0.159928-1.22840.112082
8-0.234166-1.79870.038594
9-0.138898-1.06690.145182
10-0.042953-0.32990.371312
110.0533210.40960.341802
12-0.06707-0.51520.304178
13-0.098335-0.75530.226528
14-0.031316-0.24050.405371
150.0079140.06080.475866
16-0.016573-0.12730.449567
17-0.101428-0.77910.219523
18-0.06043-0.46420.322117
19-0.071825-0.55170.291619
20-0.102278-0.78560.21762
210.0282350.21690.414526
220.0261790.20110.420661
230.165431.27070.104413
240.0286390.220.413322
250.2287911.75740.042021
260.1745181.34050.092611
270.1187320.9120.182742
28-0.005229-0.04020.484048
29-0.093025-0.71450.238855
30-0.026362-0.20250.420115
31-0.157558-1.21020.115509
32-0.010838-0.08320.466968
33-0.045447-0.34910.364133
340.0224170.17220.431941
354e-0600.499987
360.0918830.70580.241556
370.0914140.70220.242669
380.0268870.20650.418548
39-0.028636-0.220.413331
40-0.060694-0.46620.321396
41-0.048559-0.3730.355246
42-0.083434-0.64090.262045
43-0.079936-0.6140.270788
44-0.156867-1.20490.116522
45-0.127136-0.97660.166389
46-0.033022-0.25360.400326
47-0.066059-0.50740.30688
480.0357610.27470.392258
49-0.019716-0.15140.440071
500.0756770.58130.281631
510.0722260.55480.290573
520.0298150.2290.409824
530.0607650.46670.321202
54-0.034423-0.26440.396192
550.0291250.22370.411876
56-0.000271-0.00210.499174
570.0132080.10150.459766
580.0078890.06060.475943
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.433269 & 3.328 & 0.000755 \tabularnewline
2 & 0.314383 & 2.4148 & 0.009431 \tabularnewline
3 & 0.07004 & 0.538 & 0.296305 \tabularnewline
4 & -0.001932 & -0.0148 & 0.494105 \tabularnewline
5 & -0.166499 & -1.2789 & 0.102969 \tabularnewline
6 & -0.335677 & -2.5784 & 0.006221 \tabularnewline
7 & -0.159928 & -1.2284 & 0.112082 \tabularnewline
8 & -0.234166 & -1.7987 & 0.038594 \tabularnewline
9 & -0.138898 & -1.0669 & 0.145182 \tabularnewline
10 & -0.042953 & -0.3299 & 0.371312 \tabularnewline
11 & 0.053321 & 0.4096 & 0.341802 \tabularnewline
12 & -0.06707 & -0.5152 & 0.304178 \tabularnewline
13 & -0.098335 & -0.7553 & 0.226528 \tabularnewline
14 & -0.031316 & -0.2405 & 0.405371 \tabularnewline
15 & 0.007914 & 0.0608 & 0.475866 \tabularnewline
16 & -0.016573 & -0.1273 & 0.449567 \tabularnewline
17 & -0.101428 & -0.7791 & 0.219523 \tabularnewline
18 & -0.06043 & -0.4642 & 0.322117 \tabularnewline
19 & -0.071825 & -0.5517 & 0.291619 \tabularnewline
20 & -0.102278 & -0.7856 & 0.21762 \tabularnewline
21 & 0.028235 & 0.2169 & 0.414526 \tabularnewline
22 & 0.026179 & 0.2011 & 0.420661 \tabularnewline
