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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 16 Mar 2016 22:34:03 +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/2016/Mar/16/t14581676985dlmoqd2gcx0uwo.htm/, Retrieved Mon, 06 May 2024 22:09:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294176, Retrieved Mon, 06 May 2024 22:09:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Vers Fruit - Auto...] [2016-03-16 22:34:03] [9229f16b23a3f07f1433c1291c3e5666] [Current]
- R PD    [(Partial) Autocorrelation Function] [Vers Fruit - Auto...] [2016-03-16 22:35:41] [b1a7cb6d93e9c32863cdeb6d14632a38]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82,6
85,99
86,85
86,12
97,19
89,8
90,27
90,68
90,05
90,28
91,52
88,3
85,31
87,86
87,77
88,44
88,73
94,4
94,09
90,32
89,68
94,15
95,2
91,82
90,33
95,14
96,06
97,21
100,33
98,79
102,48
99,29
98,83
97,25
94,55
93,53
93,58
95,79
94,77
94,2
96,23
92,3
88,86
86,44
86,21
88,57
90,69
89
86,88
90,65
90,68
89,64
102,62
101,84
92,51
94,29
94,68
96,94
94,03
89,65
84,9
89,07
89,8
93,22
92,23
98,41
96,63
89,8
90
92,13
93,27
90,81
85,42
88,28
88,73
90,18
92,74
96,13
94,85
94,25
96,94
101,22
98,71
95,51
93,91
98,17
97,59
99,64
107,88
108,49
100,25
99,27
101,73
101,25
97,09
94,74
94,53
93,48
96,05
106,22
98,33
99,86
93,78
88,96
83,77
89,46
86,78
88,4
87,19
92,23
95,99
104,75
105,63
108,71
96,4
93,31
93,77
98,7
95,04
95,61

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294176&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294176&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294176&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7192567.87910
20.4817755.27760
30.3228133.53620.000289
40.223222.44530.007963
50.129831.42220.078778
60.0993591.08840.139295
70.0395920.43370.332638
80.0154960.16970.432748
9-0.015704-0.1720.431853
100.0626590.68640.246895
110.1428331.56470.060148
120.1796791.96830.025671
130.0689650.75550.225724
14-0.076772-0.8410.201012
15-0.20659-2.26310.012714
16-0.223268-2.44580.007953
17-0.20442-2.23930.013489
18-0.13887-1.52120.065414
19-0.121359-1.32940.093116
20-0.106036-1.16160.123859
21-0.089336-0.97860.164867
22-0.005743-0.06290.474972
230.0945291.03550.151255
240.1512191.65650.050114
250.0732860.80280.211837
26-0.015289-0.16750.433636
27-0.06052-0.6630.254314
28-0.024769-0.27130.3933
29-0.004488-0.04920.480437
300.0306750.3360.368717
310.0664060.72740.234187
320.0571050.62550.266399
330.0502220.55020.291618
340.0704930.77220.220755
350.124331.3620.087881
360.13321.45910.073571
37-0.018408-0.20170.420265
38-0.130123-1.42540.078315
39-0.16576-1.81580.035948
40-0.141649-1.55170.061686
