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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, 06 Aug 2015 09:58:25 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/06/t1438851640e4qg077v34uu42d.htm/, Retrieved Thu, 31 Oct 2024 22:48:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279865, Retrieved Thu, 31 Oct 2024 22:48:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2015-08-06 08:58:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
5947968,00
5925816,00
5903352,00
5856864,00
6316752,00
6292416,00
5947968,00
5718960,00
5741112,00
5741112,00
5765760,00
5810064,00
5879016,00
5879016,00
5834712,00
5718960,00
6316752,00
6407856,00
6270264,00
5947968,00
6085872,00
5879016,00
5972304,00
6016920,00
6063408,00
5947968,00
5972304,00
5810064,00
6316752,00
6476808,00
6339216,00
6085872,00
6361368,00
6063408,00
6339216,00
6316752,00
6385704,00
6132360,00
6407856,00
6385704,00
6799104,00
6705816,00
6339216,00
6154512,00
6407856,00
6063408,00
6316752,00
6361368,00
6454656,00
6248112,00
6361368,00
6430320,00
6683664,00
6476808,00
6201312,00
5903352,00
6179160,00
5421000,00
5787912,00
5994456,00
6201312,00
5903352,00
5903352,00
5903352,00
6063408,00
5834712,00
5534568,00
5283408,00
5465616,00
4754256,00
5190120,00
5443464,00
5489952,00
5236608,00
5258760,00
5190120,00
5421000,00
5258760,00
4938960,00
4707768,00
5098704,00
4249752,00
4801056,00
5052216,00
5052216,00
4754256,00
4478760,00
4456608,00
4707768,00
4478760,00
4043208,00
3743064,00
4065360,00
3307512,00
3996408,00
4363008,00
4478760,00
4225416,00
3905304,00
4134312,00
4225416,00
4156464,00
3467256,00
3147456,00
3376152,00
2687256,00
3398616,00
3651960,00
3858504,00
3514056,00
3191760,00
3376152,00
3467256,00
3285048,00
2596152,00
2296008,00
2571504,00
1813656,00
2640456,00
3147456,00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279865&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279865&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279865&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.94790310.38380
20.9052669.91670
30.8557299.3740
40.8262069.05060
50.785688.60670
60.7579688.30310
70.7361898.06450
80.7236547.92720
90.7031827.7030
100.6921027.58160
110.6875717.5320
120.7001337.66960
130.647967.0980
140.6088366.66950
150.5635126.1730
160.5363635.87560
170.4979735.4550
180.4738355.19060
190.4526914.9591e-06
200.440014.82012e-06
210.4182934.58226e-06
220.4033944.4191.1e-05
230.3933244.30871.7e-05
240.3968984.34781.4e-05
250.3480743.8130.000109
260.3117633.41520.000435
270.2687162.94360.001948
280.243362.66590.004369
290.2063782.26080.012788
300.1844192.02020.022794
310.1603371.75640.040785
320.1452791.59150.057069
330.119031.30390.09738
340.1022791.12040.132388
350.0881890.96610.167977
360.0855640.93730.17524
370.0421530.46180.322544
380.0125270.13720.445541
39-0.023121-0.25330.400243
40-0.042346-0.46390.321788
41-0.070055-0.76740.22217
42-0.081845-0.89660.185873
43-0.096617-1.05840.146003
44-0.105098-1.15130.125951
45-0.124959-1.36890.086801
46-0.136033-1.49020.069402
47-0.147634-1.61720.054226
