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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 computationTue, 15 Nov 2011 02:35:02 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/15/t1321342600l5f6co9ddl51qmo.htm/, Retrieved Fri, 19 Apr 2024 18:54:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=142484, Retrieved Fri, 19 Apr 2024 18:54:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact172

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] [gemiddelde consum...] [2011-11-15 07:35:02] [08802a004a000ae20ac4145e9a22f7e4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15,14
14,2
13,83
14,31
14,04
14,9
14,92
15,36
15,5
15,65
16,18
15,44
15,58
15,24
15,33
16,07
15,82
15,87
15,72
17,07
16,83
17,52
17,76
17,36
17,95
16,71
17,14
16,72
17,26
17,24
17,69
18,13
18,08
18,18
18,18
17,64
17,89
16,82
16,61
16,66
17,02
16,91
17,18
18,06
17,58
17,48
17,54
17,44
17,79
16,79
16,19
16,62
16,39
16,54
17,26
18
17,29
18,16
17,82
17,48
18,31
17,04
17,03
16,97
17,11
17,12
17,69
18,5
18,27
18,45
18,35
18,03
18,49
18,07
17,8
17,88
18,12
18,68
18,8
19,64
19,56
19,3
20,07
19,82
20,29
19,36
18,74
18,87
18,87
18,91
19,31
20,06
20,72
20,42
20,58
20,58
21,18
19,87
19,83
19,48
19,49
19,4
19,89
20,44
20,07
19,75
19,54
19,07
19,55
18,01
17,5
17,41
17,47
17,6
17,64
18,3
18,27
17,99
18,04
17,62
18,22
17,67
17,73
17,99
18,15
18,41
18,36
19,52
19,96
19,6
19,48
19,13

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142484&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142484&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142484&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.178762-2.0460.021378
20.1369551.56750.059702
30.0189080.21640.414503
4-0.158108-1.80960.036323
50.0236320.27050.393607
6-0.350589-4.01275e-05
70.0317150.3630.358598
8-0.174536-1.99770.023913
90.0709040.81150.209264
100.0836660.95760.170013
11-0.080661-0.92320.178799
120.5944466.80370
13-0.078833-0.90230.184281
140.078120.89410.186448
15-0.019846-0.22710.410332
16-0.113557-1.29970.09799
17-0.062367-0.71380.238303
18-0.371808-4.25552e-05
190.001310.0150.494031
20-0.13729-1.57140.059256
210.0482460.55220.290878
220.0234410.26830.394449
23-0.060245-0.68950.245852
240.4698475.37760
250.0139810.160.436557
260.0456130.52210.301255
27-0.024324-0.27840.390573
28-0.14588-1.66970.048687
29-0.031741-0.36330.358488
30-0.313688-3.59030.000233
31-0.024382-0.27910.390319
32-0.112269-1.2850.100534
330.0578520.66210.254522
340.046440.53150.297974
35-0.081568-0.93360.176118
360.4871695.57590
37-0.080155-0.91740.180307
380.1002951.14790.126546
39-0.003719-0.04260.483055
40-0.153838-1.76080.040307
410.0206170.2360.406912
42-0.306916-3.51280.000305
43-0.002247-0.02570.48976
44-0.094241-1.07860.141365
450.0776370.88860.187924
460.0197430.2260.410788
47-0.079915-0.91470.181022
480.4001754.58025e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.178762 & -2.046 & 0.021378 \tabularnewline
