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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 computationFri, 27 Nov 2009 05:17:16 -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/Nov/27/t1259324283fx9au710q2p5du1.htm/, Retrieved Sun, 28 Apr 2024 23:39:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60623, Retrieved Sun, 28 Apr 2024 23:39:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 8 - Model ACF 2
Estimated Impact169
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-24 11:49:44] [214e6e00abbde49700521a7ef1d30da2]
- R PD            [(Partial) Autocorrelation Function] [shw-ws8] [2009-11-27 12:17:16] [5b5bced41faf164488f2c271c918b21f] [Current]
-   P               [(Partial) Autocorrelation Function] [ACF_2] [2009-12-29 15:23:43] [2663058f2a5dda519058ac6b2228468f]
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Dataseries X:
1178
2141
2238
2685
4341
5376
4478
6404
4617
3024
1897
2075
1351
2211
2453
3042
4765
4992
4601
6266
4812
3159
1916
2237
1595
2453
2226
3597
4706
4974
5756
5493
5004
3225
2006
2291
1588
2105
2191
3591
4668
4885
5822
5599
5340
3082
2010
2301
1514
1979
2480
3499
4676
5585
5610
5796
6199
3030
1930
2552




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=60623&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=60623&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60623&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
1-0.359702-2.49210.008103
2-0.043887-0.30410.381199
30.3145292.17910.017131
4-0.193175-1.33840.093543
50.0198420.13750.445618
60.1291260.89460.187729
7-0.135308-0.93740.176613
8-0.096373-0.66770.253764
90.1687271.1690.124093
10-0.082649-0.57260.284791
11-0.065908-0.45660.325001
120.1155710.80070.213626
13-0.204149-1.41440.081852
140.2195631.52120.067388
15-0.070795-0.49050.313013
16-0.099951-0.69250.245987
170.007720.05350.478783
18-0.011812-0.08180.467558
19-0.148832-1.03110.153823
200.1225330.84890.200066
21-0.044056-0.30520.380755
22-0.200985-1.39250.0851
230.2259381.56530.062036
24-0.130113-0.90140.185925
25-0.182615-1.26520.105955
260.2720181.88460.032774
27-0.129577-0.89770.186903
28-0.010414-0.07220.471391
290.1389160.96240.170326
30-0.056031-0.38820.349793
31-0.015859-0.10990.456484
320.0802120.55570.290489
33-0.050379-0.3490.364293
34-0.037329-0.25860.398515
350.0349110.24190.404954
36-0.063919-0.44280.329933
370.0162610.11270.455386
380.0147780.10240.459438
39-0.06614-0.45820.324428
400.0560770.38850.349678
410.0693610.48050.316512
42-0.022977-0.15920.437095
43-0.004061-0.02810.488834
440.0192980.13370.447098
450.0026010.0180.492848
46-0.003875-0.02680.489347
470.0028890.020.492058
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.359702 & -2.4921 & 0.008103 \tabularnewline
2 & -0.043887 & -0.3041 & 0.381199 \tabularnewline
3 & 0.314529 & 2.1791 & 0.017131 \tabularnewline
4 & -0.193175 & -1.3384 & 0.093543 \tabularnewline
5 & 0.019842 & 0.1375 & 0.445618 \tabularnewline
6 & 0.129126 & 0.8946 & 0.187729 \tabularnewline