48-0.152258-1.66790.048972

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947903 & 10.3838 & 0 \tabularnewline
2 & 0.905266 & 9.9167 & 0 \tabularnewline
3 & 0.855729 & 9.374 & 0 \tabularnewline
4 & 0.826206 & 9.0506 & 0 \tabularnewline
5 & 0.78568 & 8.6067 & 0 \tabularnewline
6 & 0.757968 & 8.3031 & 0 \tabularnewline
7 & 0.736189 & 8.0645 & 0 \tabularnewline
8 & 0.723654 & 7.9272 & 0 \tabularnewline
9 & 0.703182 & 7.703 & 0 \tabularnewline
10 & 0.692102 & 7.5816 & 0 \tabularnewline
11 & 0.687571 & 7.532 & 0 \tabularnewline
12 & 0.700133 & 7.6696 & 0 \tabularnewline
13 & 0.64796 & 7.098 & 0 \tabularnewline
14 & 0.608836 & 6.6695 & 0 \tabularnewline
15 & 0.563512 & 6.173 & 0 \tabularnewline
16 & 0.536363 & 5.8756 & 0 \tabularnewline
17 & 0.497973 & 5.455 & 0 \tabularnewline
18 & 0.473835 & 5.1906 & 0 \tabularnewline
19 & 0.452691 & 4.959 & 1e-06 \tabularnewline
20 & 0.44001 & 4.8201 & 2e-06 \tabularnewline
21 & 0.418293 & 4.5822 & 6e-06 \tabularnewline
22 & 0.403394 & 4.419 & 1.1e-05 \tabularnewline
23 & 0.393324 & 4.3087 & 1.7e-05 \tabularnewline
24 & 0.396898 & 4.3478 & 1.4e-05 \tabularnewline
25 & 0.348074 & 3.813 & 0.000109 \tabularnewline
26 & 0.311763 & 3.4152 & 0.000435 \tabularnewline
27 & 0.268716 & 2.9436 & 0.001948 \tabularnewline
28 & 0.24336 & 2.6659 & 0.004369 \tabularnewline
29 & 0.206378 & 2.2608 & 0.012788 \tabularnewline
30 & 0.184419 & 2.0202 & 0.022794 \tabularnewline
31 & 0.160337 & 1.7564 & 0.040785 \tabularnewline
32 & 0.145279 & 1.5915 & 0.057069 \tabularnewline
33 & 0.11903 & 1.3039 & 0.09738 \tabularnewline
34 & 0.102279 & 1.1204 & 0.132388 \tabularnewline
35 & 0.088189 & 0.9661 & 0.167977 \tabularnewline
36 & 0.085564 & 0.9373 & 0.17524 \tabularnewline
37 & 0.042153 & 0.4618 & 0.322544 \tabularnewline
38 & 0.012527 & 0.1372 & 0.445541 \tabularnewline
39 & -0.023121 & -0.2533 & 0.400243 \tabularnewline
40 & -0.042346 & -0.4639 & 0.321788 \tabularnewline
41 & -0.070055 & -0.7674 & 0.22217 \tabularnewline
42 & -0.081845 & -0.8966 & 0.185873 \tabularnewline
43 & -0.096617 & -1.0584 & 0.146003 \tabularnewline
44 & -0.105098 & -1.1513 & 0.125951 \tabularnewline
45 & -0.124959 & -1.3689 & 0.086801 \tabularnewline
46 & -0.136033 & -1.4902 & 0.069402 \tabularnewline
47 & -0.147634 & -1.6172 & 0.054226 \tabularnewline
48 & -0.152258 & -1.6679 & 0.048972 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279865&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]0.947903[/C][C]10.3838[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.905266[/C][C]9.9167[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.855729[/C][C]9.374[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.826206[/C][C]9.0506[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.78568[/C][C]8.6067[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.757968[/C][C]8.3031[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.736189[/C][C]8.0645[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.723654[/C][C]7.9272[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.703182[/C][C]7.703[