23 & 0.16543 & 1.2707 & 0.104413 \tabularnewline
24 & 0.028639 & 0.22 & 0.413322 \tabularnewline
25 & 0.228791 & 1.7574 & 0.042021 \tabularnewline
26 & 0.174518 & 1.3405 & 0.092611 \tabularnewline
27 & 0.118732 & 0.912 & 0.182742 \tabularnewline
28 & -0.005229 & -0.0402 & 0.484048 \tabularnewline
29 & -0.093025 & -0.7145 & 0.238855 \tabularnewline
30 & -0.026362 & -0.2025 & 0.420115 \tabularnewline
31 & -0.157558 & -1.2102 & 0.115509 \tabularnewline
32 & -0.010838 & -0.0832 & 0.466968 \tabularnewline
33 & -0.045447 & -0.3491 & 0.364133 \tabularnewline
34 & 0.022417 & 0.1722 & 0.431941 \tabularnewline
35 & 4e-06 & 0 & 0.499987 \tabularnewline
36 & 0.091883 & 0.7058 & 0.241556 \tabularnewline
37 & 0.091414 & 0.7022 & 0.242669 \tabularnewline
38 & 0.026887 & 0.2065 & 0.418548 \tabularnewline
39 & -0.028636 & -0.22 & 0.413331 \tabularnewline
40 & -0.060694 & -0.4662 & 0.321396 \tabularnewline
41 & -0.048559 & -0.373 & 0.355246 \tabularnewline
42 & -0.083434 & -0.6409 & 0.262045 \tabularnewline
43 & -0.079936 & -0.614 & 0.270788 \tabularnewline
44 & -0.156867 & -1.2049 & 0.116522 \tabularnewline
45 & -0.127136 & -0.9766 & 0.166389 \tabularnewline
46 & -0.033022 & -0.2536 & 0.400326 \tabularnewline
47 & -0.066059 & -0.5074 & 0.30688 \tabularnewline
48 & 0.035761 & 0.2747 & 0.392258 \tabularnewline
49 & -0.019716 & -0.1514 & 0.440071 \tabularnewline
50 & 0.075677 & 0.5813 & 0.281631 \tabularnewline
51 & 0.072226 & 0.5548 & 0.290573 \tabularnewline
52 & 0.029815 & 0.229 & 0.409824 \tabularnewline
53 & 0.060765 & 0.4667 & 0.321202 \tabularnewline
54 & -0.034423 & -0.2644 & 0.396192 \tabularnewline
55 & 0.029125 & 0.2237 & 0.411876 \tabularnewline
56 & -0.000271 & -0.0021 & 0.499174 \tabularnewline
57 & 0.013208 & 0.1015 & 0.459766 \tabularnewline
58 & 0.007889 & 0.0606 & 0.475943 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71422&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]0.433269[/C][C]3.328[/C][C]0.000755[/C][/ROW]
[ROW][C]2[/C][C]0.314383[/C][C]2.4148[/C][C]0.009431[/C][/ROW]
[ROW][C]3[/C][C]0.07004[/C][C]0.538[/C][C]0.296305[/C][/ROW]
[ROW][C]4[/C][C]-0.001932[/C][C]-0.0148[/C][C]0.494105[/C][/ROW]
[ROW][C]5[/C][C]-0.166499[/C][C]-1.2789[/C][C]0.102969[/C][/ROW]
[ROW][C]6[/C][C]-0.335677[/C][C]-2.5784[/C][C]0.006221[/C][/ROW]
[ROW][C]7[/C][C]-0.159928[/C][C]-1.2284[/C][C]0.112082[/C][/ROW]
[ROW][C]8[/C][C]-0.234166[/C][C]-1.7987[/C][C]0.038594[/C][/ROW]
[ROW][C]9[/C][C]-0.138898[/C][C]-1.0669[/C][C]0.145182[/C][/ROW]
