Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 03 May 2010 17:25:04 +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/May/03/t1272907796eyf9gi5iz2hojew.htm/, Retrieved Fri, 29 Mar 2024 07:57:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75265, Retrieved Fri, 29 Mar 2024 07:57:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2010-05-03 17:25:04] [c51d2a758763dfb1938fc52f7893fda4] [Current]
Feedback Forum

Post a new message
Dataseries X:
132.8
132.5
131.4
131.4
130.7
131.5
131.2
130.1
130.5
129
128.2
128.4
127.3
127.7
127
123.9
125.4
124.6
124.5
124.8
124.1
124.2
122.8
122.3
121.1
121.7
122.2
122.2
122.7
121.7
121
119.8
120.2
116.6
116
118
117.1
116.2
113.3
114.3
113.6
113
112.9
112.7
112.5
113
111.9
110.9
109.8
108.3
109.2
109.2
108.7
109.8
110.8
110
109.6
109.5
110.8
111.6
113.1
114.3
114.1
113.8
112.6
112.7
111.5
110.7
110.4
109.7
110
111.3
109
108.2
107.2
108.7
110.3
110.3
109.5
109.5
109.4
109.6
111.3
110
109.5
110.693
109.195
108.095
108.199
106.87
105.278
108.711
111.192
109.641
109.42
109.935
111.126
110.733
110.34
111.766
111.294
111.54
112.008
111.007
114.963
112.045
110.703
108.894
107.51
111.35
112.964
115.203
115.182
115.191
112.346
110.774
113.07
111.138
109.092
107.971
107.051




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75265&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75265&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75265&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95393410.49330
20.90959410.00550
30.871899.59080
40.8362699.1990
50.8094448.90390
60.7738328.51210
70.7422978.16530
80.7129017.84190
90.6825737.50830
100.6555877.21150
110.6271326.89840
120.5970016.5670
130.5629396.19230
140.5298695.82860
150.5015415.5170
160.4823345.30570
170.4613635.0751e-06
180.4348614.78352e-06
190.4067354.47419e-06
200.3753794.12923.4e-05
210.3458713.80460.000112
220.3153533.46890.000362
230.2875713.16330.000986
240.2642552.90680.002172
250.2426072.66870.00433
260.2166282.38290.009367
270.1892292.08150.019748
280.1639421.80340.03691
290.1384121.52250.065243
300.111691.22860.110804
310.0849550.93450.175951
320.0586970.64570.259859
330.0336120.36970.356114
340.0171850.1890.425192
35-0.002721-0.02990.488084
36-0.026915-0.29610.383845
37-0.050574-0.55630.289512
38-0.069229-0.76150.223916
39-0.07662-0.84280.200496
40-0.089168-0.98090.164312
41-0.102661-1.12930.13051
42-0.117954-1.29750.098465
43-0.133117-1.46430.072855
44-0.14474-1.59210.056981
45-0.152749-1.68020.047746
46-0.164495-1.80940.036432
47-0.175606-1.93170.02787
48-0.180567-1.98620.024634

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953934 & 10.4933 & 0 \tabularnewline
2 & 0.909594 & 10.0055 & 0 \tabularnewline
3 & 0.87189 & 9.5908 & 0 \tabularnewline
4 & 0.836269 & 9.199 & 0 \tabularnewline
5 & 0.809444 & 8.9039 & 0 \tabularnewline
6 & 0.773832 & 8.5121 & 0 \tabularnewline
7 & 0.742297 & 8.1653 & 0 \tabularnewline
8 & 0.712901 & 7.8419 & 0 \tabularnewline
9 & 0.682573 & 7.5083 & 0 \tabularnewline