7 & -0.135308 & -0.9374 & 0.176613 \tabularnewline
8 & -0.096373 & -0.6677 & 0.253764 \tabularnewline
9 & 0.168727 & 1.169 & 0.124093 \tabularnewline
10 & -0.082649 & -0.5726 & 0.284791 \tabularnewline
11 & -0.065908 & -0.4566 & 0.325001 \tabularnewline
12 & 0.115571 & 0.8007 & 0.213626 \tabularnewline
13 & -0.204149 & -1.4144 & 0.081852 \tabularnewline
14 & 0.219563 & 1.5212 & 0.067388 \tabularnewline
15 & -0.070795 & -0.4905 & 0.313013 \tabularnewline
16 & -0.099951 & -0.6925 & 0.245987 \tabularnewline
17 & 0.00772 & 0.0535 & 0.478783 \tabularnewline
18 & -0.011812 & -0.0818 & 0.467558 \tabularnewline
19 & -0.148832 & -1.0311 & 0.153823 \tabularnewline
20 & 0.122533 & 0.8489 & 0.200066 \tabularnewline
21 & -0.044056 & -0.3052 & 0.380755 \tabularnewline
22 & -0.200985 & -1.3925 & 0.0851 \tabularnewline
23 & 0.225938 & 1.5653 & 0.062036 \tabularnewline
24 & -0.130113 & -0.9014 & 0.185925 \tabularnewline
25 & -0.182615 & -1.2652 & 0.105955 \tabularnewline
26 & 0.272018 & 1.8846 & 0.032774 \tabularnewline
27 & -0.129577 & -0.8977 & 0.186903 \tabularnewline
28 & -0.010414 & -0.0722 & 0.471391 \tabularnewline
29 & 0.138916 & 0.9624 & 0.170326 \tabularnewline
30 & -0.056031 & -0.3882 & 0.349793 \tabularnewline
31 & -0.015859 & -0.1099 & 0.456484 \tabularnewline
32 & 0.080212 & 0.5557 & 0.290489 \tabularnewline
33 & -0.050379 & -0.349 & 0.364293 \tabularnewline
34 & -0.037329 & -0.2586 & 0.398515 \tabularnewline
35 & 0.034911 & 0.2419 & 0.404954 \tabularnewline
36 & -0.063919 & -0.4428 & 0.329933 \tabularnewline
37 & 0.016261 & 0.1127 & 0.455386 \tabularnewline
38 & 0.014778 & 0.1024 & 0.459438 \tabularnewline
39 & -0.06614 & -0.4582 & 0.324428 \tabularnewline
40 & 0.056077 & 0.3885 & 0.349678 \tabularnewline
41 & 0.069361 & 0.4805 & 0.316512 \tabularnewline
42 & -0.022977 & -0.1592 & 0.437095 \tabularnewline
43 & -0.004061 & -0.0281 & 0.488834 \tabularnewline
44 & 0.019298 & 0.1337 & 0.447098 \tabularnewline
45 & 0.002601 & 0.018 & 0.492848 \tabularnewline
46 & -0.003875 & -0.0268 & 0.489347 \tabularnewline
47 & 0.002889 & 0.02 & 0.492058 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60623&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]-0.359702[/C][C]-2.4921[/C][C]0.008103[/C][/ROW]
[ROW][C]2[/C][C]-0.043887[/C][C]-0.3041[/C][C]0.381199[/C][/ROW]
[ROW][C]3[/C][C]0.314529[/C][C]2.1791[/C][C]0.017131[/C][/ROW]
[ROW][C]4[/C][C]-0.193175[/C][C]-1.3384[/C][C]0.093543[/C][/ROW]
[ROW][C]5[/C][C]0.019842[/C][C]0.1375[/C][C]0.445618[/C][/ROW]
[ROW][C]6[/C][C]0.129126[/C][C]0.8946[/C][C]0.187729[/C][/ROW]
[ROW][C]7[/C][C]-0.135308[/C][C]-0.9374[/C][C]0.176613[/C][/ROW]
[ROW][C]8[/C][C]-0.096373[/C][C]-0.6677[/C][C]0.253764[/C][/ROW]
[ROW][C]9[/C][C]0.168727[/C][C]1.169[/C][C]0.124093[/C][/ROW]
[ROW][C]10[/C][C]-0.082649[/C][C]-0.5726[/C][C]0.284791[/C][/ROW]
[ROW][C]11[/C][C]-0.065908[/C][C]-0.4566[/C][C]0.325001[/C][/ROW]
[ROW][C]12[/C][C]0.115571[/C][C]0.8007[/C][C]0.213626[/C][/ROW]
[ROW][C]13[/C][C]-0.204149[/C][C]-1.4144[/C][C]0.081852[/C][/ROW]
