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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 29 Apr 2010 16:10:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Apr/29/t12725575017fqkc6pugcw9ou8.htm/, Retrieved Tue, 23 Apr 2024 15:00:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75053, Retrieved Tue, 23 Apr 2024 15:00:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact225
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [6.2.3 bis] [2010-04-29 16:10:36] [0e5311d1fc10a1511b42f76588fb6510] [Current]
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Dataseries X:
81.28
69.39
67.63
51.25
103.97
133.83
162.37
172.91
163.01
151.50
111.73
88.58
74.29
63.98
61.18
76.48
107.98
124.97
145.57
140.20
143.84
138.80
104.06
74.70
60.18
55.16
35.62
56.18
85.44
114.08
133.64
67.14
95.58
89.37
75.24
69.18
54.49
57.50
62.16
76.67
110.04
127.38
156.47
167.56
153.54
124.08
100.97
79.17
68.13
61.77
54.31
60.30
84.18
104.05
114.66
105.55
96.61
70.94
63.91
58.61
44.53
49.58
57.39
76.76
104.57
125.41
143.11
136.35
135.15
131.70
96.87
70.63
66.29
63.49
62.97
66.43
101.49
127.69
133.21
158.72
148.61
134.31
100.99
75.16
59.74
52.87
52.07
57.38
79.43
101.40
120.19
134.38
135.97
113.83
84.38
70.28
65.96
56.36
49.57
68.33
90.32
117.06
134.69
131.67
129.25
118.77
88.44
76.79
75.28
73.89
76.24
88.58
105.83
115.84
127.76
131.75
119.63
93.38
75.55
51.79




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=75053&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=75053&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75053&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
10.4904315.350
20.2685542.92960.002035
3-0.029329-0.31990.374789
4-0.341536-3.72570.00015
5-0.471064-5.13871e-06
6-0.660847-7.2090
7-0.476493-5.19790
8-0.258125-2.81580.002848
9-0.005611-0.06120.47565
100.2795243.04920.001414
110.4742635.17360
120.5952386.49330
130.4511554.92151e-06
140.2469672.69410.004039
15-0.069781-0.76120.224014
16-0.268103-2.92470.002065
17-0.494987-5.39970
18-0.562274-6.13370
19-0.415958-4.53767e-06
20-0.2033-2.21770.014235
210.043740.47710.317067
220.2273012.47960.007277
230.4811435.24860
240.5136535.60330
250.3782454.12623.4e-05
260.2181912.38020.009446
27-0.108769-1.18650.118888
28-0.208167-2.27080.012478
29-0.4068-4.43771e-05
30-0.45535-4.96731e-06
31-0.351699-3.83660.000101
32-0.206952-2.25760.012898
330.0200210.21840.413746
340.230992.51980.006534
350.3831324.17952.8e-05
360.4959875.41060
370.3747544.08814e-05
380.1715961.87190.031838
39-0.007737-0.08440.466442
40-0.236805-2.58320.005499
41-0.379309-4.13783.3e-05
42-0.398643-4.34871.5e-05
43-0.312985-3.41430.000438
44-0.133122-1.45220.07454
45-0.026411-0.28810.386881
460.1568761.71130.044814
470.3472893.78850.00012
480.3519973.83989.9e-05
490.3204663.49590.000332