[ROW][C]10[/C][C]-0.042953[/C][C]-0.3299[/C][C]0.371312[/C][/ROW]
[ROW][C]11[/C][C]0.053321[/C][C]0.4096[/C][C]0.341802[/C][/ROW]
[ROW][C]12[/C][C]-0.06707[/C][C]-0.5152[/C][C]0.304178[/C][/ROW]
[ROW][C]13[/C][C]-0.098335[/C][C]-0.7553[/C][C]0.226528[/C][/ROW]
[ROW][C]14[/C][C]-0.031316[/C][C]-0.2405[/C][C]0.405371[/C][/ROW]
[ROW][C]15[/C][C]0.007914[/C][C]0.0608[/C][C]0.475866[/C][/ROW]
[ROW][C]16[/C][C]-0.016573[/C][C]-0.1273[/C][C]0.449567[/C][/ROW]
[ROW][C]17[/C][C]-0.101428[/C][C]-0.7791[/C][C]0.219523[/C][/ROW]
[ROW][C]18[/C][C]-0.06043[/C][C]-0.4642[/C][C]0.322117[/C][/ROW]
[ROW][C]19[/C][C]-0.071825[/C][C]-0.5517[/C][C]0.291619[/C][/ROW]
[ROW][C]20[/C][C]-0.102278[/C][C]-0.7856[/C][C]0.21762[/C][/ROW]
[ROW][C]21[/C][C]0.028235[/C][C]0.2169[/C][C]0.414526[/C][/ROW]
[ROW][C]22[/C][C]0.026179[/C][C]0.2011[/C][C]0.420661[/C][/ROW]
[ROW][C]23[/C][C]0.16543[/C][C]1.2707[/C][C]0.104413[/C][/ROW]
[ROW][C]24[/C][C]0.028639[/C][C]0.22[/C][C]0.413322[/C][/ROW]
[ROW][C]25[/C][C]0.228791[/C][C]1.7574[/C][C]0.042021[/C][/ROW]
[ROW][C]26[/C][C]0.174518[/C][C]1.3405[/C][C]0.092611[/C][/ROW]
[ROW][C]27[/C][C]0.118732[/C][C]0.912[/C][C]0.182742[/C][/ROW]
[ROW][C]28[/C][C]-0.005229[/C][C]-0.0402[/C][C]0.484048[/C][/ROW]
[ROW][C]29[/C][C]-0.093025[/C][C]-0.7145[/C][C]0.238855[/C][/ROW]
[ROW][C]30[/C][C]-0.026362[/C][C]-0.2025[/C][C]0.420115[/C][/ROW]
[ROW][C]31[/C][C]-0.157558[/C][C]-1.2102[/C][C]0.115509[/C][/ROW]
[ROW][C]32[/C][C]-0.010838[/C][C]-0.0832[/C][C]0.466968[/C][/ROW]
[ROW][C]33[/C][C]-0.045447[/C][C]-0.3491[/C][C]0.364133[/C][/ROW]
[ROW][C]34[/C][C]0.022417[/C][C]0.1722[/C][C]0.431941[/C][/ROW]
[ROW][C]35[/C][C]4e-06[/C][C]0[/C][C]0.499987[/C][/ROW]
[ROW][C]36[/C][C]0.091883[/C][C]0.7058[/C][C]0.241556[/C][/ROW]
[ROW][C]37[/C][C]0.091414[/C][C]0.7022[/C][C]0.242669[/C][/ROW]
[ROW][C]38[/C][C]0.026887[/C][C]0.2065[/C][C]0.418548[/C][/ROW]
[ROW][C]39[/C][C]-0.028636[/C][C]-0.22[/C][C]0.413331[/C][/ROW]
[ROW][C]40[/C][C]-0.060694[/C][C]-0.4662[/C][C]0.321396[/C][/ROW]
[ROW][C]41[/C][C]-0.048559[/C][C]-0.373[/C][C]0.355246[/C][/ROW]
[ROW][C]42[/C][C]-0.083434[/C][C]-0.6409[/C][C]0.262045[/C][/ROW]
[ROW][C]43[/C][C]-0.079936[/C][C]-0.614[/C][C]0.270788[/C][/ROW]
[ROW][C]44[/C][C]-0.156867[/C][C]-1.2049[/C][C]0.116522[/C][/ROW]
[ROW][C]45[/C][C]-0.127136[/C][C]-0.9766[/C][C]0.166389[/C][/ROW]
[ROW][C]46[/C][C]-0.033022[/C][C]-0.2536[/C][C]0.400326[/C][/ROW]
[ROW][C]47[/C][C]-0.066059[/C][C]-0.5074[/C][C]0.30688[/C][/ROW]
[ROW][C]48[/C][C]0.035761[/C][C]0.2747[/C][C]0.392258[/C][/ROW]