10 & 0.655587 & 7.2115 & 0 \tabularnewline
11 & 0.627132 & 6.8984 & 0 \tabularnewline
12 & 0.597001 & 6.567 & 0 \tabularnewline
13 & 0.562939 & 6.1923 & 0 \tabularnewline
14 & 0.529869 & 5.8286 & 0 \tabularnewline
15 & 0.501541 & 5.517 & 0 \tabularnewline
16 & 0.482334 & 5.3057 & 0 \tabularnewline
17 & 0.461363 & 5.075 & 1e-06 \tabularnewline
18 & 0.434861 & 4.7835 & 2e-06 \tabularnewline
19 & 0.406735 & 4.4741 & 9e-06 \tabularnewline
20 & 0.375379 & 4.1292 & 3.4e-05 \tabularnewline
21 & 0.345871 & 3.8046 & 0.000112 \tabularnewline
22 & 0.315353 & 3.4689 & 0.000362 \tabularnewline
23 & 0.287571 & 3.1633 & 0.000986 \tabularnewline
24 & 0.264255 & 2.9068 & 0.002172 \tabularnewline
25 & 0.242607 & 2.6687 & 0.00433 \tabularnewline
26 & 0.216628 & 2.3829 & 0.009367 \tabularnewline
27 & 0.189229 & 2.0815 & 0.019748 \tabularnewline
28 & 0.163942 & 1.8034 & 0.03691 \tabularnewline
29 & 0.138412 & 1.5225 & 0.065243 \tabularnewline
30 & 0.11169 & 1.2286 & 0.110804 \tabularnewline
31 & 0.084955 & 0.9345 & 0.175951 \tabularnewline
32 & 0.058697 & 0.6457 & 0.259859 \tabularnewline
33 & 0.033612 & 0.3697 & 0.356114 \tabularnewline
34 & 0.017185 & 0.189 & 0.425192 \tabularnewline
35 & -0.002721 & -0.0299 & 0.488084 \tabularnewline
36 & -0.026915 & -0.2961 & 0.383845 \tabularnewline
37 & -0.050574 & -0.5563 & 0.289512 \tabularnewline
38 & -0.069229 & -0.7615 & 0.223916 \tabularnewline
39 & -0.07662 & -0.8428 & 0.200496 \tabularnewline
40 & -0.089168 & -0.9809 & 0.164312 \tabularnewline
41 & -0.102661 & -1.1293 & 0.13051 \tabularnewline
42 & -0.117954 & -1.2975 & 0.098465 \tabularnewline
43 & -0.133117 & -1.4643 & 0.072855 \tabularnewline
44 & -0.14474 & -1.5921 & 0.056981 \tabularnewline
45 & -0.152749 & -1.6802 & 0.047746 \tabularnewline
46 & -0.164495 & -1.8094 & 0.036432 \tabularnewline
47 & -0.175606 & -1.9317 & 0.02787 \tabularnewline
48 & -0.180567 & -1.9862 & 0.024634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75265&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]0.953934[/C][C]10.4933[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.909594[/C][C]10.0055[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.87189[/C][C]9.5908[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.836269[/C][C]9.199[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.809444[/C][C]8.9039[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.773832[/C][C]8.5121[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.742297[/C][C]8.1653[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.712901[/C][C]7.8419[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.682573[/C][C]7.5083[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.655587[/C][C]7.2115[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.627132[/C][C]6.8984[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.597001[/C][C]6.567[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.562939[/C][C]6.1923[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.529869[/C][C]5.8286[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.501541[/C][C]5.517[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.482334[/C][C]5.3057[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.461363[/C][C]5.075[/C][C]1e-06[/C][/ROW]