500.1222521.33360.092439
51-0.028606-0.31210.377773
52-0.163624-1.78490.03841
53-0.31842-3.47350.000359
54-0.340001-3.7090.000159
55-0.285153-3.11060.001168
56-0.130617-1.42490.078408
570.0065850.07180.471428
580.1504711.64140.051672
590.288443.14650.001044
600.3223283.51620.00031

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.490431 & 5.35 & 0 \tabularnewline
2 & 0.268554 & 2.9296 & 0.002035 \tabularnewline
3 & -0.029329 & -0.3199 & 0.374789 \tabularnewline
4 & -0.341536 & -3.7257 & 0.00015 \tabularnewline
5 & -0.471064 & -5.1387 & 1e-06 \tabularnewline
6 & -0.660847 & -7.209 & 0 \tabularnewline
7 & -0.476493 & -5.1979 & 0 \tabularnewline
8 & -0.258125 & -2.8158 & 0.002848 \tabularnewline
9 & -0.005611 & -0.0612 & 0.47565 \tabularnewline
10 & 0.279524 & 3.0492 & 0.001414 \tabularnewline
11 & 0.474263 & 5.1736 & 0 \tabularnewline
12 & 0.595238 & 6.4933 & 0 \tabularnewline
13 & 0.451155 & 4.9215 & 1e-06 \tabularnewline
14 & 0.246967 & 2.6941 & 0.004039 \tabularnewline
15 & -0.069781 & -0.7612 & 0.224014 \tabularnewline
16 & -0.268103 & -2.9247 & 0.002065 \tabularnewline
17 & -0.494987 & -5.3997 & 0 \tabularnewline
18 & -0.562274 & -6.1337 & 0 \tabularnewline
19 & -0.415958 & -4.5376 & 7e-06 \tabularnewline
20 & -0.2033 & -2.2177 & 0.014235 \tabularnewline
21 & 0.04374 & 0.4771 & 0.317067 \tabularnewline
22 & 0.227301 & 2.4796 & 0.007277 \tabularnewline
23 & 0.481143 & 5.2486 & 0 \tabularnewline
24 & 0.513653 & 5.6033 & 0 \tabularnewline
25 & 0.378245 & 4.1262 & 3.4e-05 \tabularnewline
26 & 0.218191 & 2.3802 & 0.009446 \tabularnewline
27 & -0.108769 & -1.1865 & 0.118888 \tabularnewline
28 & -0.208167 & -2.2708 & 0.012478 \tabularnewline
29 & -0.4068 & -4.4377 & 1e-05 \tabularnewline
30 & -0.45535 & -4.9673 & 1e-06 \tabularnewline
31 & -0.351699 & -3.8366 & 0.000101 \tabularnewline
32 & -0.206952 & -2.2576 & 0.012898 \tabularnewline
33 & 0.020021 & 0.2184 & 0.413746 \tabularnewline
34 & 0.23099 & 2.5198 & 0.006534 \tabularnewline
35 & 0.383132 & 4.1795 & 2.8e-05 \tabularnewline
36 & 0.495987 & 5.4106 & 0 \tabularnewline
37 & 0.374754 & 4.0881 & 4e-05 \tabularnewline
38 & 0.171596 & 1.8719 & 0.031838 \tabularnewline
39 & -0.007737 & -0.0844 & 0.466442 \tabularnewline
40 & -0.236805 & -2.5832 & 0.005499 \tabularnewline
41 & -0.379309 & -4.1378 & 3.3e-05 \tabularnewline
42 & -0.398643 & -4.3487 & 1.5e-05 \tabularnewline
43 & -0.312985 & -3.4143 & 0.000438 \tabularnewline
44 & -0.133122 & -1.4522 & 0.07454 \tabularnewline
45 & -0.026411 & -0.2881 & 0.386881 \tabularnewline
46 & 0.156876 & 1.7113 & 0.044814 \tabularnewline
47 & 0.347289 & 3.7885 & 0.00012 \tabularnewline
48 & 0.351997 & 3.8398 & 9.9e-05 \tabularnewline
49 & 0.320466 & 3.4959 & 0.000332 \tabularnewline
50 & 0.122252 & 1.3336 & 0.092439 \tabularnewline