2 & 0.136955 & 1.5675 & 0.059702 \tabularnewline
3 & 0.018908 & 0.2164 & 0.414503 \tabularnewline
4 & -0.158108 & -1.8096 & 0.036323 \tabularnewline
5 & 0.023632 & 0.2705 & 0.393607 \tabularnewline
6 & -0.350589 & -4.0127 & 5e-05 \tabularnewline
7 & 0.031715 & 0.363 & 0.358598 \tabularnewline
8 & -0.174536 & -1.9977 & 0.023913 \tabularnewline
9 & 0.070904 & 0.8115 & 0.209264 \tabularnewline
10 & 0.083666 & 0.9576 & 0.170013 \tabularnewline
11 & -0.080661 & -0.9232 & 0.178799 \tabularnewline
12 & 0.594446 & 6.8037 & 0 \tabularnewline
13 & -0.078833 & -0.9023 & 0.184281 \tabularnewline
14 & 0.07812 & 0.8941 & 0.186448 \tabularnewline
15 & -0.019846 & -0.2271 & 0.410332 \tabularnewline
16 & -0.113557 & -1.2997 & 0.09799 \tabularnewline
17 & -0.062367 & -0.7138 & 0.238303 \tabularnewline
18 & -0.371808 & -4.2555 & 2e-05 \tabularnewline
19 & 0.00131 & 0.015 & 0.494031 \tabularnewline
20 & -0.13729 & -1.5714 & 0.059256 \tabularnewline
21 & 0.048246 & 0.5522 & 0.290878 \tabularnewline
22 & 0.023441 & 0.2683 & 0.394449 \tabularnewline
23 & -0.060245 & -0.6895 & 0.245852 \tabularnewline
24 & 0.469847 & 5.3776 & 0 \tabularnewline
25 & 0.013981 & 0.16 & 0.436557 \tabularnewline
26 & 0.045613 & 0.5221 & 0.301255 \tabularnewline
27 & -0.024324 & -0.2784 & 0.390573 \tabularnewline
28 & -0.14588 & -1.6697 & 0.048687 \tabularnewline
29 & -0.031741 & -0.3633 & 0.358488 \tabularnewline
30 & -0.313688 & -3.5903 & 0.000233 \tabularnewline
31 & -0.024382 & -0.2791 & 0.390319 \tabularnewline
32 & -0.112269 & -1.285 & 0.100534 \tabularnewline
33 & 0.057852 & 0.6621 & 0.254522 \tabularnewline
34 & 0.04644 & 0.5315 & 0.297974 \tabularnewline
35 & -0.081568 & -0.9336 & 0.176118 \tabularnewline
36 & 0.487169 & 5.5759 & 0 \tabularnewline
37 & -0.080155 & -0.9174 & 0.180307 \tabularnewline
38 & 0.100295 & 1.1479 & 0.126546 \tabularnewline
39 & -0.003719 & -0.0426 & 0.483055 \tabularnewline
40 & -0.153838 & -1.7608 & 0.040307 \tabularnewline
41 & 0.020617 & 0.236 & 0.406912 \tabularnewline
42 & -0.306916 & -3.5128 & 0.000305 \tabularnewline
43 & -0.002247 & -0.0257 & 0.48976 \tabularnewline
44 & -0.094241 & -1.0786 & 0.141365 \tabularnewline
45 & 0.077637 & 0.8886 & 0.187924 \tabularnewline
46 & 0.019743 & 0.226 & 0.410788 \tabularnewline
47 & -0.079915 & -0.9147 & 0.181022 \tabularnewline
48 & 0.400175 & 4.5802 & 5e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142484&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]-0.178762[/C][C]-2.046[/C][C]0.021378[/C][/ROW]
[ROW][C]2[/C][C]0.136955[/C][C]1.5675[/C][C]0.059702[/C][/ROW]
[ROW][C]3[/C][C]0.018908[/C][C]0.2164[/C][C]0.414503[/C][/ROW]
[ROW][C]4[/C][C]-0.158108[/C][C]-1.8096[/C][C]0.036323[/C][/ROW]
[ROW][C]5[/C][C]0.023632[/C][C]0.2705[/C][C]0.393607[/C][/ROW]
[ROW][C]6[/C][C]-0.350589[/C][C]-4.0127[/C][C]5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.031715[/C][C]0.363[/C][C]0.358598[/C][/ROW]