[ROW][C]49[/C][C]-0.019716[/C][C]-0.1514[/C][C]0.440071[/C][/ROW]
[ROW][C]50[/C][C]0.075677[/C][C]0.5813[/C][C]0.281631[/C][/ROW]
[ROW][C]51[/C][C]0.072226[/C][C]0.5548[/C][C]0.290573[/C][/ROW]
[ROW][C]52[/C][C]0.029815[/C][C]0.229[/C][C]0.409824[/C][/ROW]
[ROW][C]53[/C][C]0.060765[/C][C]0.4667[/C][C]0.321202[/C][/ROW]
[ROW][C]54[/C][C]-0.034423[/C][C]-0.2644[/C][C]0.396192[/C][/ROW]
[ROW][C]55[/C][C]0.029125[/C][C]0.2237[/C][C]0.411876[/C][/ROW]
[ROW][C]56[/C][C]-0.000271[/C][C]-0.0021[/C][C]0.499174[/C][/ROW]
[ROW][C]57[/C][C]0.013208[/C][C]0.1015[/C][C]0.459766[/C][/ROW]
[ROW][C]58[/C][C]0.007889[/C][C]0.0606[/C][C]0.475943[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=71422&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71422&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
10.4332693.3280.000755
20.3143832.41480.009431
30.070040.5380.296305
4-0.001932-0.01480.494105
5-0.166499-1.27890.102969
6-0.335677-2.57840.006221
7-0.159928-1.22840.112082
8-0.234166-1.79870.038594
9-0.138898-1.06690.145182
10-0.042953-0.32990.371312
110.0533210.40960.341802
12-0.06707-0.51520.304178
13-0.098335-0.75530.226528
14-0.031316-0.24050.405371
150.0079140.06080.475866
16-0.016573-0.12730.449567
17-0.101428-0.77910.219523
18-0.06043-0.46420.322117
19-0.071825-0.55170.291619
20-0.102278-0.78560.21762
210.0282350.21690.414526
220.0261790.20110.420661
230.165431.27070.104413
240.0286390.220.413322
250.2287911.75740.042021
260.1745181.34050.092611
270.1187320.9120.182742
28-0.005229-0.04020.484048
29-0.093025-0.71450.238855
30-0.026362-0.20250.420115
31-0.157558-1.21020.115509
32-0.010838-0.08320.466968
33-0.045447-0.34910.364133
340.0224170.17220.431941
354e-0600.499987
360.0918830.70580.241556
370.0914140.70220.242669
380.0268870.20650.418548
39-0.028636-0.220.413331
40-0.060694-0.46620.321396
41-0.048559-0.3730.355246
42-0.083434-0.64090.262045
43-0.079936-0.6140.270788
44-0.156867-1.20490.116522
45-0.127136-0.97660.166389
46-0.033022-0.25360.400326
47-0.066059-0.50740.30688
480.0357610.27470.392258
49-0.019716-0.15140.440071
500.0756770.58130.281631
510.0722260.55480.290573
520.0298150.2290.409824
530.0607650.46670.321202
54-0.034423-0.26440.396192
550.0291250.22370.411876
56-0.000271-0.00210.499174
570.0132080.10150.459766
580.0078890.06060.475943
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4332693.3280.000755
20.1559331.19770.117904
3-0.141943-1.09030.140011
4-0.042416-0.32580.372862
5-0.158813-1.21990.113685
6-0.269167-2.06750.02154
70.1638021.25820.106641