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.692102[/C][C]7.5816[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.687571[/C][C]7.532[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.700133[/C][C]7.6696[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.64796[/C][C]7.098[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.608836[/C][C]6.6695[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.563512[/C][C]6.173[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.536363[/C][C]5.8756[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.497973[/C][C]5.455[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.473835[/C][C]5.1906[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.452691[/C][C]4.959[/C][C]1e-06[/C][/ROW]
[ROW][C]20[/C][C]0.44001[/C][C]4.8201[/C][C]2e-06[/C][/ROW]
[ROW][C]21[/C][C]0.418293[/C][C]4.5822[/C][C]6e-06[/C][/ROW]
[ROW][C]22[/C][C]0.403394[/C][C]4.419[/C][C]1.1e-05[/C][/ROW]
[ROW][C]23[/C][C]0.393324[/C][C]4.3087[/C][C]1.7e-05[/C][/ROW]
[ROW][C]24[/C][C]0.396898[/C][C]4.3478[/C][C]1.4e-05[/C][/ROW]
[ROW][C]25[/C][C]0.348074[/C][C]3.813[/C][C]0.000109[/C][/ROW]
[ROW][C]26[/C][C]0.311763[/C][C]3.4152[/C][C]0.000435[/C][/ROW]
[ROW][C]27[/C][C]0.268716[/C][C]2.9436[/C][C]0.001948[/C][/ROW]
[ROW][C]28[/C][C]0.24336[/C][C]2.6659[/C][C]0.004369[/C][/ROW]
[ROW][C]29[/C][C]0.206378[/C][C]2.2608[/C][C]0.012788[/C][/ROW]
[ROW][C]30[/C][C]0.184419[/C][C]2.0202[/C][C]0.022794[/C][/ROW]
[ROW][C]31[/C][C]0.160337[/C][C]1.7564[/C][C]0.040785[/C][/ROW]
[ROW][C]32[/C][C]0.145279[/C][C]1.5915[/C][C]0.057069[/C][/ROW]
[ROW][C]33[/C][C]0.11903[/C][C]1.3039[/C][C]0.09738[/C][/ROW]
[ROW][C]34[/C][C]0.102279[/C][C]1.1204[/C][C]0.132388[/C][/ROW]
[ROW][C]35[/C][C]0.088189[/C][C]0.9661[/C][C]0.167977[/C][/ROW]
[ROW][C]36[/C][C]0.085564[/C][C]0.9373[/C][C]0.17524[/C][/ROW]
[ROW][C]37[/C][C]0.042153[/C][C]0.4618[/C][C]0.322544[/C][/ROW]
[ROW][C]38[/C][C]0.012527[/C][C]0.1372[/C][C]0.445541[/C][/ROW]
[ROW][C]39[/C][C]-0.023121[/C][C]-0.2533[/C][C]0.400243[/C][/ROW]
[ROW][C]40[/C][C]-0.042346[/C][C]-0.4639[/C][C]0.321788[/C][/ROW]
[ROW][C]41[/C][C]-0.070055[/C][C]-0.7674[/C][C]0.22217[/C][/ROW]
[ROW][C]42[/C][C]-0.081845[/C][C]-0.8966[/C][C]0.185873[/C][/ROW]
[ROW][C]43[/C][C]-0.096617[/C][C]-1.0584[/C][C]0.146003[/C][/ROW]
[ROW][C]44[/C][C]-0.105098[/C][C]-1.1513[/C][C]0.125951[/C][/ROW]
[ROW][C]45[/C][C]-0.124959[/C][C]-1.3689[/C][C]0.086801[/C][/ROW]
[ROW][C]46[/C][C]-0.136033[/C][C]-1.4902[/C][C]0.069402[/C][/ROW]
[ROW][C]47[/C][C]-0.147634[/C][C]-1.6172[/C][C]0.054226[/C][/ROW]
[ROW][C]48[/C][C]-0.152258[/C][C]-1.6679[/C][C]0.048972[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279865&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279865&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
10.94790310.38380
20.9052669.91670
30.8557299.3740
40.8262069.05060
50.785688.60670
60.7579688.30310
70.7361898.06450
80.7236547.92720
90.7031827.7030
100.6921027.58160
110.6875717.5320
120.7001337.66960
130.647967.0980
140.6088366.66950
150.5635126.1730
160.5363635.87560
170.4979735.4550