51 & -0.028606 & -0.3121 & 0.377773 \tabularnewline
52 & -0.163624 & -1.7849 & 0.03841 \tabularnewline
53 & -0.31842 & -3.4735 & 0.000359 \tabularnewline
54 & -0.340001 & -3.709 & 0.000159 \tabularnewline
55 & -0.285153 & -3.1106 & 0.001168 \tabularnewline
56 & -0.130617 & -1.4249 & 0.078408 \tabularnewline
57 & 0.006585 & 0.0718 & 0.471428 \tabularnewline
58 & 0.150471 & 1.6414 & 0.051672 \tabularnewline
59 & 0.28844 & 3.1465 & 0.001044 \tabularnewline
60 & 0.322328 & 3.5162 & 0.00031 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75053&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]0.490431[/C][C]5.35[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.268554[/C][C]2.9296[/C][C]0.002035[/C][/ROW]
[ROW][C]3[/C][C]-0.029329[/C][C]-0.3199[/C][C]0.374789[/C][/ROW]
[ROW][C]4[/C][C]-0.341536[/C][C]-3.7257[/C][C]0.00015[/C][/ROW]
[ROW][C]5[/C][C]-0.471064[/C][C]-5.1387[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]-0.660847[/C][C]-7.209[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.476493[/C][C]-5.1979[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]-0.258125[/C][C]-2.8158[/C][C]0.002848[/C][/ROW]
[ROW][C]9[/C][C]-0.005611[/C][C]-0.0612[/C][C]0.47565[/C][/ROW]
[ROW][C]10[/C][C]0.279524[/C][C]3.0492[/C][C]0.001414[/C][/ROW]
[ROW][C]11[/C][C]0.474263[/C][C]5.1736[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.595238[/C][C]6.4933[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.451155[/C][C]4.9215[/C][C]1e-06[/C][/ROW]
[ROW][C]14[/C][C]0.246967[/C][C]2.6941[/C][C]0.004039[/C][/ROW]
[ROW][C]15[/C][C]-0.069781[/C][C]-0.7612[/C][C]0.224014[/C][/ROW]
[ROW][C]16[/C][C]-0.268103[/C][C]-2.9247[/C][C]0.002065[/C][/ROW]
[ROW][C]17[/C][C]-0.494987[/C][C]-5.3997[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]-0.562274[/C][C]-6.1337[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.415958[/C][C]-4.5376[/C][C]7e-06[/C][/ROW]
[ROW][C]20[/C][C]-0.2033[/C][C]-2.2177[/C][C]0.014235[/C][/ROW]
[ROW][C]21[/C][C]0.04374[/C][C]0.4771[/C][C]0.317067[/C][/ROW]
[ROW][C]22[/C][C]0.227301[/C][C]2.4796[/C][C]0.007277[/C][/ROW]
[ROW][C]23[/C][C]0.481143[/C][C]5.2486[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.513653[/C][C]5.6033[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.378245[/C][C]4.1262[/C][C]3.4e-05[/C][/ROW]
[ROW][C]26[/C][C]0.218191[/C][C]2.3802[/C][C]0.009446[/C][/ROW]
[ROW][C]27[/C][C]-0.108769[/C][C]-1.1865[/C][C]0.118888[/C][/ROW]
[ROW][C]28[/C][C]-0.208167[/C][C]-2.2708[/C][C]0.012478[/C][/ROW]
[ROW][C]29[/C][C]-0.4068[/C][C]-4.4377[/C][C]1e-05[/C][/ROW]
[ROW][C]30[/C][C]-0.45535[/C][C]-4.9673[/C][C]1e-06[/C][/ROW]
[ROW][C]31[/C][C]-0.351699[/C][C]-3.8366[/C][C]0.000101[/C][/ROW]
[ROW][C]32[/C][C]-0.206952[/C][C]-2.2576[/C][C]0.012898[/C][/ROW]