8-0.127531-0.97960.165646
9-0.05835-0.44820.327828
100.128640.98810.163568
11-0.02852-0.21910.413678
12-0.273683-2.10220.019907
13-0.023077-0.17730.429956
140.0052880.04060.483868
150.0080390.06170.475486
160.0263320.20230.420204
17-0.176631-1.35670.090019
18-0.133612-1.02630.154472
190.0157040.12060.4522
20-0.148088-1.13750.129967
210.1227790.94310.174743
220.0178690.13730.445648
230.0931780.71570.238496
24-0.157122-1.20690.116148
250.1600511.22940.111905
26-0.054713-0.42030.33791
270.0046060.03540.485948
28-0.045854-0.35220.362966
29-0.059299-0.45550.325217
300.0196360.15080.440312
310.0097530.07490.470268
320.0499340.38350.351346
330.0085060.06530.474065
34-0.008879-0.06820.472928
350.0320160.24590.4033
360.0505770.38850.349525
37-0.028559-0.21940.413562
380.0417220.32050.374872
39-0.023048-0.1770.430044
40-0.054702-0.42020.337943
410.0145320.11160.455751
420.0081940.06290.475013
43-0.032175-0.24710.402829
44-0.151995-1.16750.123853
450.0413650.31770.375905
460.0324650.24940.401971
47-0.131416-1.00940.158447
480.0170830.13120.448026
49-0.049519-0.38040.352522
50-0.016245-0.12480.450561
510.0445210.3420.366793
52-0.116171-0.89230.187922
53-0.081404-0.62530.2671
540.1079380.82910.205199
55-0.044313-0.34040.367391
560.0265690.20410.419495
57-0.093931-0.72150.236725
58-0.04305-0.33070.371032
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.433269 & 3.328 & 0.000755 \tabularnewline
2 & 0.155933 & 1.1977 & 0.117904 \tabularnewline
3 & -0.141943 & -1.0903 & 0.140011 \tabularnewline
4 & -0.042416 & -0.3258 & 0.372862 \tabularnewline
5 & -0.158813 & -1.2199 & 0.113685 \tabularnewline
6 & -0.269167 & -2.0675 & 0.02154 \tabularnewline
7 & 0.163802 & 1.2582 & 0.106641 \tabularnewline
8 & -0.127531 & -0.9796 & 0.165646 \tabularnewline
9 & -0.05835 & -0.4482 & 0.327828 \tabularnewline
10 & 0.12864 & 0.9881 & 0.163568 \tabularnewline
11 & -0.02852 & -0.2191 & 0.413678 \tabularnewline
12 & -0.273683 & -2.1022 & 0.019907 \tabularnewline
13 & -0.023077 & -0.1773 & 0.429956 \tabularnewline
14 & 0.005288 & 0.0406 & 0.483868 \tabularnewline
15 & 0.008039 & 0.0617 & 0.475486 \tabularnewline
16 & 0.026332 & 0.2023 & 0.420204 \tabularnewline
17 & -0.176631 & -1.3567 & 0.090019 \tabularnewline
18 & -0.133612 & -1.0263 & 0.154472 \tabularnewline
19 & 0.015704 & 0.1206 & 0.4522 \tabularnewline
20 & -0.148088 & -1.1375 & 0.129967 \tabularnewline
21 & 0.122779 & 0.9431 & 0.174743 \tabularnewline
22 & 0.017869 & 0.1373 & 0.445648 \tabularnewline