[ROW][C]14[/C][C]0.219563[/C][C]1.5212[/C][C]0.067388[/C][/ROW]
[ROW][C]15[/C][C]-0.070795[/C][C]-0.4905[/C][C]0.313013[/C][/ROW]
[ROW][C]16[/C][C]-0.099951[/C][C]-0.6925[/C][C]0.245987[/C][/ROW]
[ROW][C]17[/C][C]0.00772[/C][C]0.0535[/C][C]0.478783[/C][/ROW]
[ROW][C]18[/C][C]-0.011812[/C][C]-0.0818[/C][C]0.467558[/C][/ROW]
[ROW][C]19[/C][C]-0.148832[/C][C]-1.0311[/C][C]0.153823[/C][/ROW]
[ROW][C]20[/C][C]0.122533[/C][C]0.8489[/C][C]0.200066[/C][/ROW]
[ROW][C]21[/C][C]-0.044056[/C][C]-0.3052[/C][C]0.380755[/C][/ROW]
[ROW][C]22[/C][C]-0.200985[/C][C]-1.3925[/C][C]0.0851[/C][/ROW]
[ROW][C]23[/C][C]0.225938[/C][C]1.5653[/C][C]0.062036[/C][/ROW]
[ROW][C]24[/C][C]-0.130113[/C][C]-0.9014[/C][C]0.185925[/C][/ROW]
[ROW][C]25[/C][C]-0.182615[/C][C]-1.2652[/C][C]0.105955[/C][/ROW]
[ROW][C]26[/C][C]0.272018[/C][C]1.8846[/C][C]0.032774[/C][/ROW]
[ROW][C]27[/C][C]-0.129577[/C][C]-0.8977[/C][C]0.186903[/C][/ROW]
[ROW][C]28[/C][C]-0.010414[/C][C]-0.0722[/C][C]0.471391[/C][/ROW]
[ROW][C]29[/C][C]0.138916[/C][C]0.9624[/C][C]0.170326[/C][/ROW]
[ROW][C]30[/C][C]-0.056031[/C][C]-0.3882[/C][C]0.349793[/C][/ROW]
[ROW][C]31[/C][C]-0.015859[/C][C]-0.1099[/C][C]0.456484[/C][/ROW]
[ROW][C]32[/C][C]0.080212[/C][C]0.5557[/C][C]0.290489[/C][/ROW]
[ROW][C]33[/C][C]-0.050379[/C][C]-0.349[/C][C]0.364293[/C][/ROW]
[ROW][C]34[/C][C]-0.037329[/C][C]-0.2586[/C][C]0.398515[/C][/ROW]
[ROW][C]35[/C][C]0.034911[/C][C]0.2419[/C][C]0.404954[/C][/ROW]
[ROW][C]36[/C][C]-0.063919[/C][C]-0.4428[/C][C]0.329933[/C][/ROW]
[ROW][C]37[/C][C]0.016261[/C][C]0.1127[/C][C]0.455386[/C][/ROW]
[ROW][C]38[/C][C]0.014778[/C][C]0.1024[/C][C]0.459438[/C][/ROW]
[ROW][C]39[/C][C]-0.06614[/C][C]-0.4582[/C][C]0.324428[/C][/ROW]
[ROW][C]40[/C][C]0.056077[/C][C]0.3885[/C][C]0.349678[/C][/ROW]
[ROW][C]41[/C][C]0.069361[/C][C]0.4805[/C][C]0.316512[/C][/ROW]
[ROW][C]42[/C][C]-0.022977[/C][C]-0.1592[/C][C]0.437095[/C][/ROW]
[ROW][C]43[/C][C]-0.004061[/C][C]-0.0281[/C][C]0.488834[/C][/ROW]
[ROW][C]44[/C][C]0.019298[/C][C]0.1337[/C][C]0.447098[/C][/ROW]
[ROW][C]45[/C][C]0.002601[/C][C]0.018[/C][C]0.492848[/C][/ROW]
[ROW][C]46[/C][C]-0.003875[/C][C]-0.0268[/C][C]0.489347[/C][/ROW]
[ROW][C]47[/C][C]0.002889[/C][C]0.02[/C][C]0.492058[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/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=60623&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60623&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
1-0.359702-2.49210.008103
2-0.043887-0.30410.381199
30.3145292.17910.017131
4-0.193175-1.33840.093543
50.0198420.13750.445618
60.1291260.89460.187729
7-0.135308-0.93740.176613
8-0.096373-0.66770.253764
90.1687271.1690.124093
10-0.082649-0.57260.284791
11-0.065908-0.45660.325001
120.1155710.80070.213626
13-0.204149-1.41440.081852
140.2195631.52120.067388
15-0.070795-0.49050.313013
16-0.099951-0.69250.245987
170.007720.05350.478783
18-0.011812-0.08180.467558
19-0.148832-1.03110.153823
200.1225330.84890.200066
21-0.044056-0.30520.380755
22-0.200985-1.39250.0851