180.4738355.19060
190.4526914.9591e-06
200.440014.82012e-06
210.4182934.58226e-06
220.4033944.4191.1e-05
230.3933244.30871.7e-05
240.3968984.34781.4e-05
250.3480743.8130.000109
260.3117633.41520.000435
270.2687162.94360.001948
280.243362.66590.004369
290.2063782.26080.012788
300.1844192.02020.022794
310.1603371.75640.040785
320.1452791.59150.057069
330.119031.30390.09738
340.1022791.12040.132388
350.0881890.96610.167977
360.0855640.93730.17524
370.0421530.46180.322544
380.0125270.13720.445541
39-0.023121-0.25330.400243
40-0.042346-0.46390.321788
41-0.070055-0.76740.22217
42-0.081845-0.89660.185873
43-0.096617-1.05840.146003
44-0.105098-1.15130.125951
45-0.124959-1.36890.086801
46-0.136033-1.49020.069402
47-0.147634-1.61720.054226
48-0.152258-1.66790.048972







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.94790310.38380
20.0664850.72830.233921
3-0.082604-0.90490.18367
40.1617561.77190.039471
5-0.095006-1.04070.150044
60.0752330.82410.205747
70.1033481.13210.129921
80.0490890.53770.295874
9-0.040338-0.44190.329684
100.0882590.96680.167786
110.1024121.12190.132079
120.1708631.87170.031841
13-0.617564-6.76510
140.1401171.53490.06372
150.0791090.86660.193946
16-0.101788-1.1150.133532
170.0628720.68870.246163
180.0384160.42080.337316
19-0.041005-0.44920.327054
200.026510.29040.386003
21-0.026507-0.29040.386017
220.0847270.92810.177601
23-0.085814-0.940.17454
24-0.059736-0.65440.257061
25-0.132117-1.44730.075215
260.0095640.10480.458367
270.0063860.070.472174
28-0.014108-0.15450.438721
29-0.004643-0.05090.47976
300.0057190.06260.475076
31-0.091586-1.00330.158874
320.0335910.3680.356771
33-0.043549-0.47710.317095
340.0585110.6410.261385
35-0.071713-0.78560.216831
36-0.075129-0.8230.20607
370.0145270.15910.436916
380.0073090.08010.46816
39-0.021755-0.23830.406022
400.0172970.18950.425017
410.0142180.15570.438247
420.0038790.04250.483088
43-0.02902-0.31790.375557
44-0.021908-0.240.405372
450.0166560.18250.427764
46-0.028062-0.30740.379534
47-0.067435-0.73870.230761
48-0.046562-0.51010.305474

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.947903 & 10.3838 & 0 \tabularnewline
2 & 0.066485 & 0.7283 & 0.233921 \tabularnewline
3 & -0.082604 & -0.9049 & 0.18367 \tabularnewline
4 & 0.161756 & 1.7719 & 0.039471 \tabularnewline
5 & -0.095006 & -1.0407 & 0.150044 \tabularnewline
6 & 0.075233 & 0.8241 & 0.205747 \tabularnewline
7 & 0.103348 & 1.1321 & 0.129921 \tabularnewline
8 & 0.049089 & 0.5377 & 0.295874 \tabularnewline
9 & -0.040338 & -0.4419 & 0.329684 \tabularnewline
10 & 0.088259 & 0.9668 & 0.167786 \tabularnewline
11 & 0.102412 & 1.1219 & 0.132079 \tabularnewline
12 & 0.170863 & 1.8717 & 0.031841 \tabularnewline
13 & -0.617564 & -6.7651 & 0 \tabularnewline
14 & 0.140117 & 1.5349 & 0.06372 \tabularnewline
15 & 0.079109 & 0.8666 & 0.193946 \tabularnewline
16 & -0.101788 & -1.115 & 0.133532 \tabularnewline
17 & 0.062872 & 0.6887 & 0.246163 \tabularnewline
18 & 0.038416 & 0.4208 & 0.337316 \tabularnewline
19 & -0.041005 & -0.4492 & 0.327054 \tabularnewline
20 & 0.02651 & 0.2904 & 0.386003 \tabularnewline