23 & 0.093178 & 0.7157 & 0.238496 \tabularnewline
24 & -0.157122 & -1.2069 & 0.116148 \tabularnewline
25 & 0.160051 & 1.2294 & 0.111905 \tabularnewline
26 & -0.054713 & -0.4203 & 0.33791 \tabularnewline
27 & 0.004606 & 0.0354 & 0.485948 \tabularnewline
28 & -0.045854 & -0.3522 & 0.362966 \tabularnewline
29 & -0.059299 & -0.4555 & 0.325217 \tabularnewline
30 & 0.019636 & 0.1508 & 0.440312 \tabularnewline
31 & 0.009753 & 0.0749 & 0.470268 \tabularnewline
32 & 0.049934 & 0.3835 & 0.351346 \tabularnewline
33 & 0.008506 & 0.0653 & 0.474065 \tabularnewline
34 & -0.008879 & -0.0682 & 0.472928 \tabularnewline
35 & 0.032016 & 0.2459 & 0.4033 \tabularnewline
36 & 0.050577 & 0.3885 & 0.349525 \tabularnewline
37 & -0.028559 & -0.2194 & 0.413562 \tabularnewline
38 & 0.041722 & 0.3205 & 0.374872 \tabularnewline
39 & -0.023048 & -0.177 & 0.430044 \tabularnewline
40 & -0.054702 & -0.4202 & 0.337943 \tabularnewline
41 & 0.014532 & 0.1116 & 0.455751 \tabularnewline
42 & 0.008194 & 0.0629 & 0.475013 \tabularnewline
43 & -0.032175 & -0.2471 & 0.402829 \tabularnewline
44 & -0.151995 & -1.1675 & 0.123853 \tabularnewline
45 & 0.041365 & 0.3177 & 0.375905 \tabularnewline
46 & 0.032465 & 0.2494 & 0.401971 \tabularnewline
47 & -0.131416 & -1.0094 & 0.158447 \tabularnewline
48 & 0.017083 & 0.1312 & 0.448026 \tabularnewline
49 & -0.049519 & -0.3804 & 0.352522 \tabularnewline
50 & -0.016245 & -0.1248 & 0.450561 \tabularnewline
51 & 0.044521 & 0.342 & 0.366793 \tabularnewline
52 & -0.116171 & -0.8923 & 0.187922 \tabularnewline
53 & -0.081404 & -0.6253 & 0.2671 \tabularnewline
54 & 0.107938 & 0.8291 & 0.205199 \tabularnewline
55 & -0.044313 & -0.3404 & 0.367391 \tabularnewline
56 & 0.026569 & 0.2041 & 0.419495 \tabularnewline
57 & -0.093931 & -0.7215 & 0.236725 \tabularnewline
58 & -0.04305 & -0.3307 & 0.371032 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71422&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]0.433269[/C][C]3.328[/C][C]0.000755[/C][/ROW]
[ROW][C]2[/C][C]0.155933[/C][C]1.1977[/C][C]0.117904[/C][/ROW]
[ROW][C]3[/C][C]-0.141943[/C][C]-1.0903[/C][C]0.140011[/C][/ROW]
[ROW][C]4[/C][C]-0.042416[/C][C]-0.3258[/C][C]0.372862[/C][/ROW]
[ROW][C]5[/C][C]-0.158813[/C][C]-1.2199[/C][C]0.113685[/C][/ROW]
[ROW][C]6[/C][C]-0.269167[/C][C]-2.0675[/C][C]0.02154[/C][/ROW]
[ROW][C]7[/C][C]0.163802[/C][C]1.2582[/C][C]0.106641[/C][/ROW]
[ROW][C]8[/C][C]-0.127531[/C][C]-0.9796[/C][C]0.165646[/C][/ROW]
[ROW][C]9[/C][C]-0.05835[/C][C]-0.4482[/C][C]0.327828[/C][/ROW]
[ROW][C]10[/C][C]0.12864[/C][C]0.9881[/C][C]0.163568[/C][/ROW]