[ROW][C]33[/C][C]0.020021[/C][C]0.2184[/C][C]0.413746[/C][/ROW]
[ROW][C]34[/C][C]0.23099[/C][C]2.5198[/C][C]0.006534[/C][/ROW]
[ROW][C]35[/C][C]0.383132[/C][C]4.1795[/C][C]2.8e-05[/C][/ROW]
[ROW][C]36[/C][C]0.495987[/C][C]5.4106[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.374754[/C][C]4.0881[/C][C]4e-05[/C][/ROW]
[ROW][C]38[/C][C]0.171596[/C][C]1.8719[/C][C]0.031838[/C][/ROW]
[ROW][C]39[/C][C]-0.007737[/C][C]-0.0844[/C][C]0.466442[/C][/ROW]
[ROW][C]40[/C][C]-0.236805[/C][C]-2.5832[/C][C]0.005499[/C][/ROW]
[ROW][C]41[/C][C]-0.379309[/C][C]-4.1378[/C][C]3.3e-05[/C][/ROW]
[ROW][C]42[/C][C]-0.398643[/C][C]-4.3487[/C][C]1.5e-05[/C][/ROW]
[ROW][C]43[/C][C]-0.312985[/C][C]-3.4143[/C][C]0.000438[/C][/ROW]
[ROW][C]44[/C][C]-0.133122[/C][C]-1.4522[/C][C]0.07454[/C][/ROW]
[ROW][C]45[/C][C]-0.026411[/C][C]-0.2881[/C][C]0.386881[/C][/ROW]
[ROW][C]46[/C][C]0.156876[/C][C]1.7113[/C][C]0.044814[/C][/ROW]
[ROW][C]47[/C][C]0.347289[/C][C]3.7885[/C][C]0.00012[/C][/ROW]
[ROW][C]48[/C][C]0.351997[/C][C]3.8398[/C][C]9.9e-05[/C][/ROW]
[ROW][C]49[/C][C]0.320466[/C][C]3.4959[/C][C]0.000332[/C][/ROW]
[ROW][C]50[/C][C]0.122252[/C][C]1.3336[/C][C]0.092439[/C][/ROW]
[ROW][C]51[/C][C]-0.028606[/C][C]-0.3121[/C][C]0.377773[/C][/ROW]
[ROW][C]52[/C][C]-0.163624[/C][C]-1.7849[/C][C]0.03841[/C][/ROW]
[ROW][C]53[/C][C]-0.31842[/C][C]-3.4735[/C][C]0.000359[/C][/ROW]
[ROW][C]54[/C][C]-0.340001[/C][C]-3.709[/C][C]0.000159[/C][/ROW]
[ROW][C]55[/C][C]-0.285153[/C][C]-3.1106[/C][C]0.001168[/C][/ROW]
[ROW][C]56[/C][C]-0.130617[/C][C]-1.4249[/C][C]0.078408[/C][/ROW]
[ROW][C]57[/C][C]0.006585[/C][C]0.0718[/C][C]0.471428[/C][/ROW]
[ROW][C]58[/C][C]0.150471[/C][C]1.6414[/C][C]0.051672[/C][/ROW]
[ROW][C]59[/C][C]0.28844[/C][C]3.1465[/C][C]0.001044[/C][/ROW]
[ROW][C]60[/C][C]0.322328[/C][C]3.5162[/C][C]0.00031[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75053&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75053&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
10.4904315.350
20.2685542.92960.002035
3-0.029329-0.31990.374789
4-0.341536-3.72570.00015
5-0.471064-5.13871e-06
6-0.660847-7.2090
7-0.476493-5.19790
8-0.258125-2.81580.002848
9-0.005611-0.06120.47565
100.2795243.04920.001414
110.4742635.17360
120.5952386.49330
130.4511554.92151e-06
140.2469672.69410.004039
15-0.069781-0.76120.224014
16-0.268103-2.92470.002065
17-0.494987-5.39970
18-0.562274-6.13370
19-0.415958-4.53767e-06
20-0.2033-2.21770.014235
210.043740.47710.317067
220.2273012.47960.007277
230.4811435.24860
240.5136535.60330
250.3782454.12623.4e-05
260.2181912.38020.009446
27-0.108769-1.18650.118888
28-0.208167-2.27080.012478
29-0.4068-4.43771e-05
30-0.45535-4.96731e-06
31-0.351699-3.83660.000101
32-0.206952-2.25760.012898
330.0200210.21840.413746
340.230992.51980.006534
350.3831324.17952.8e-05