230.2259381.56530.062036
24-0.130113-0.90140.185925
25-0.182615-1.26520.105955
260.2720181.88460.032774
27-0.129577-0.89770.186903
28-0.010414-0.07220.471391
290.1389160.96240.170326
30-0.056031-0.38820.349793
31-0.015859-0.10990.456484
320.0802120.55570.290489
33-0.050379-0.3490.364293
34-0.037329-0.25860.398515
350.0349110.24190.404954
36-0.063919-0.44280.329933
370.0162610.11270.455386
380.0147780.10240.459438
39-0.06614-0.45820.324428
400.0560770.38850.349678
410.0693610.48050.316512
42-0.022977-0.15920.437095
43-0.004061-0.02810.488834
440.0192980.13370.447098
450.0026010.0180.492848
46-0.003875-0.02680.489347
470.0028890.020.492058
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.359702-2.49210.008103
2-0.199024-1.37890.087163
30.2679151.85620.034787
40.0237250.16440.435063
5-0.01042-0.07220.471374
60.0410770.28460.388592
7-0.032634-0.22610.411043
8-0.191853-1.32920.095034
90.0251250.17410.431272
100.0544550.37730.353815
11-0.011026-0.07640.469714
120.0022270.01540.493876
13-0.17503-1.21260.1156
140.1801761.24830.108989
15-0.017526-0.12140.45193
16-0.048907-0.33880.368104
17-0.186598-1.29280.101137
18-0.036822-0.25510.399863
19-0.191825-1.3290.095065
200.0481680.33370.370023
210.0070850.04910.480526
22-0.099561-0.68980.246827
230.0199210.1380.445403
24-0.120589-0.83550.203797
25-0.208685-1.44580.077364
260.024630.17060.432612
270.0998220.69160.246265
280.0420050.2910.386144
290.010360.07180.471539
30-0.030009-0.20790.41809
310.0615430.42640.335867
32-0.086462-0.5990.275986
33-0.029231-0.20250.420185
34-0.068-0.47110.319845
35-0.097704-0.67690.250855
36-0.103286-0.71560.238856
37-0.047714-0.33060.371204
38-0.006803-0.04710.481301
390.0305810.21190.416553
40-0.066545-0.4610.323426
410.0008650.0060.497622
420.0289270.20040.421003
43-0.093911-0.65060.259192
44-0.093378-0.64690.260376
450.072310.5010.309338
46-0.011378-0.07880.468749
47-0.059022-0.40890.342209
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.359702 & -2.4921 & 0.008103 \tabularnewline
2 & -0.199024 & -1.3789 & 0.087163 \tabularnewline
3 & 0.267915 & 1.8562 & 0.034787 \tabularnewline
4 & 0.023725 & 0.1644 & 0.435063 \tabularnewline
5 & -0.01042 & -0.0722 & 0.471374 \tabularnewline
6 & 0.041077 & 0.2846 & 0.388592 \tabularnewline
7 & -0.032634 & -0.2261 & 0.411043 \tabularnewline
8 & -0.191853 & -1.3292 & 0.095034 \tabularnewline
9 & 0.025125 & 0.1741 & 0.431272 \tabularnewline
10 & 0.054455 & 0.3773 & 0.353815 \tabularnewline
11 & -0.011026 & -0.0764 & 0.469714 \tabularnewline
12 & 0.002227 & 0.0154 & 0.493876 \tabularnewline
13 & -0.17503 & -1.2126 & 0.1156 \tabularnewline
14 & 0.180176 & 1.2483 & 0.108989 \tabularnewline
15 & -0.017526 & -0.1214 & 0.45193 \tabularnewline
16 & -0.048907 & -0.3388 & 0.368104 \tabularnewline
17 & -0.186598 & -1.2928 & 0.101137 \tabularnewline
18 & -0.036822 & -0.2551 & 0.399863 \tabularnewline
19 & -0.191825 & -1.329 & 0.095065 \tabularnewline
20 & 0.048168 & 0.3337 & 0.370023 \tabularnewline
21 & 0.007085 & 0.0491 & 0.480526 \tabularnewline