[ROW][C]18[/C][C]0.434861[/C][C]4.7835[/C][C]2e-06[/C][/ROW]
[ROW][C]19[/C][C]0.406735[/C][C]4.4741[/C][C]9e-06[/C][/ROW]
[ROW][C]20[/C][C]0.375379[/C][C]4.1292[/C][C]3.4e-05[/C][/ROW]
[ROW][C]21[/C][C]0.345871[/C][C]3.8046[/C][C]0.000112[/C][/ROW]
[ROW][C]22[/C][C]0.315353[/C][C]3.4689[/C][C]0.000362[/C][/ROW]
[ROW][C]23[/C][C]0.287571[/C][C]3.1633[/C][C]0.000986[/C][/ROW]
[ROW][C]24[/C][C]0.264255[/C][C]2.9068[/C][C]0.002172[/C][/ROW]
[ROW][C]25[/C][C]0.242607[/C][C]2.6687[/C][C]0.00433[/C][/ROW]
[ROW][C]26[/C][C]0.216628[/C][C]2.3829[/C][C]0.009367[/C][/ROW]
[ROW][C]27[/C][C]0.189229[/C][C]2.0815[/C][C]0.019748[/C][/ROW]
[ROW][C]28[/C][C]0.163942[/C][C]1.8034[/C][C]0.03691[/C][/ROW]
[ROW][C]29[/C][C]0.138412[/C][C]1.5225[/C][C]0.065243[/C][/ROW]
[ROW][C]30[/C][C]0.11169[/C][C]1.2286[/C][C]0.110804[/C][/ROW]
[ROW][C]31[/C][C]0.084955[/C][C]0.9345[/C][C]0.175951[/C][/ROW]
[ROW][C]32[/C][C]0.058697[/C][C]0.6457[/C][C]0.259859[/C][/ROW]
[ROW][C]33[/C][C]0.033612[/C][C]0.3697[/C][C]0.356114[/C][/ROW]
[ROW][C]34[/C][C]0.017185[/C][C]0.189[/C][C]0.425192[/C][/ROW]
[ROW][C]35[/C][C]-0.002721[/C][C]-0.0299[/C][C]0.488084[/C][/ROW]
[ROW][C]36[/C][C]-0.026915[/C][C]-0.2961[/C][C]0.383845[/C][/ROW]
[ROW][C]37[/C][C]-0.050574[/C][C]-0.5563[/C][C]0.289512[/C][/ROW]
[ROW][C]38[/C][C]-0.069229[/C][C]-0.7615[/C][C]0.223916[/C][/ROW]
[ROW][C]39[/C][C]-0.07662[/C][C]-0.8428[/C][C]0.200496[/C][/ROW]
[ROW][C]40[/C][C]-0.089168[/C][C]-0.9809[/C][C]0.164312[/C][/ROW]
[ROW][C]41[/C][C]-0.102661[/C][C]-1.1293[/C][C]0.13051[/C][/ROW]
[ROW][C]42[/C][C]-0.117954[/C][C]-1.2975[/C][C]0.098465[/C][/ROW]
[ROW][C]43[/C][C]-0.133117[/C][C]-1.4643[/C][C]0.072855[/C][/ROW]
[ROW][C]44[/C][C]-0.14474[/C][C]-1.5921[/C][C]0.056981[/C][/ROW]
[ROW][C]45[/C][C]-0.152749[/C][C]-1.6802[/C][C]0.047746[/C][/ROW]
[ROW][C]46[/C][C]-0.164495[/C][C]-1.8094[/C][C]0.036432[/C][/ROW]
[ROW][C]47[/C][C]-0.175606[/C][C]-1.9317[/C][C]0.02787[/C][/ROW]
[ROW][C]48[/C][C]-0.180567[/C][C]-1.9862[/C][C]0.024634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75265&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75265&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
10.95393410.49330
20.90959410.00550
30.871899.59080
40.8362699.1990
50.8094448.90390
60.7738328.51210
70.7422978.16530
80.7129017.84190
90.6825737.50830
100.6555877.21150
110.6271326.89840
120.5970016.5670
130.5629396.19230
140.5298695.82860
150.5015415.5170
160.4823345.30570
170.4613635.0751e-06
180.4348614.78352e-06
190.4067354.47419e-06
200.3753794.12923.4e-05
210.3458713.80460.000112
220.3153533.46890.000362
230.2875713.16330.000986
240.2642552.90680.002172
250.2426072.66870.00433
260.2166282.38290.009367
270.1892292.08150.019748
280.1639421.80340.03691
290.1384121.52250.065243
300.111691.22860.110804