360.4959875.41060
370.3747544.08814e-05
380.1715961.87190.031838
39-0.007737-0.08440.466442
40-0.236805-2.58320.005499
41-0.379309-4.13783.3e-05
42-0.398643-4.34871.5e-05
43-0.312985-3.41430.000438
44-0.133122-1.45220.07454
45-0.026411-0.28810.386881
460.1568761.71130.044814
470.3472893.78850.00012
480.3519973.83989.9e-05
490.3204663.49590.000332
500.1222521.33360.092439
51-0.028606-0.31210.377773
52-0.163624-1.78490.03841
53-0.31842-3.47350.000359
54-0.340001-3.7090.000159
55-0.285153-3.11060.001168
56-0.130617-1.42490.078408
570.0065850.07180.471428
580.1504711.64140.051672
590.288443.14650.001044
600.3223283.51620.00031







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4904315.350
20.0369080.40260.343974
3-0.229781-2.50660.006769
4-0.353288-3.85399.4e-05
5-0.221792-2.41950.008528
6-0.447391-4.88052e-06
7-0.150765-1.64470.05134
8-0.114937-1.25380.106184
9-0.106839-1.16550.123078
10-0.053628-0.5850.279824
110.0769410.83930.201483
120.1301021.41920.07922
130.0122820.1340.44682
140.0296290.32320.373552
15-0.11791-1.28630.100426
160.0339630.37050.355837
17-0.137478-1.49970.068169
18-0.099332-1.08360.14037
19-0.04362-0.47580.317532
200.0227240.24790.402324
21-0.099115-1.08120.140893
22-0.129635-1.41420.079964
230.0734570.80130.212273
24-0.027583-0.30090.382009
25-0.082042-0.8950.186303
260.0218270.23810.406104
27-0.146209-1.5950.056687
280.0774860.84530.199828
290.0408160.44530.328473
30-0.014784-0.16130.436074
31-0.054464-0.59410.276775
32-0.03199-0.3490.363863
33-0.137027-1.49480.068808
340.0239410.26120.397209
35-0.023879-0.26050.397467
360.1143681.24760.107312
370.0126850.13840.44509
38-0.007965-0.08690.465454
390.0459190.50090.308678
40-0.02472-0.26970.393942
410.0220470.24050.405178
420.0532120.58050.281347
430.1190941.29920.0982
440.065890.71880.236844
45-0.056491-0.61620.269456
46-0.060109-0.65570.256636
470.1003091.09420.13803
48-0.076563-0.83520.202638
490.0133150.14520.44238
50-0.059368-0.64760.259235
51-0.029838-0.32550.37269
52-0.004631-0.05050.479896
530.0361420.39430.347045
54-0.068927-0.75190.226796
55-0.005278-0.05760.477091
56-0.008348-0.09110.463795
57-0.044615-0.48670.313687
58-0.015273-0.16660.433979
59-0.012962-0.14140.443898
60-0.039295-0.42870.334474

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.490431 & 5.35 & 0 \tabularnewline
2 & 0.036908 & 0.4026 & 0.343974 \tabularnewline
3 & -0.229781 & -2.5066 & 0.006769 \tabularnewline
4 & -0.353288 & -3.8539 & 9.4e-05 \tabularnewline
5 & -0.221792 & -2.4195 & 0.008528 \tabularnewline
6 & -0.447391 & -4.8805 & 2e-06 \tabularnewline
7 & -0.150765 & -1.6447 & 0.05134 \tabularnewline
8 & -0.114937 & -1.2538 & 0.106184 \tabularnewline
9 & -0.106839 & -1.1655 & 0.123078 \tabularnewline
10 & -0.053628 & -0.585 & 0.279824 \tabularnewline