22 & -0.099561 & -0.6898 & 0.246827 \tabularnewline
23 & 0.019921 & 0.138 & 0.445403 \tabularnewline
24 & -0.120589 & -0.8355 & 0.203797 \tabularnewline
25 & -0.208685 & -1.4458 & 0.077364 \tabularnewline
26 & 0.02463 & 0.1706 & 0.432612 \tabularnewline
27 & 0.099822 & 0.6916 & 0.246265 \tabularnewline
28 & 0.042005 & 0.291 & 0.386144 \tabularnewline
29 & 0.01036 & 0.0718 & 0.471539 \tabularnewline
30 & -0.030009 & -0.2079 & 0.41809 \tabularnewline
31 & 0.061543 & 0.4264 & 0.335867 \tabularnewline
32 & -0.086462 & -0.599 & 0.275986 \tabularnewline
33 & -0.029231 & -0.2025 & 0.420185 \tabularnewline
34 & -0.068 & -0.4711 & 0.319845 \tabularnewline
35 & -0.097704 & -0.6769 & 0.250855 \tabularnewline
36 & -0.103286 & -0.7156 & 0.238856 \tabularnewline
37 & -0.047714 & -0.3306 & 0.371204 \tabularnewline
38 & -0.006803 & -0.0471 & 0.481301 \tabularnewline
39 & 0.030581 & 0.2119 & 0.416553 \tabularnewline
40 & -0.066545 & -0.461 & 0.323426 \tabularnewline
41 & 0.000865 & 0.006 & 0.497622 \tabularnewline
42 & 0.028927 & 0.2004 & 0.421003 \tabularnewline
43 & -0.093911 & -0.6506 & 0.259192 \tabularnewline
44 & -0.093378 & -0.6469 & 0.260376 \tabularnewline
45 & 0.07231 & 0.501 & 0.309338 \tabularnewline
46 & -0.011378 & -0.0788 & 0.468749 \tabularnewline
47 & -0.059022 & -0.4089 & 0.342209 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60623&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]-0.359702[/C][C]-2.4921[/C][C]0.008103[/C][/ROW]
[ROW][C]2[/C][C]-0.199024[/C][C]-1.3789[/C][C]0.087163[/C][/ROW]
[ROW][C]3[/C][C]0.267915[/C][C]1.8562[/C][C]0.034787[/C][/ROW]
[ROW][C]4[/C][C]0.023725[/C][C]0.1644[/C][C]0.435063[/C][/ROW]
[ROW][C]5[/C][C]-0.01042[/C][C]-0.0722[/C][C]0.471374[/C][/ROW]
[ROW][C]6[/C][C]0.041077[/C][C]0.2846[/C][C]0.388592[/C][/ROW]
[ROW][C]7[/C][C]-0.032634[/C][C]-0.2261[/C][C]0.411043[/C][/ROW]
[ROW][C]8[/C][C]-0.191853[/C][C]-1.3292[/C][C]0.095034[/C][/ROW]
[ROW][C]9[/C][C]0.025125[/C][C]0.1741[/C][C]0.431272[/C][/ROW]
[ROW][C]10[/C][C]0.054455[/C][C]0.3773[/C][C]0.353815[/C][/ROW]
[ROW][C]11[/C][C]-0.011026[/C][C]-0.0764[/C][C]0.469714[/C][/ROW]
[ROW][C]12[/C][C]0.002227[/C][C]0.0154[/C][C]0.493876[/C][/ROW]
[ROW][C]13[/C][C]-0.17503[/C][C]-1.2126[/C][C]0.1156[/C][/ROW]
[ROW][C]14[/C][C]0.180176[/C][C]1.2483[/C][C]0.108989[/C][/ROW]
[ROW][C]15[/C][C]-0.017526[/C][C]-0.1214[/C][C]0.45193[/C][/ROW]
[ROW][C]16[/C][C]-0.048907[/C][C]-0.3388[/C][C]0.368104[/C][/ROW]
[ROW][C]17[/C][C]-0.186598[/C][C]-1.2928[/C][C]0.101137[/C][/ROW]
[ROW][C]18[/C][C]-0.036822[/C][C]-0.2551[/C][C]0.399863[/C][/ROW]
[ROW][C]19[/C][C]-0.191825[/C][C]-1.329[/C][C]0.095065[/C][/ROW]
[ROW][C]20[/C][C]0.048168[/C][C]0.3337[/C][C]0.370023[/C][/ROW]
[ROW][C]21[/C][C]0.007085[/C][C]0.0491[/C][C]0.480526[/C][/ROW]
[ROW][C]22[/C][C]-0.099561[/C][C]-0.6898[/C][C]0.246827[/C][/ROW]
[ROW][C]23[/C][C]0.019921[/C][C]0.138[/C][C]0.445403[/C][/ROW]
[ROW][C]24[/C][C]-0.120589[/C][C]-0.8355[/C][C]0.203797[/C][/ROW]