310.0849550.93450.175951
320.0586970.64570.259859
330.0336120.36970.356114
340.0171850.1890.425192
35-0.002721-0.02990.488084
36-0.026915-0.29610.383845
37-0.050574-0.55630.289512
38-0.069229-0.76150.223916
39-0.07662-0.84280.200496
40-0.089168-0.98090.164312
41-0.102661-1.12930.13051
42-0.117954-1.29750.098465
43-0.133117-1.46430.072855
44-0.14474-1.59210.056981
45-0.152749-1.68020.047746
46-0.164495-1.80940.036432
47-0.175606-1.93170.02787
48-0.180567-1.98620.024634







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95393410.49330
2-0.004391-0.04830.480777
30.0508420.55930.288508
40.0055670.06120.475638
50.0845030.92950.177232
6-0.106692-1.17360.121427
70.0387530.42630.335328
8-0.002605-0.02870.488592
9-0.013691-0.15060.440272
100.0062480.06870.47266
11-0.013867-0.15250.439507
12-0.037686-0.41450.339606
13-0.065312-0.71840.236937
14-0.005325-0.05860.476693
150.0182530.20080.420604
160.0863180.94950.172131
17-0.030618-0.33680.368426
18-0.05344-0.58780.278868
19-0.035388-0.38930.348882
20-0.054303-0.59730.275701
21-0.023014-0.25320.400288
22-0.035848-0.39430.347017
230.0190340.20940.417255
240.0221890.24410.403793
250.0173170.19050.424623
26-0.074748-0.82220.206281
27-0.035107-0.38620.350022
28-0.011502-0.12650.449765
29-0.022512-0.24760.402421
30-0.027545-0.3030.381206
31-0.003824-0.04210.483258
32-0.02028-0.22310.411923
33-0.029272-0.3220.374007
340.0731860.80510.211185
35-0.066738-0.73410.232149
36-0.060535-0.66590.253375
37-0.017453-0.1920.42404
380.0628080.69090.245481
390.0999951.09990.13677
40-0.060216-0.66240.254494
41-0.020267-0.22290.411981
42-0.049796-0.54780.292433
430.0003550.00390.498447
44-0.013874-0.15260.439478
450.0492650.54190.294435
46-0.06186-0.68050.248755
470.0160340.17640.430147
480.0694040.76340.223342

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953934 & 10.4933 & 0 \tabularnewline
2 & -0.004391 & -0.0483 & 0.480777 \tabularnewline
3 & 0.050842 & 0.5593 & 0.288508 \tabularnewline
4 & 0.005567 & 0.0612 & 0.475638 \tabularnewline
5 & 0.084503 & 0.9295 & 0.177232 \tabularnewline
6 & -0.106692 & -1.1736 & 0.121427 \tabularnewline
7 & 0.038753 & 0.4263 & 0.335328 \tabularnewline
8 & -0.002605 & -0.0287 & 0.488592 \tabularnewline
9 & -0.013691 & -0.1506 & 0.440272 \tabularnewline
10 & 0.006248 & 0.0687 & 0.47266 \tabularnewline
11 & -0.013867 & -0.1525 & 0.439507 \tabularnewline
12 & -0.037686 & -0.4145 & 0.339606 \tabularnewline
13 & -0.065312 & -0.7184 & 0.236937 \tabularnewline
14 & -0.005325 & -0.0586 & 0.476693 \tabularnewline
15 & 0.018253 & 0.2008 & 0.420604 \tabularnewline
16 & 0.086318 & 0.9495 & 0.172131 \tabularnewline
17 & -0.030618 & -0.3368 & 0.368426 \tabularnewline
18 & -0.05344 & -0.5878 & 0.278868 \tabularnewline
19 & -0.035388 & -0.3893 & 0.348882 \tabularnewline
20 & -0.054303 & -0.5973 & 0.275701 \tabularnewline
21 & -0.023014 & -0.2532 & 0.400288 \tabularnewline
22 & -0.035848 & -0.3943 & 0.347017 \tabularnewline
23 & 0.019034 & 0.2094 & 0.417255 \tabularnewline