[ROW][C]11[/C][C]-0.02852[/C][C]-0.2191[/C][C]0.413678[/C][/ROW]
[ROW][C]12[/C][C]-0.273683[/C][C]-2.1022[/C][C]0.019907[/C][/ROW]
[ROW][C]13[/C][C]-0.023077[/C][C]-0.1773[/C][C]0.429956[/C][/ROW]
[ROW][C]14[/C][C]0.005288[/C][C]0.0406[/C][C]0.483868[/C][/ROW]
[ROW][C]15[/C][C]0.008039[/C][C]0.0617[/C][C]0.475486[/C][/ROW]
[ROW][C]16[/C][C]0.026332[/C][C]0.2023[/C][C]0.420204[/C][/ROW]
[ROW][C]17[/C][C]-0.176631[/C][C]-1.3567[/C][C]0.090019[/C][/ROW]
[ROW][C]18[/C][C]-0.133612[/C][C]-1.0263[/C][C]0.154472[/C][/ROW]
[ROW][C]19[/C][C]0.015704[/C][C]0.1206[/C][C]0.4522[/C][/ROW]
[ROW][C]20[/C][C]-0.148088[/C][C]-1.1375[/C][C]0.129967[/C][/ROW]
[ROW][C]21[/C][C]0.122779[/C][C]0.9431[/C][C]0.174743[/C][/ROW]
[ROW][C]22[/C][C]0.017869[/C][C]0.1373[/C][C]0.445648[/C][/ROW]
[ROW][C]23[/C][C]0.093178[/C][C]0.7157[/C][C]0.238496[/C][/ROW]
[ROW][C]24[/C][C]-0.157122[/C][C]-1.2069[/C][C]0.116148[/C][/ROW]
[ROW][C]25[/C][C]0.160051[/C][C]1.2294[/C][C]0.111905[/C][/ROW]
[ROW][C]26[/C][C]-0.054713[/C][C]-0.4203[/C][C]0.33791[/C][/ROW]
[ROW][C]27[/C][C]0.004606[/C][C]0.0354[/C][C]0.485948[/C][/ROW]
[ROW][C]28[/C][C]-0.045854[/C][C]-0.3522[/C][C]0.362966[/C][/ROW]
[ROW][C]29[/C][C]-0.059299[/C][C]-0.4555[/C][C]0.325217[/C][/ROW]
[ROW][C]30[/C][C]0.019636[/C][C]0.1508[/C][C]0.440312[/C][/ROW]
[ROW][C]31[/C][C]0.009753[/C][C]0.0749[/C][C]0.470268[/C][/ROW]
[ROW][C]32[/C][C]0.049934[/C][C]0.3835[/C][C]0.351346[/C][/ROW]
[ROW][C]33[/C][C]0.008506[/C][C]0.0653[/C][C]0.474065[/C][/ROW]
[ROW][C]34[/C][C]-0.008879[/C][C]-0.0682[/C][C]0.472928[/C][/ROW]
[ROW][C]35[/C][C]0.032016[/C][C]0.2459[/C][C]0.4033[/C][/ROW]
[ROW][C]36[/C][C]0.050577[/C][C]0.3885[/C][C]0.349525[/C][/ROW]
[ROW][C]37[/C][C]-0.028559[/C][C]-0.2194[/C][C]0.413562[/C][/ROW]
[ROW][C]38[/C][C]0.041722[/C][C]0.3205[/C][C]0.374872[/C][/ROW]
[ROW][C]39[/C][C]-0.023048[/C][C]-0.177[/C][C]0.430044[/C][/ROW]
[ROW][C]40[/C][C]-0.054702[/C][C]-0.4202[/C][C]0.337943[/C][/ROW]
[ROW][C]41[/C][C]0.014532[/C][C]0.1116[/C][C]0.455751[/C][/ROW]
[ROW][C]42[/C][C]0.008194[/C][C]0.0629[/C][C]0.475013[/C][/ROW]
[ROW][C]43[/C][C]-0.032175[/C][C]-0.2471[/C][C]0.402829[/C][/ROW]
[ROW][C]44[/C][C]-0.151995[/C][C]-1.1675[/C][C]0.123853[/C][/ROW]
[ROW][C]45[/C][C]0.041365[/C][C]0.3177[/C][C]0.375905[/C][/ROW]
[ROW][C]46[/C][C]0.032465[/C][C]0.2494[/C][C]0.401971[/C][/ROW]
[ROW][C]47[/C][C]-0.131416[/C][C]-1.0094[/C][C]0.158447[/C][/ROW]
[ROW][C]48[/C][C]0.017083[/C][C]0.1312[/C][C]0.448026[/C][/ROW]