[ROW][C]25[/C][C]-0.208685[/C][C]-1.4458[/C][C]0.077364[/C][/ROW]
[ROW][C]26[/C][C]0.02463[/C][C]0.1706[/C][C]0.432612[/C][/ROW]
[ROW][C]27[/C][C]0.099822[/C][C]0.6916[/C][C]0.246265[/C][/ROW]
[ROW][C]28[/C][C]0.042005[/C][C]0.291[/C][C]0.386144[/C][/ROW]
[ROW][C]29[/C][C]0.01036[/C][C]0.0718[/C][C]0.471539[/C][/ROW]
[ROW][C]30[/C][C]-0.030009[/C][C]-0.2079[/C][C]0.41809[/C][/ROW]
[ROW][C]31[/C][C]0.061543[/C][C]0.4264[/C][C]0.335867[/C][/ROW]
[ROW][C]32[/C][C]-0.086462[/C][C]-0.599[/C][C]0.275986[/C][/ROW]
[ROW][C]33[/C][C]-0.029231[/C][C]-0.2025[/C][C]0.420185[/C][/ROW]
[ROW][C]34[/C][C]-0.068[/C][C]-0.4711[/C][C]0.319845[/C][/ROW]
[ROW][C]35[/C][C]-0.097704[/C][C]-0.6769[/C][C]0.250855[/C][/ROW]
[ROW][C]36[/C][C]-0.103286[/C][C]-0.7156[/C][C]0.238856[/C][/ROW]
[ROW][C]37[/C][C]-0.047714[/C][C]-0.3306[/C][C]0.371204[/C][/ROW]
[ROW][C]38[/C][C]-0.006803[/C][C]-0.0471[/C][C]0.481301[/C][/ROW]
[ROW][C]39[/C][C]0.030581[/C][C]0.2119[/C][C]0.416553[/C][/ROW]
[ROW][C]40[/C][C]-0.066545[/C][C]-0.461[/C][C]0.323426[/C][/ROW]
[ROW][C]41[/C][C]0.000865[/C][C]0.006[/C][C]0.497622[/C][/ROW]
[ROW][C]42[/C][C]0.028927[/C][C]0.2004[/C][C]0.421003[/C][/ROW]
[ROW][C]43[/C][C]-0.093911[/C][C]-0.6506[/C][C]0.259192[/C][/ROW]
[ROW][C]44[/C][C]-0.093378[/C][C]-0.6469[/C][C]0.260376[/C][/ROW]
[ROW][C]45[/C][C]0.07231[/C][C]0.501[/C][C]0.309338[/C][/ROW]
[ROW][C]46[/C][C]-0.011378[/C][C]-0.0788[/C][C]0.468749[/C][/ROW]
[ROW][C]47[/C][C]-0.059022[/C][C]-0.4089[/C][C]0.342209[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/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=60623&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60623&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
1-0.359702-2.49210.008103
2-0.199024-1.37890.087163
30.2679151.85620.034787
40.0237250.16440.435063
5-0.01042-0.07220.471374
60.0410770.28460.388592
7-0.032634-0.22610.411043
8-0.191853-1.32920.095034
90.0251250.17410.431272
100.0544550.37730.353815
11-0.011026-0.07640.469714
120.0022270.01540.493876
13-0.17503-1.21260.1156
140.1801761.24830.108989
15-0.017526-0.12140.45193
16-0.048907-0.33880.368104
17-0.186598-1.29280.101137
18-0.036822-0.25510.399863
19-0.191825-1.3290.095065
200.0481680.33370.370023
210.0070850.04910.480526
22-0.099561-0.68980.246827
230.0199210.1380.445403
24-0.120589-0.83550.203797
25-0.208685-1.44580.077364
260.024630.17060.432612
270.0998220.69160.246265
280.0420050.2910.386144
290.010360.07180.471539
30-0.030009-0.20790.41809
310.0615430.42640.335867
32-0.086462-0.5990.275986
33-0.029231-0.20250.420185
34-0.068-0.47110.319845
35-0.097704-0.67690.250855
36-0.103286-0.71560.238856
37-0.047714-0.33060.371204
38-0.006803-0.04710.481301
390.0305810.21190.416553
40-0.066545-0.4610.323426
410.0008650.0060.497622
420.0289270.20040.421003
43-0.093911-0.65060.259192
44-0.093378-0.64690.260376
450.072310.5010.309338
46-0.011378-0.07880.468749
47-0.059022-0.40890.342209
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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')