24 & 0.022189 & 0.2441 & 0.403793 \tabularnewline
25 & 0.017317 & 0.1905 & 0.424623 \tabularnewline
26 & -0.074748 & -0.8222 & 0.206281 \tabularnewline
27 & -0.035107 & -0.3862 & 0.350022 \tabularnewline
28 & -0.011502 & -0.1265 & 0.449765 \tabularnewline
29 & -0.022512 & -0.2476 & 0.402421 \tabularnewline
30 & -0.027545 & -0.303 & 0.381206 \tabularnewline
31 & -0.003824 & -0.0421 & 0.483258 \tabularnewline
32 & -0.02028 & -0.2231 & 0.411923 \tabularnewline
33 & -0.029272 & -0.322 & 0.374007 \tabularnewline
34 & 0.073186 & 0.8051 & 0.211185 \tabularnewline
35 & -0.066738 & -0.7341 & 0.232149 \tabularnewline
36 & -0.060535 & -0.6659 & 0.253375 \tabularnewline
37 & -0.017453 & -0.192 & 0.42404 \tabularnewline
38 & 0.062808 & 0.6909 & 0.245481 \tabularnewline
39 & 0.099995 & 1.0999 & 0.13677 \tabularnewline
40 & -0.060216 & -0.6624 & 0.254494 \tabularnewline
41 & -0.020267 & -0.2229 & 0.411981 \tabularnewline
42 & -0.049796 & -0.5478 & 0.292433 \tabularnewline
43 & 0.000355 & 0.0039 & 0.498447 \tabularnewline
44 & -0.013874 & -0.1526 & 0.439478 \tabularnewline
45 & 0.049265 & 0.5419 & 0.294435 \tabularnewline
46 & -0.06186 & -0.6805 & 0.248755 \tabularnewline
47 & 0.016034 & 0.1764 & 0.430147 \tabularnewline
48 & 0.069404 & 0.7634 & 0.223342 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75265&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]0.953934[/C][C]10.4933[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.004391[/C][C]-0.0483[/C][C]0.480777[/C][/ROW]
[ROW][C]3[/C][C]0.050842[/C][C]0.5593[/C][C]0.288508[/C][/ROW]
[ROW][C]4[/C][C]0.005567[/C][C]0.0612[/C][C]0.475638[/C][/ROW]
[ROW][C]5[/C][C]0.084503[/C][C]0.9295[/C][C]0.177232[/C][/ROW]
[ROW][C]6[/C][C]-0.106692[/C][C]-1.1736[/C][C]0.121427[/C][/ROW]
[ROW][C]7[/C][C]0.038753[/C][C]0.4263[/C][C]0.335328[/C][/ROW]
[ROW][C]8[/C][C]-0.002605[/C][C]-0.0287[/C][C]0.488592[/C][/ROW]
[ROW][C]9[/C][C]-0.013691[/C][C]-0.1506[/C][C]0.440272[/C][/ROW]
[ROW][C]10[/C][C]0.006248[/C][C]0.0687[/C][C]0.47266[/C][/ROW]
[ROW][C]11[/C][C]-0.013867[/C][C]-0.1525[/C][C]0.439507[/C][/ROW]
[ROW][C]12[/C][C]-0.037686[/C][C]-0.4145[/C][C]0.339606[/C][/ROW]
[ROW][C]13[/C][C]-0.065312[/C][C]-0.7184[/C][C]0.236937[/C][/ROW]
[ROW][C]14[/C][C]-0.005325[/C][C]-0.0586[/C][C]0.476693[/C][/ROW]
[ROW][C]15[/C][C]0.018253[/C][C]0.2008[/C][C]0.420604[/C][/ROW]
[ROW][C]16[/C][C]0.086318[/C][C]0.9495[/C][C]0.172131[/C][/ROW]
[ROW][C]17[/C][C]-0.030618[/C][C]-0.3368[/C][C]0.368426[/C][/ROW]
[ROW][C]18[/C][C]-0.05344[/C][C]-0.5878[/C][C]0.278868[/C][/ROW]
[ROW][C]19[/C][C]-0.035388[/C][C]-0.3893[/C][C]0.348882[/C][/ROW]
[ROW][C]20[/C][C]-0.054303[/C][C]-0.5973[/C][C]0.275701[/C][/ROW]
[ROW][C]21[/C][C]-0.023014[/C][C]-0.2532[/C][C]0.400288[/C][/ROW]
[ROW][C]22[/C][C]-0.035848[/C][C]-0.3943[/C][C]0.347017[/C][/ROW]
[ROW][C]23[/C][C]0.019034[/C][C]0.2094[/C][C]0.417255[/C][/ROW]
[ROW][C]24[/C][C]0.022189[/C][C]0.2441[/C][C]0.403793[/C][/ROW]
[ROW][C]25[/C][C]0.017317[/C][C]0.1905[/C][C]0.424623[/C][/ROW]