41-0.134005-1.46790.072367
42-0.088883-0.97370.166091
43-0.074155-0.81230.209106
44-0.079232-0.86790.193578
45-0.08544-0.93590.17559
46-0.012006-0.13150.447794
470.0572150.62680.266005
480.1032811.13140.130075

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.719256 & 7.8791 & 0 \tabularnewline
2 & 0.481775 & 5.2776 & 0 \tabularnewline
3 & 0.322813 & 3.5362 & 0.000289 \tabularnewline
4 & 0.22322 & 2.4453 & 0.007963 \tabularnewline
5 & 0.12983 & 1.4222 & 0.078778 \tabularnewline
6 & 0.099359 & 1.0884 & 0.139295 \tabularnewline
7 & 0.039592 & 0.4337 & 0.332638 \tabularnewline
8 & 0.015496 & 0.1697 & 0.432748 \tabularnewline
9 & -0.015704 & -0.172 & 0.431853 \tabularnewline
10 & 0.062659 & 0.6864 & 0.246895 \tabularnewline
11 & 0.142833 & 1.5647 & 0.060148 \tabularnewline
12 & 0.179679 & 1.9683 & 0.025671 \tabularnewline
13 & 0.068965 & 0.7555 & 0.225724 \tabularnewline
14 & -0.076772 & -0.841 & 0.201012 \tabularnewline
15 & -0.20659 & -2.2631 & 0.012714 \tabularnewline
16 & -0.223268 & -2.4458 & 0.007953 \tabularnewline
17 & -0.20442 & -2.2393 & 0.013489 \tabularnewline
18 & -0.13887 & -1.5212 & 0.065414 \tabularnewline
19 & -0.121359 & -1.3294 & 0.093116 \tabularnewline
20 & -0.106036 & -1.1616 & 0.123859 \tabularnewline
21 & -0.089336 & -0.9786 & 0.164867 \tabularnewline
22 & -0.005743 & -0.0629 & 0.474972 \tabularnewline
23 & 0.094529 & 1.0355 & 0.151255 \tabularnewline
24 & 0.151219 & 1.6565 & 0.050114 \tabularnewline
25 & 0.073286 & 0.8028 & 0.211837 \tabularnewline
26 & -0.015289 & -0.1675 & 0.433636 \tabularnewline
27 & -0.06052 & -0.663 & 0.254314 \tabularnewline
28 & -0.024769 & -0.2713 & 0.3933 \tabularnewline
29 & -0.004488 & -0.0492 & 0.480437 \tabularnewline
30 & 0.030675 & 0.336 & 0.368717 \tabularnewline
31 & 0.066406 & 0.7274 & 0.234187 \tabularnewline
32 & 0.057105 & 0.6255 & 0.266399 \tabularnewline
33 & 0.050222 & 0.5502 & 0.291618 \tabularnewline
34 & 0.070493 & 0.7722 & 0.220755 \tabularnewline
35 & 0.12433 & 1.362 & 0.087881 \tabularnewline
36 & 0.1332 & 1.4591 & 0.073571 \tabularnewline
37 & -0.018408 & -0.2017 & 0.420265 \tabularnewline
38 & -0.130123 & -1.4254 & 0.078315 \tabularnewline
39 & -0.16576 & -1.8158 & 0.035948 \tabularnewline
40 & -0.141649 & -1.5517 & 0.061686 \tabularnewline
41 & -0.134005 & -1.4679 & 0.072367 \tabularnewline
42 & -0.088883 & -0.9737 & 0.166091 \tabularnewline
43 & -0.074155 & -0.8123 & 0.209106 \tabularnewline
44 & -0.079232 & -0.8679 & 0.193578 \tabularnewline
45 & -0.08544 & -0.9359 & 0.17559 \tabularnewline
46 & -0.012006 & -0.1315 & 0.447794 \tabularnewline
47 & 0.057215 & 0.6268 & 0.266005 \tabularnewline