[ROW][C]49[/C][C]-0.049519[/C][C]-0.3804[/C][C]0.352522[/C][/ROW]
[ROW][C]50[/C][C]-0.016245[/C][C]-0.1248[/C][C]0.450561[/C][/ROW]
[ROW][C]51[/C][C]0.044521[/C][C]0.342[/C][C]0.366793[/C][/ROW]
[ROW][C]52[/C][C]-0.116171[/C][C]-0.8923[/C][C]0.187922[/C][/ROW]
[ROW][C]53[/C][C]-0.081404[/C][C]-0.6253[/C][C]0.2671[/C][/ROW]
[ROW][C]54[/C][C]0.107938[/C][C]0.8291[/C][C]0.205199[/C][/ROW]
[ROW][C]55[/C][C]-0.044313[/C][C]-0.3404[/C][C]0.367391[/C][/ROW]
[ROW][C]56[/C][C]0.026569[/C][C]0.2041[/C][C]0.419495[/C][/ROW]
[ROW][C]57[/C][C]-0.093931[/C][C]-0.7215[/C][C]0.236725[/C][/ROW]
[ROW][C]58[/C][C]-0.04305[/C][C]-0.3307[/C][C]0.371032[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=71422&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71422&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
10.4332693.3280.000755
20.1559331.19770.117904
3-0.141943-1.09030.140011
4-0.042416-0.32580.372862
5-0.158813-1.21990.113685
6-0.269167-2.06750.02154
70.1638021.25820.106641
8-0.127531-0.97960.165646
9-0.05835-0.44820.327828
100.128640.98810.163568
11-0.02852-0.21910.413678
12-0.273683-2.10220.019907
13-0.023077-0.17730.429956
140.0052880.04060.483868
150.0080390.06170.475486
160.0263320.20230.420204
17-0.176631-1.35670.090019
18-0.133612-1.02630.154472
190.0157040.12060.4522
20-0.148088-1.13750.129967
210.1227790.94310.174743
220.0178690.13730.445648
230.0931780.71570.238496
24-0.157122-1.20690.116148
250.1600511.22940.111905
26-0.054713-0.42030.33791
270.0046060.03540.485948
28-0.045854-0.35220.362966
29-0.059299-0.45550.325217
300.0196360.15080.440312
310.0097530.07490.470268
320.0499340.38350.351346
330.0085060.06530.474065
34-0.008879-0.06820.472928
350.0320160.24590.4033
360.0505770.38850.349525
37-0.028559-0.21940.413562
380.0417220.32050.374872
39-0.023048-0.1770.430044
40-0.054702-0.42020.337943
410.0145320.11160.455751
420.0081940.06290.475013
43-0.032175-0.24710.402829
44-0.151995-1.16750.123853
450.0413650.31770.375905
460.0324650.24940.401971
47-0.131416-1.00940.158447
480.0170830.13120.448026
49-0.049519-0.38040.352522
50-0.016245-0.12480.450561
510.0445210.3420.366793
52-0.116171-0.89230.187922
53-0.081404-0.62530.2671
540.1079380.82910.205199
55-0.044313-0.34040.367391
560.0265690.20410.419495
57-0.093931-0.72150.236725
58-0.04305-0.33070.371032
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = -0.7 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ;
Parameters (R input):
par1 = 60 ; par2 = -0.7 ; 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')