11 & 0.076941 & 0.8393 & 0.201483 \tabularnewline
12 & 0.130102 & 1.4192 & 0.07922 \tabularnewline
13 & 0.012282 & 0.134 & 0.44682 \tabularnewline
14 & 0.029629 & 0.3232 & 0.373552 \tabularnewline
15 & -0.11791 & -1.2863 & 0.100426 \tabularnewline
16 & 0.033963 & 0.3705 & 0.355837 \tabularnewline
17 & -0.137478 & -1.4997 & 0.068169 \tabularnewline
18 & -0.099332 & -1.0836 & 0.14037 \tabularnewline
19 & -0.04362 & -0.4758 & 0.317532 \tabularnewline
20 & 0.022724 & 0.2479 & 0.402324 \tabularnewline
21 & -0.099115 & -1.0812 & 0.140893 \tabularnewline
22 & -0.129635 & -1.4142 & 0.079964 \tabularnewline
23 & 0.073457 & 0.8013 & 0.212273 \tabularnewline
24 & -0.027583 & -0.3009 & 0.382009 \tabularnewline
25 & -0.082042 & -0.895 & 0.186303 \tabularnewline
26 & 0.021827 & 0.2381 & 0.406104 \tabularnewline
27 & -0.146209 & -1.595 & 0.056687 \tabularnewline
28 & 0.077486 & 0.8453 & 0.199828 \tabularnewline
29 & 0.040816 & 0.4453 & 0.328473 \tabularnewline
30 & -0.014784 & -0.1613 & 0.436074 \tabularnewline
31 & -0.054464 & -0.5941 & 0.276775 \tabularnewline
32 & -0.03199 & -0.349 & 0.363863 \tabularnewline
33 & -0.137027 & -1.4948 & 0.068808 \tabularnewline
34 & 0.023941 & 0.2612 & 0.397209 \tabularnewline
35 & -0.023879 & -0.2605 & 0.397467 \tabularnewline
36 & 0.114368 & 1.2476 & 0.107312 \tabularnewline
37 & 0.012685 & 0.1384 & 0.44509 \tabularnewline
38 & -0.007965 & -0.0869 & 0.465454 \tabularnewline
39 & 0.045919 & 0.5009 & 0.308678 \tabularnewline
40 & -0.02472 & -0.2697 & 0.393942 \tabularnewline
41 & 0.022047 & 0.2405 & 0.405178 \tabularnewline
42 & 0.053212 & 0.5805 & 0.281347 \tabularnewline
43 & 0.119094 & 1.2992 & 0.0982 \tabularnewline
44 & 0.06589 & 0.7188 & 0.236844 \tabularnewline
45 & -0.056491 & -0.6162 & 0.269456 \tabularnewline
46 & -0.060109 & -0.6557 & 0.256636 \tabularnewline
47 & 0.100309 & 1.0942 & 0.13803 \tabularnewline
48 & -0.076563 & -0.8352 & 0.202638 \tabularnewline
49 & 0.013315 & 0.1452 & 0.44238 \tabularnewline
50 & -0.059368 & -0.6476 & 0.259235 \tabularnewline
51 & -0.029838 & -0.3255 & 0.37269 \tabularnewline
52 & -0.004631 & -0.0505 & 0.479896 \tabularnewline
53 & 0.036142 & 0.3943 & 0.347045 \tabularnewline
54 & -0.068927 & -0.7519 & 0.226796 \tabularnewline
55 & -0.005278 & -0.0576 & 0.477091 \tabularnewline
56 & -0.008348 & -0.0911 & 0.463795 \tabularnewline
57 & -0.044615 & -0.4867 & 0.313687 \tabularnewline
58 & -0.015273 & -0.1666 & 0.433979 \tabularnewline
59 & -0.012962 & -0.1414 & 0.443898 \tabularnewline
60 & -0.039295 & -0.4287 & 0.334474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75053&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]0.490431[/C][C]5.35[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.036908[/C][C]0.4026[/C][C]0.343974[/C][/ROW]