48 & 0.103281 & 1.1314 & 0.130075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294176&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]0.719256[/C][C]7.8791[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.481775[/C][C]5.2776[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.322813[/C][C]3.5362[/C][C]0.000289[/C][/ROW]
[ROW][C]4[/C][C]0.22322[/C][C]2.4453[/C][C]0.007963[/C][/ROW]
[ROW][C]5[/C][C]0.12983[/C][C]1.4222[/C][C]0.078778[/C][/ROW]
[ROW][C]6[/C][C]0.099359[/C][C]1.0884[/C][C]0.139295[/C][/ROW]
[ROW][C]7[/C][C]0.039592[/C][C]0.4337[/C][C]0.332638[/C][/ROW]
[ROW][C]8[/C][C]0.015496[/C][C]0.1697[/C][C]0.432748[/C][/ROW]
[ROW][C]9[/C][C]-0.015704[/C][C]-0.172[/C][C]0.431853[/C][/ROW]
[ROW][C]10[/C][C]0.062659[/C][C]0.6864[/C][C]0.246895[/C][/ROW]
[ROW][C]11[/C][C]0.142833[/C][C]1.5647[/C][C]0.060148[/C][/ROW]
[ROW][C]12[/C][C]0.179679[/C][C]1.9683[/C][C]0.025671[/C][/ROW]
[ROW][C]13[/C][C]0.068965[/C][C]0.7555[/C][C]0.225724[/C][/ROW]
[ROW][C]14[/C][C]-0.076772[/C][C]-0.841[/C][C]0.201012[/C][/ROW]
[ROW][C]15[/C][C]-0.20659[/C][C]-2.2631[/C][C]0.012714[/C][/ROW]
[ROW][C]16[/C][C]-0.223268[/C][C]-2.4458[/C][C]0.007953[/C][/ROW]
[ROW][C]17[/C][C]-0.20442[/C][C]-2.2393[/C][C]0.013489[/C][/ROW]
[ROW][C]18[/C][C]-0.13887[/C][C]-1.5212[/C][C]0.065414[/C][/ROW]
[ROW][C]19[/C][C]-0.121359[/C][C]-1.3294[/C][C]0.093116[/C][/ROW]
[ROW][C]20[/C][C]-0.106036[/C][C]-1.1616[/C][C]0.123859[/C][/ROW]
[ROW][C]21[/C][C]-0.089336[/C][C]-0.9786[/C][C]0.164867[/C][/ROW]
[ROW][C]22[/C][C]-0.005743[/C][C]-0.0629[/C][C]0.474972[/C][/ROW]
[ROW][C]23[/C][C]0.094529[/C][C]1.0355[/C][C]0.151255[/C][/ROW]
[ROW][C]24[/C][C]0.151219[/C][C]1.6565[/C][C]0.050114[/C][/ROW]
[ROW][C]25[/C][C]0.073286[/C][C]0.8028[/C][C]0.211837[/C][/ROW]
[ROW][C]26[/C][C]-0.015289[/C][C]-0.1675[/C][C]0.433636[/C][/ROW]
[ROW][C]27[/C][C]-0.06052[/C][C]-0.663[/C][C]0.254314[/C][/ROW]
[ROW][C]28[/C][C]-0.024769[/C][C]-0.2713[/C][C]0.3933[/C][/ROW]
[ROW][C]29[/C][C]-0.004488[/C][C]-0.0492[/C][C]0.480437[/C][/ROW]
[ROW][C]30[/C][C]0.030675[/C][C]0.336[/C][C]0.368717[/C][/ROW]
[ROW][C]31[/C][C]0.066406[/C][C]0.7274[/C][C]0.234187[/C][/ROW]
[ROW][C]32[/C][C]0.057105[/C][C]0.6255[/C][C]0.266399[/C][/ROW]
[ROW][C]33[/C][C]0.050222[/C][C]0.5502[/C][C]0.291618[/C][/ROW]
[ROW][C]34[/C][C]0.070493[/C][C]0.7722[/C][C]0.220755[/C][/ROW]
[ROW][C]35[/C][C]0.12433[/C][C]1.362[/C][C]0.087881[/C][/ROW]
[ROW][C]36[/C][C]0.1332[/C][C]1.4591[/C][C]0.073571[/C][/ROW]
[ROW][C]37[/C][C]-0.018408[/C][C]-0.2017[/C][C]0.420265[/C][/ROW]
[ROW][C]38[/C][C]-0.130123[/C][C]-1.4254[/C][C]0.078315[/C][/ROW]
[ROW][C]39[/C][C]-0.16576[/C][C]-1.8158[/C][C]0.035948[/C][/ROW]