[ROW][C]26[/C][C]-0.074748[/C][C]-0.8222[/C][C]0.206281[/C][/ROW]
[ROW][C]27[/C][C]-0.035107[/C][C]-0.3862[/C][C]0.350022[/C][/ROW]
[ROW][C]28[/C][C]-0.011502[/C][C]-0.1265[/C][C]0.449765[/C][/ROW]
[ROW][C]29[/C][C]-0.022512[/C][C]-0.2476[/C][C]0.402421[/C][/ROW]
[ROW][C]30[/C][C]-0.027545[/C][C]-0.303[/C][C]0.381206[/C][/ROW]
[ROW][C]31[/C][C]-0.003824[/C][C]-0.0421[/C][C]0.483258[/C][/ROW]
[ROW][C]32[/C][C]-0.02028[/C][C]-0.2231[/C][C]0.411923[/C][/ROW]
[ROW][C]33[/C][C]-0.029272[/C][C]-0.322[/C][C]0.374007[/C][/ROW]
[ROW][C]34[/C][C]0.073186[/C][C]0.8051[/C][C]0.211185[/C][/ROW]
[ROW][C]35[/C][C]-0.066738[/C][C]-0.7341[/C][C]0.232149[/C][/ROW]
[ROW][C]36[/C][C]-0.060535[/C][C]-0.6659[/C][C]0.253375[/C][/ROW]
[ROW][C]37[/C][C]-0.017453[/C][C]-0.192[/C][C]0.42404[/C][/ROW]
[ROW][C]38[/C][C]0.062808[/C][C]0.6909[/C][C]0.245481[/C][/ROW]
[ROW][C]39[/C][C]0.099995[/C][C]1.0999[/C][C]0.13677[/C][/ROW]
[ROW][C]40[/C][C]-0.060216[/C][C]-0.6624[/C][C]0.254494[/C][/ROW]
[ROW][C]41[/C][C]-0.020267[/C][C]-0.2229[/C][C]0.411981[/C][/ROW]
[ROW][C]42[/C][C]-0.049796[/C][C]-0.5478[/C][C]0.292433[/C][/ROW]
[ROW][C]43[/C][C]0.000355[/C][C]0.0039[/C][C]0.498447[/C][/ROW]
[ROW][C]44[/C][C]-0.013874[/C][C]-0.1526[/C][C]0.439478[/C][/ROW]
[ROW][C]45[/C][C]0.049265[/C][C]0.5419[/C][C]0.294435[/C][/ROW]
[ROW][C]46[/C][C]-0.06186[/C][C]-0.6805[/C][C]0.248755[/C][/ROW]
[ROW][C]47[/C][C]0.016034[/C][C]0.1764[/C][C]0.430147[/C][/ROW]
[ROW][C]48[/C][C]0.069404[/C][C]0.7634[/C][C]0.223342[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75265&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75265&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
10.95393410.49330
2-0.004391-0.04830.480777
30.0508420.55930.288508
40.0055670.06120.475638
50.0845030.92950.177232
6-0.106692-1.17360.121427
70.0387530.42630.335328
8-0.002605-0.02870.488592
9-0.013691-0.15060.440272
100.0062480.06870.47266
11-0.013867-0.15250.439507
12-0.037686-0.41450.339606
13-0.065312-0.71840.236937
14-0.005325-0.05860.476693
150.0182530.20080.420604
160.0863180.94950.172131
17-0.030618-0.33680.368426
18-0.05344-0.58780.278868
19-0.035388-0.38930.348882
20-0.054303-0.59730.275701
21-0.023014-0.25320.400288
22-0.035848-0.39430.347017
230.0190340.20940.417255
240.0221890.24410.403793
250.0173170.19050.424623
26-0.074748-0.82220.206281
27-0.035107-0.38620.350022
28-0.011502-0.12650.449765
29-0.022512-0.24760.402421
30-0.027545-0.3030.381206
31-0.003824-0.04210.483258
32-0.02028-0.22310.411923
33-0.029272-0.3220.374007
340.0731860.80510.211185
35-0.066738-0.73410.232149
36-0.060535-0.66590.253375
37-0.017453-0.1920.42404
380.0628080.69090.245481
390.0999951.09990.13677
40-0.060216-0.66240.254494
41-0.020267-0.22290.411981
42-0.049796-0.54780.292433
430.0003550.00390.498447
44-0.013874-0.15260.439478
450.0492650.54190.294435
46-0.06186-0.68050.248755
470.0160340.17640.430147
480.0694040.76340.223342



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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')