21 & -0.026507 & -0.2904 & 0.386017 \tabularnewline
22 & 0.084727 & 0.9281 & 0.177601 \tabularnewline
23 & -0.085814 & -0.94 & 0.17454 \tabularnewline
24 & -0.059736 & -0.6544 & 0.257061 \tabularnewline
25 & -0.132117 & -1.4473 & 0.075215 \tabularnewline
26 & 0.009564 & 0.1048 & 0.458367 \tabularnewline
27 & 0.006386 & 0.07 & 0.472174 \tabularnewline
28 & -0.014108 & -0.1545 & 0.438721 \tabularnewline
29 & -0.004643 & -0.0509 & 0.47976 \tabularnewline
30 & 0.005719 & 0.0626 & 0.475076 \tabularnewline
31 & -0.091586 & -1.0033 & 0.158874 \tabularnewline
32 & 0.033591 & 0.368 & 0.356771 \tabularnewline
33 & -0.043549 & -0.4771 & 0.317095 \tabularnewline
34 & 0.058511 & 0.641 & 0.261385 \tabularnewline
35 & -0.071713 & -0.7856 & 0.216831 \tabularnewline
36 & -0.075129 & -0.823 & 0.20607 \tabularnewline
37 & 0.014527 & 0.1591 & 0.436916 \tabularnewline
38 & 0.007309 & 0.0801 & 0.46816 \tabularnewline
39 & -0.021755 & -0.2383 & 0.406022 \tabularnewline
40 & 0.017297 & 0.1895 & 0.425017 \tabularnewline
41 & 0.014218 & 0.1557 & 0.438247 \tabularnewline
42 & 0.003879 & 0.0425 & 0.483088 \tabularnewline
43 & -0.02902 & -0.3179 & 0.375557 \tabularnewline
44 & -0.021908 & -0.24 & 0.405372 \tabularnewline
45 & 0.016656 & 0.1825 & 0.427764 \tabularnewline
46 & -0.028062 & -0.3074 & 0.379534 \tabularnewline
47 & -0.067435 & -0.7387 & 0.230761 \tabularnewline
48 & -0.046562 & -0.5101 & 0.305474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279865&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]0.947903[/C][C]10.3838[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.066485[/C][C]0.7283[/C][C]0.233921[/C][/ROW]
[ROW][C]3[/C][C]-0.082604[/C][C]-0.9049[/C][C]0.18367[/C][/ROW]
[ROW][C]4[/C][C]0.161756[/C][C]1.7719[/C][C]0.039471[/C][/ROW]
[ROW][C]5[/C][C]-0.095006[/C][C]-1.0407[/C][C]0.150044[/C][/ROW]
[ROW][C]6[/C][C]0.075233[/C][C]0.8241[/C][C]0.205747[/C][/ROW]
[ROW][C]7[/C][C]0.103348[/C][C]1.1321[/C][C]0.129921[/C][/ROW]
[ROW][C]8[/C][C]0.049089[/C][C]0.5377[/C][C]0.295874[/C][/ROW]
[ROW][C]9[/C][C]-0.040338[/C][C]-0.4419[/C][C]0.329684[/C][/ROW]
[ROW][C]10[/C][C]0.088259[/C][C]0.9668[/C][C]0.167786[/C][/ROW]
[ROW][C]11[/C][C]0.102412[/C][C]1.1219[/C][C]0.132079[/C][/ROW]
[ROW][C]12[/C][C]0.170863[/C][C]1.8717[/C][C]0.031841[/C][/ROW]
[ROW][C]13[/C][C]-0.617564[/C][C]-6.7651[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.140117[/C][C]1.5349[/C][C]0.06372[/C][/ROW]
[ROW][C]15[/C][C]0.079109[/C][C]0.8666[/C][C]0.193946[/C][/ROW]
[ROW][C]16[/C][C]-0.101788[/C][C]-1.115[/C][C]0.133532[/C][/ROW]
[ROW][C]17[/C][C]0.062872[/C][C]0.6887[/C][C]0.246163[/C][/ROW]
[ROW][C]18[/C][C]0.038416[/C][C]0.4208[/C][C]0.337316[/C][/ROW]
[ROW][C]19[/C][C]-0.041005[/C][C]-0.4492[/C][C]0.327054[/C][/ROW]
[ROW][C]20[/C][C]0.02651[/C][C]0.2904[/C][C]0.386003[/C][/ROW]
[ROW][C]21[/C][C]-0.026507[/C][C]-0.2904[/C][C]0.386017[/C][/ROW]
[ROW][C]22[/C][C]0.084727[/C][C]0.9281[/C][C]0.177601[/C][/ROW]
[ROW][C]23[/C][C]-0.085814[/C][C]-0.94[/C][C]0.17454[/C][/ROW]
[ROW][C]24[/C][C]-0.059736[/C][C]-0.6544[/C][C]0.257061[/C][/ROW]