[ROW][C]40[/C][C]-0.141649[/C][C]-1.5517[/C][C]0.061686[/C][/ROW]
[ROW][C]41[/C][C]-0.134005[/C][C]-1.4679[/C][C]0.072367[/C][/ROW]
[ROW][C]42[/C][C]-0.088883[/C][C]-0.9737[/C][C]0.166091[/C][/ROW]
[ROW][C]43[/C][C]-0.074155[/C][C]-0.8123[/C][C]0.209106[/C][/ROW]
[ROW][C]44[/C][C]-0.079232[/C][C]-0.8679[/C][C]0.193578[/C][/ROW]
[ROW][C]45[/C][C]-0.08544[/C][C]-0.9359[/C][C]0.17559[/C][/ROW]
[ROW][C]46[/C][C]-0.012006[/C][C]-0.1315[/C][C]0.447794[/C][/ROW]
[ROW][C]47[/C][C]0.057215[/C][C]0.6268[/C][C]0.266005[/C][/ROW]
[ROW][C]48[/C][C]0.103281[/C][C]1.1314[/C][C]0.130075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294176&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294176&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7192567.87910
20.4817755.27760
30.3228133.53620.000289
40.223222.44530.007963
50.129831.42220.078778
60.0993591.08840.139295
70.0395920.43370.332638
80.0154960.16970.432748
9-0.015704-0.1720.431853
100.0626590.68640.246895
110.1428331.56470.060148
120.1796791.96830.025671
130.0689650.75550.225724
14-0.076772-0.8410.201012
15-0.20659-2.26310.012714
16-0.223268-2.44580.007953
17-0.20442-2.23930.013489
18-0.13887-1.52120.065414
19-0.121359-1.32940.093116
20-0.106036-1.16160.123859
21-0.089336-0.97860.164867
22-0.005743-0.06290.474972
230.0945291.03550.151255
240.1512191.65650.050114
250.0732860.80280.211837
26-0.015289-0.16750.433636
27-0.06052-0.6630.254314
28-0.024769-0.27130.3933
29-0.004488-0.04920.480437
300.0306750.3360.368717
310.0664060.72740.234187
320.0571050.62550.266399
330.0502220.55020.291618
340.0704930.77220.220755
350.124331.3620.087881
360.13321.45910.073571
37-0.018408-0.20170.420265
38-0.130123-1.42540.078315
39-0.16576-1.81580.035948
40-0.141649-1.55170.061686
41-0.134005-1.46790.072367
42-0.088883-0.97370.166091
43-0.074155-0.81230.209106
44-0.079232-0.86790.193578
45-0.08544-0.93590.17559
46-0.012006-0.13150.447794
470.0572150.62680.266005
480.1032811.13140.130075






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7192567.87910
2-0.073664-0.80690.210648
30.0078140.08560.465965
40.0135860.14880.44097
5-0.053662-0.58780.278873
60.0644180.70570.240882
7-0.086781-0.95060.171849
80.031850.34890.363887
9-0.041713-0.45690.324268
100.1932422.11690.018169
110.0784690.85960.195866
120.0055560.06090.475786
13-0.224412-2.45830.007693
14-0.183096-2.00570.023568
15-0.116795-1.27940.101608
160.0535990.58710.279104
170.0477410.5230.300978
180.0869950.9530.171256
19-0.015683-0.17180.431943
20-0.014411-0.15790.437414
21-0.017216-0.18860.425365
220.0395960.43380.332622
230.0853060.93450.175968