[ROW][C]3[/C][C]-0.229781[/C][C]-2.5066[/C][C]0.006769[/C][/ROW]
[ROW][C]4[/C][C]-0.353288[/C][C]-3.8539[/C][C]9.4e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.221792[/C][C]-2.4195[/C][C]0.008528[/C][/ROW]
[ROW][C]6[/C][C]-0.447391[/C][C]-4.8805[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]-0.150765[/C][C]-1.6447[/C][C]0.05134[/C][/ROW]
[ROW][C]8[/C][C]-0.114937[/C][C]-1.2538[/C][C]0.106184[/C][/ROW]
[ROW][C]9[/C][C]-0.106839[/C][C]-1.1655[/C][C]0.123078[/C][/ROW]
[ROW][C]10[/C][C]-0.053628[/C][C]-0.585[/C][C]0.279824[/C][/ROW]
[ROW][C]11[/C][C]0.076941[/C][C]0.8393[/C][C]0.201483[/C][/ROW]
[ROW][C]12[/C][C]0.130102[/C][C]1.4192[/C][C]0.07922[/C][/ROW]
[ROW][C]13[/C][C]0.012282[/C][C]0.134[/C][C]0.44682[/C][/ROW]
[ROW][C]14[/C][C]0.029629[/C][C]0.3232[/C][C]0.373552[/C][/ROW]
[ROW][C]15[/C][C]-0.11791[/C][C]-1.2863[/C][C]0.100426[/C][/ROW]
[ROW][C]16[/C][C]0.033963[/C][C]0.3705[/C][C]0.355837[/C][/ROW]
[ROW][C]17[/C][C]-0.137478[/C][C]-1.4997[/C][C]0.068169[/C][/ROW]
[ROW][C]18[/C][C]-0.099332[/C][C]-1.0836[/C][C]0.14037[/C][/ROW]
[ROW][C]19[/C][C]-0.04362[/C][C]-0.4758[/C][C]0.317532[/C][/ROW]
[ROW][C]20[/C][C]0.022724[/C][C]0.2479[/C][C]0.402324[/C][/ROW]
[ROW][C]21[/C][C]-0.099115[/C][C]-1.0812[/C][C]0.140893[/C][/ROW]
[ROW][C]22[/C][C]-0.129635[/C][C]-1.4142[/C][C]0.079964[/C][/ROW]
[ROW][C]23[/C][C]0.073457[/C][C]0.8013[/C][C]0.212273[/C][/ROW]
[ROW][C]24[/C][C]-0.027583[/C][C]-0.3009[/C][C]0.382009[/C][/ROW]
[ROW][C]25[/C][C]-0.082042[/C][C]-0.895[/C][C]0.186303[/C][/ROW]
[ROW][C]26[/C][C]0.021827[/C][C]0.2381[/C][C]0.406104[/C][/ROW]
[ROW][C]27[/C][C]-0.146209[/C][C]-1.595[/C][C]0.056687[/C][/ROW]
[ROW][C]28[/C][C]0.077486[/C][C]0.8453[/C][C]0.199828[/C][/ROW]
[ROW][C]29[/C][C]0.040816[/C][C]0.4453[/C][C]0.328473[/C][/ROW]
[ROW][C]30[/C][C]-0.014784[/C][C]-0.1613[/C][C]0.436074[/C][/ROW]
[ROW][C]31[/C][C]-0.054464[/C][C]-0.5941[/C][C]0.276775[/C][/ROW]
[ROW][C]32[/C][C]-0.03199[/C][C]-0.349[/C][C]0.363863[/C][/ROW]
[ROW][C]33[/C][C]-0.137027[/C][C]-1.4948[/C][C]0.068808[/C][/ROW]
[ROW][C]34[/C][C]0.023941[/C][C]0.2612[/C][C]0.397209[/C][/ROW]
[ROW][C]35[/C][C]-0.023879[/C][C]-0.2605[/C][C]0.397467[/C][/ROW]
[ROW][C]36[/C][C]0.114368[/C][C]1.2476[/C][C]0.107312[/C][/ROW]
[ROW][C]37[/C][C]0.012685[/C][C]0.1384[/C][C]0.44509[/C][/ROW]
[ROW][C]38[/C][C]-0.007965[/C][C]-0.0869[/C][C]0.465454[/C][/ROW]
[ROW][C]39[/C][C]0.045919[/C][C]0.5009[/C][C]0.308678[/C][/ROW]
[ROW][C]40[/C][C]-0.02472[/C][C]-0.2697[/C][C]0.393942[/C][/ROW]
[ROW][C]41[/C][C]0.022047[/C][C]0.2405[/C][C]0.405178[/C][/ROW]
[ROW][C]42[/C][C]0.053212[/C][C]0.5805[/C][C]0.281347[/C][/ROW]
[ROW][C]43[/C][C]0.119094[/C][C]1.2992[/C][C]0.0982[/C][/ROW]
[ROW][C]44[/C][C]0.06589[/C][C]0.7188[/C][C]0.236844[/C][/ROW]