[ROW][C]25[/C][C]-0.132117[/C][C]-1.4473[/C][C]0.075215[/C][/ROW]
[ROW][C]26[/C][C]0.009564[/C][C]0.1048[/C][C]0.458367[/C][/ROW]
[ROW][C]27[/C][C]0.006386[/C][C]0.07[/C][C]0.472174[/C][/ROW]
[ROW][C]28[/C][C]-0.014108[/C][C]-0.1545[/C][C]0.438721[/C][/ROW]
[ROW][C]29[/C][C]-0.004643[/C][C]-0.0509[/C][C]0.47976[/C][/ROW]
[ROW][C]30[/C][C]0.005719[/C][C]0.0626[/C][C]0.475076[/C][/ROW]
[ROW][C]31[/C][C]-0.091586[/C][C]-1.0033[/C][C]0.158874[/C][/ROW]
[ROW][C]32[/C][C]0.033591[/C][C]0.368[/C][C]0.356771[/C][/ROW]
[ROW][C]33[/C][C]-0.043549[/C][C]-0.4771[/C][C]0.317095[/C][/ROW]
[ROW][C]34[/C][C]0.058511[/C][C]0.641[/C][C]0.261385[/C][/ROW]
[ROW][C]35[/C][C]-0.071713[/C][C]-0.7856[/C][C]0.216831[/C][/ROW]
[ROW][C]36[/C][C]-0.075129[/C][C]-0.823[/C][C]0.20607[/C][/ROW]
[ROW][C]37[/C][C]0.014527[/C][C]0.1591[/C][C]0.436916[/C][/ROW]
[ROW][C]38[/C][C]0.007309[/C][C]0.0801[/C][C]0.46816[/C][/ROW]
[ROW][C]39[/C][C]-0.021755[/C][C]-0.2383[/C][C]0.406022[/C][/ROW]
[ROW][C]40[/C][C]0.017297[/C][C]0.1895[/C][C]0.425017[/C][/ROW]
[ROW][C]41[/C][C]0.014218[/C][C]0.1557[/C][C]0.438247[/C][/ROW]
[ROW][C]42[/C][C]0.003879[/C][C]0.0425[/C][C]0.483088[/C][/ROW]
[ROW][C]43[/C][C]-0.02902[/C][C]-0.3179[/C][C]0.375557[/C][/ROW]
[ROW][C]44[/C][C]-0.021908[/C][C]-0.24[/C][C]0.405372[/C][/ROW]
[ROW][C]45[/C][C]0.016656[/C][C]0.1825[/C][C]0.427764[/C][/ROW]
[ROW][C]46[/C][C]-0.028062[/C][C]-0.3074[/C][C]0.379534[/C][/ROW]
[ROW][C]47[/C][C]-0.067435[/C][C]-0.7387[/C][C]0.230761[/C][/ROW]
[ROW][C]48[/C][C]-0.046562[/C][C]-0.5101[/C][C]0.305474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279865&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279865&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
10.94790310.38380
20.0664850.72830.233921
3-0.082604-0.90490.18367
40.1617561.77190.039471
5-0.095006-1.04070.150044
60.0752330.82410.205747
70.1033481.13210.129921
80.0490890.53770.295874
9-0.040338-0.44190.329684
100.0882590.96680.167786
110.1024121.12190.132079
120.1708631.87170.031841
13-0.617564-6.76510
140.1401171.53490.06372
150.0791090.86660.193946
16-0.101788-1.1150.133532
170.0628720.68870.246163
180.0384160.42080.337316
19-0.041005-0.44920.327054
200.026510.29040.386003
21-0.026507-0.29040.386017
220.0847270.92810.177601
23-0.085814-0.940.17454
24-0.059736-0.65440.257061
25-0.132117-1.44730.075215
260.0095640.10480.458367
270.0063860.070.472174
28-0.014108-0.15450.438721
29-0.004643-0.05090.47976
300.0057190.06260.475076
31-0.091586-1.00330.158874
320.0335910.3680.356771
33-0.043549-0.47710.317095
340.0585110.6410.261385
35-0.071713-0.78560.216831
36-0.075129-0.8230.20607
370.0145270.15910.436916
380.0073090.08010.46816
39-0.021755-0.23830.406022
400.0172970.18950.425017
410.0142180.15570.438247
420.0038790.04250.483088
43-0.02902-0.31790.375557
44-0.021908-0.240.405372
450.0166560.18250.427764
46-0.028062-0.30740.379534
47-0.067435-0.73870.230761
48-0.046562-0.51010.305474



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 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')