240.0211430.23160.408616
25-0.090776-0.99440.161013
26-0.016186-0.17730.429783
270.0569490.62390.266955
280.0779630.8540.197391
29-0.058487-0.64070.261471
30-0.032896-0.36040.359608
310.0606260.66410.253942
32-0.026761-0.29320.384954
330.0460780.50480.307328
34-0.062648-0.68630.246932
350.0529010.57950.281669
36-0.02065-0.22620.41071
37-0.222421-2.43650.008149
380.0134250.14710.441663
390.0253150.27730.391008
400.0646410.70810.240127
41-0.087951-0.96350.168628
420.0222180.24340.404061
43-0.010153-0.11120.455816
44-0.004552-0.04990.480157
45-0.00256-0.0280.488838
460.0569910.62430.266806
470.0481770.52780.299321
480.1033231.13180.129979

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.719256 & 7.8791 & 0 \tabularnewline
2 & -0.073664 & -0.8069 & 0.210648 \tabularnewline
3 & 0.007814 & 0.0856 & 0.465965 \tabularnewline
4 & 0.013586 & 0.1488 & 0.44097 \tabularnewline
5 & -0.053662 & -0.5878 & 0.278873 \tabularnewline
6 & 0.064418 & 0.7057 & 0.240882 \tabularnewline
7 & -0.086781 & -0.9506 & 0.171849 \tabularnewline
8 & 0.03185 & 0.3489 & 0.363887 \tabularnewline
9 & -0.041713 & -0.4569 & 0.324268 \tabularnewline
10 & 0.193242 & 2.1169 & 0.018169 \tabularnewline
11 & 0.078469 & 0.8596 & 0.195866 \tabularnewline
12 & 0.005556 & 0.0609 & 0.475786 \tabularnewline
13 & -0.224412 & -2.4583 & 0.007693 \tabularnewline
14 & -0.183096 & -2.0057 & 0.023568 \tabularnewline
15 & -0.116795 & -1.2794 & 0.101608 \tabularnewline
16 & 0.053599 & 0.5871 & 0.279104 \tabularnewline
17 & 0.047741 & 0.523 & 0.300978 \tabularnewline
18 & 0.086995 & 0.953 & 0.171256 \tabularnewline
19 & -0.015683 & -0.1718 & 0.431943 \tabularnewline
20 & -0.014411 & -0.1579 & 0.437414 \tabularnewline
21 & -0.017216 & -0.1886 & 0.425365 \tabularnewline
22 & 0.039596 & 0.4338 & 0.332622 \tabularnewline
23 & 0.085306 & 0.9345 & 0.175968 \tabularnewline
24 & 0.021143 & 0.2316 & 0.408616 \tabularnewline
25 & -0.090776 & -0.9944 & 0.161013 \tabularnewline
26 & -0.016186 & -0.1773 & 0.429783 \tabularnewline
27 & 0.056949 & 0.6239 & 0.266955 \tabularnewline
28 & 0.077963 & 0.854 & 0.197391 \tabularnewline
29 & -0.058487 & -0.6407 & 0.261471 \tabularnewline
30 & -0.032896 & -0.3604 & 0.359608 \tabularnewline
31 & 0.060626 & 0.6641 & 0.253942 \tabularnewline
32 & -0.026761 & -0.2932 & 0.384954 \tabularnewline
33 & 0.046078 & 0.5048 & 0.307328 \tabularnewline
34 & -0.062648 & -0.6863 & 0.246932 \tabularnewline
35 & 0.052901 & 0.5795 & 0.281669 \tabularnewline
36 & -0.02065 & -0.2262 & 0.41071 \tabularnewline
37 & -0.222421 & -2.4365 & 0.008149 \tabularnewline
38 & 0.013425 & 0.1471 & 0.441663 \tabularnewline