[ROW][C]45[/C][C]-0.056491[/C][C]-0.6162[/C][C]0.269456[/C][/ROW]
[ROW][C]46[/C][C]-0.060109[/C][C]-0.6557[/C][C]0.256636[/C][/ROW]
[ROW][C]47[/C][C]0.100309[/C][C]1.0942[/C][C]0.13803[/C][/ROW]
[ROW][C]48[/C][C]-0.076563[/C][C]-0.8352[/C][C]0.202638[/C][/ROW]
[ROW][C]49[/C][C]0.013315[/C][C]0.1452[/C][C]0.44238[/C][/ROW]
[ROW][C]50[/C][C]-0.059368[/C][C]-0.6476[/C][C]0.259235[/C][/ROW]
[ROW][C]51[/C][C]-0.029838[/C][C]-0.3255[/C][C]0.37269[/C][/ROW]
[ROW][C]52[/C][C]-0.004631[/C][C]-0.0505[/C][C]0.479896[/C][/ROW]
[ROW][C]53[/C][C]0.036142[/C][C]0.3943[/C][C]0.347045[/C][/ROW]
[ROW][C]54[/C][C]-0.068927[/C][C]-0.7519[/C][C]0.226796[/C][/ROW]
[ROW][C]55[/C][C]-0.005278[/C][C]-0.0576[/C][C]0.477091[/C][/ROW]
[ROW][C]56[/C][C]-0.008348[/C][C]-0.0911[/C][C]0.463795[/C][/ROW]
[ROW][C]57[/C][C]-0.044615[/C][C]-0.4867[/C][C]0.313687[/C][/ROW]
[ROW][C]58[/C][C]-0.015273[/C][C]-0.1666[/C][C]0.433979[/C][/ROW]
[ROW][C]59[/C][C]-0.012962[/C][C]-0.1414[/C][C]0.443898[/C][/ROW]
[ROW][C]60[/C][C]-0.039295[/C][C]-0.4287[/C][C]0.334474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75053&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75053&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
10.4904315.350
20.0369080.40260.343974
3-0.229781-2.50660.006769
4-0.353288-3.85399.4e-05
5-0.221792-2.41950.008528
6-0.447391-4.88052e-06
7-0.150765-1.64470.05134
8-0.114937-1.25380.106184
9-0.106839-1.16550.123078
10-0.053628-0.5850.279824
110.0769410.83930.201483
120.1301021.41920.07922
130.0122820.1340.44682
140.0296290.32320.373552
15-0.11791-1.28630.100426
160.0339630.37050.355837
17-0.137478-1.49970.068169
18-0.099332-1.08360.14037
19-0.04362-0.47580.317532
200.0227240.24790.402324
21-0.099115-1.08120.140893
22-0.129635-1.41420.079964
230.0734570.80130.212273
24-0.027583-0.30090.382009
25-0.082042-0.8950.186303
260.0218270.23810.406104
27-0.146209-1.5950.056687
280.0774860.84530.199828
290.0408160.44530.328473
30-0.014784-0.16130.436074
31-0.054464-0.59410.276775
32-0.03199-0.3490.363863
33-0.137027-1.49480.068808
340.0239410.26120.397209
35-0.023879-0.26050.397467
360.1143681.24760.107312
370.0126850.13840.44509
38-0.007965-0.08690.465454
390.0459190.50090.308678
40-0.02472-0.26970.393942
410.0220470.24050.405178
420.0532120.58050.281347
430.1190941.29920.0982
440.065890.71880.236844
45-0.056491-0.61620.269456
46-0.060109-0.65570.256636
470.1003091.09420.13803
48-0.076563-0.83520.202638
490.0133150.14520.44238
50-0.059368-0.64760.259235
51-0.029838-0.32550.37269
52-0.004631-0.05050.479896
530.0361420.39430.347045
54-0.068927-0.75190.226796
55-0.005278-0.05760.477091
56-0.008348-0.09110.463795
57-0.044615-0.48670.313687
58-0.015273-0.16660.433979
59-0.012962-0.14140.443898
60-0.039295-0.42870.334474



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')