39 & 0.025315 & 0.2773 & 0.391008 \tabularnewline
40 & 0.064641 & 0.7081 & 0.240127 \tabularnewline
41 & -0.087951 & -0.9635 & 0.168628 \tabularnewline
42 & 0.022218 & 0.2434 & 0.404061 \tabularnewline
43 & -0.010153 & -0.1112 & 0.455816 \tabularnewline
44 & -0.004552 & -0.0499 & 0.480157 \tabularnewline
45 & -0.00256 & -0.028 & 0.488838 \tabularnewline
46 & 0.056991 & 0.6243 & 0.266806 \tabularnewline
47 & 0.048177 & 0.5278 & 0.299321 \tabularnewline
48 & 0.103323 & 1.1318 & 0.129979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294176&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]0.719256[/C][C]7.8791[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.073664[/C][C]-0.8069[/C][C]0.210648[/C][/ROW]
[ROW][C]3[/C][C]0.007814[/C][C]0.0856[/C][C]0.465965[/C][/ROW]
[ROW][C]4[/C][C]0.013586[/C][C]0.1488[/C][C]0.44097[/C][/ROW]
[ROW][C]5[/C][C]-0.053662[/C][C]-0.5878[/C][C]0.278873[/C][/ROW]
[ROW][C]6[/C][C]0.064418[/C][C]0.7057[/C][C]0.240882[/C][/ROW]
[ROW][C]7[/C][C]-0.086781[/C][C]-0.9506[/C][C]0.171849[/C][/ROW]
[ROW][C]8[/C][C]0.03185[/C][C]0.3489[/C][C]0.363887[/C][/ROW]
[ROW][C]9[/C][C]-0.041713[/C][C]-0.4569[/C][C]0.324268[/C][/ROW]
[ROW][C]10[/C][C]0.193242[/C][C]2.1169[/C][C]0.018169[/C][/ROW]
[ROW][C]11[/C][C]0.078469[/C][C]0.8596[/C][C]0.195866[/C][/ROW]
[ROW][C]12[/C][C]0.005556[/C][C]0.0609[/C][C]0.475786[/C][/ROW]
[ROW][C]13[/C][C]-0.224412[/C][C]-2.4583[/C][C]0.007693[/C][/ROW]
[ROW][C]14[/C][C]-0.183096[/C][C]-2.0057[/C][C]0.023568[/C][/ROW]
[ROW][C]15[/C][C]-0.116795[/C][C]-1.2794[/C][C]0.101608[/C][/ROW]
[ROW][C]16[/C][C]0.053599[/C][C]0.5871[/C][C]0.279104[/C][/ROW]
[ROW][C]17[/C][C]0.047741[/C][C]0.523[/C][C]0.300978[/C][/ROW]
[ROW][C]18[/C][C]0.086995[/C][C]0.953[/C][C]0.171256[/C][/ROW]
[ROW][C]19[/C][C]-0.015683[/C][C]-0.1718[/C][C]0.431943[/C][/ROW]
[ROW][C]20[/C][C]-0.014411[/C][C]-0.1579[/C][C]0.437414[/C][/ROW]
[ROW][C]21[/C][C]-0.017216[/C][C]-0.1886[/C][C]0.425365[/C][/ROW]
[ROW][C]22[/C][C]0.039596[/C][C]0.4338[/C][C]0.332622[/C][/ROW]
[ROW][C]23[/C][C]0.085306[/C][C]0.9345[/C][C]0.175968[/C][/ROW]
[ROW][C]24[/C][C]0.021143[/C][C]0.2316[/C][C]0.408616[/C][/ROW]
[ROW][C]25[/C][C]-0.090776[/C][C]-0.9944[/C][C]0.161013[/C][/ROW]
[ROW][C]26[/C][C]-0.016186[/C][C]-0.1773[/C][C]0.429783[/C][/ROW]
[ROW][C]27[/C][C]0.056949[/C][C]0.6239[/C][C]0.266955[/C][/ROW]
[ROW][C]28[/C][C]0.077963[/C][C]0.854[/C][C]0.197391[/C][/ROW]
[ROW][C]29[/C][C]-0.058487[/C][C]-0.6407[/C][C]0.261471[/C][/ROW]
[ROW][C]30[/C][C]-0.032896[/C][C]-0.3604[/C][C]0.359608[/C][/ROW]
[ROW][C]31[/C][C]0.060626[/C][C]0.6641[/C][C]0.253942[/C][/ROW]
[ROW][C]32[/C][C]-0.026761[/C][C]-0.2932[/C][C]0.384954[/C][/ROW]
[ROW][C]33[/C][C]0.046078[/C][C]0.5048[/C][C]0.307328[/C][/ROW]
[ROW][C]34[/C][C]-0.062648[/C][C]-0.6863[/C][C]0.246932[/C][/ROW]
[ROW][C]35[/C][C]0.052901[/C][C]0.5795[/C][C]0.281669[/C][/ROW]
[ROW][C]36[/C][C]-0.02065[/C][C]-0.2262[/C][C]0.41071[/C][/ROW]
[ROW][C]37[/C][C]-0.222421[/C][C]-2.4365[/C][C]0.008149[/C][/ROW]
[ROW][C]38[/C][C]0.013425[/C][C]0.1471[/C][C]0.441663[/C][/ROW]
[ROW][C]39[/C][C]0.025315[/C][C]0.2773[/C][C]0.391008[/C][/ROW]
[ROW][C]40[/C][C]0.064641[/C][C]0.7081[/C][C]0.240127[/C][/ROW]
[ROW][C]41[/C][C]-0.087951[/C][C]-0.9635[/C][C]0.168628[/C][/ROW]
[ROW][C]42[/C][C]0.022218[/C][C]0.2434[/C][C]0.404061[/C][/ROW]
[ROW][C]43[/C][C]-0.010153[/C][C]-0.1112[/C][C]0.455816[/C][/ROW]
[ROW][C]44[/C][C]-0.004552[/C][C]-0.0499[/C][C]0.480157[/C][/ROW]
[ROW][C]45[/C][C]-0.00256[/C][C]-0.028[/C][C]0.488838[/C][/ROW]
[ROW][C]46[/C][C]0.056991[/C][C]0.6243[/C][C]0.266806[/C][/ROW]
[ROW][C]47[/C][C]0.048177[/C][C]0.5278[/C][C]0.299321[/C][/ROW]
[ROW][C]48[/C][C]0.103323[/C][C]1.1318[/C][C]0.129979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294176&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294176&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7192567.87910
2-0.073664-0.80690.210648
30.0078140.08560.465965
40.0135860.14880.44097
5-0.053662-0.58780.278873
60.0644180.70570.240882
7-0.086781-0.95060.171849
80.031850.34890.363887
9-0.041713-0.45690.324268
100.1932422.11690.018169
110.0784690.85960.195866
120.0055560.06090.475786
13-0.224412-2.45830.007693
14-0.183096-2.00570.023568
15-0.116795-1.27940.101608
160.0535990.58710.279104
170.0477410.5230.300978
180.0869950.9530.171256
19-0.015683-0.17180.431943
20-0.014411-0.15790.437414
21-0.017216-0.18860.425365
220.0395960.43380.332622
230.0853060.93450.175968
240.0211430.23160.408616
25-0.090776-0.99440.161013
26-0.016186-0.17730.429783
270.0569490.62390.266955
280.0779630.8540.197391
29-0.058487-0.64070.261471
30-0.032896-0.36040.359608
310.0606260.66410.253942
32-0.026761-0.29320.384954
330.0460780.50480.307328
34-0.062648-0.68630.246932
350.0529010.57950.281669
36-0.02065-0.22620.41071
37-0.222421-2.43650.008149
380.0134250.14710.441663
390.0253150.27730.391008
400.0646410.70810.240127
41-0.087951-0.96350.168628
420.0222180.24340.404061
43-0.010153-0.11120.455816
44-0.004552-0.04990.480157
45-0.00256-0.0280.488838
460.0569910.62430.266806
470.0481770.52780.299321
480.1033231.13180.129979


Figures (Output of Computation)

Input Parameters & R Code

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)
x <- na.omit(x)
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')