[ROW][C]8[/C][C]-0.174536[/C][C]-1.9977[/C][C]0.023913[/C][/ROW]
[ROW][C]9[/C][C]0.070904[/C][C]0.8115[/C][C]0.209264[/C][/ROW]
[ROW][C]10[/C][C]0.083666[/C][C]0.9576[/C][C]0.170013[/C][/ROW]
[ROW][C]11[/C][C]-0.080661[/C][C]-0.9232[/C][C]0.178799[/C][/ROW]
[ROW][C]12[/C][C]0.594446[/C][C]6.8037[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.078833[/C][C]-0.9023[/C][C]0.184281[/C][/ROW]
[ROW][C]14[/C][C]0.07812[/C][C]0.8941[/C][C]0.186448[/C][/ROW]
[ROW][C]15[/C][C]-0.019846[/C][C]-0.2271[/C][C]0.410332[/C][/ROW]
[ROW][C]16[/C][C]-0.113557[/C][C]-1.2997[/C][C]0.09799[/C][/ROW]
[ROW][C]17[/C][C]-0.062367[/C][C]-0.7138[/C][C]0.238303[/C][/ROW]
[ROW][C]18[/C][C]-0.371808[/C][C]-4.2555[/C][C]2e-05[/C][/ROW]
[ROW][C]19[/C][C]0.00131[/C][C]0.015[/C][C]0.494031[/C][/ROW]
[ROW][C]20[/C][C]-0.13729[/C][C]-1.5714[/C][C]0.059256[/C][/ROW]
[ROW][C]21[/C][C]0.048246[/C][C]0.5522[/C][C]0.290878[/C][/ROW]
[ROW][C]22[/C][C]0.023441[/C][C]0.2683[/C][C]0.394449[/C][/ROW]
[ROW][C]23[/C][C]-0.060245[/C][C]-0.6895[/C][C]0.245852[/C][/ROW]
[ROW][C]24[/C][C]0.469847[/C][C]5.3776[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.013981[/C][C]0.16[/C][C]0.436557[/C][/ROW]
[ROW][C]26[/C][C]0.045613[/C][C]0.5221[/C][C]0.301255[/C][/ROW]
[ROW][C]27[/C][C]-0.024324[/C][C]-0.2784[/C][C]0.390573[/C][/ROW]
[ROW][C]28[/C][C]-0.14588[/C][C]-1.6697[/C][C]0.048687[/C][/ROW]
[ROW][C]29[/C][C]-0.031741[/C][C]-0.3633[/C][C]0.358488[/C][/ROW]
[ROW][C]30[/C][C]-0.313688[/C][C]-3.5903[/C][C]0.000233[/C][/ROW]
[ROW][C]31[/C][C]-0.024382[/C][C]-0.2791[/C][C]0.390319[/C][/ROW]
[ROW][C]32[/C][C]-0.112269[/C][C]-1.285[/C][C]0.100534[/C][/ROW]
[ROW][C]33[/C][C]0.057852[/C][C]0.6621[/C][C]0.254522[/C][/ROW]
[ROW][C]34[/C][C]0.04644[/C][C]0.5315[/C][C]0.297974[/C][/ROW]
[ROW][C]35[/C][C]-0.081568[/C][C]-0.9336[/C][C]0.176118[/C][/ROW]
[ROW][C]36[/C][C]0.487169[/C][C]5.5759[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.080155[/C][C]-0.9174[/C][C]0.180307[/C][/ROW]
[ROW][C]38[/C][C]0.100295[/C][C]1.1479[/C][C]0.126546[/C][/ROW]
[ROW][C]39[/C][C]-0.003719[/C][C]-0.0426[/C][C]0.483055[/C][/ROW]
[ROW][C]40[/C][C]-0.153838[/C][C]-1.7608[/C][C]0.040307[/C][/ROW]
[ROW][C]41[/C][C]0.020617[/C][C]0.236[/C][C]0.406912[/C][/ROW]
[ROW][C]42[/C][C]-0.306916[/C][C]-3.5128[/C][C]0.000305[/C][/ROW]
[ROW][C]43[/C][C]-0.002247[/C][C]-0.0257[/C][C]0.48976[/C][/ROW]
[ROW][C]44[/C][C]-0.094241[/C][C]-1.0786[/C][C]0.141365[/C][/ROW]
[ROW][C]45[/C][C]0.077637[/C][C]0.8886[/C][C]0.187924[/C][/ROW]
[ROW][C]46[/C][C]0.019743[/C][C]0.226[/C][C]0.410788[/C][/ROW]
[ROW][C]47[/C][C]-0.079915[/C][C]-0.9147[/C][C]0.181022[/C][/ROW]
[ROW][C]48[/C][C]0.400175[/C][C]4.5802[/C][C]5e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142484&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142484&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
1-0.178762-2.0460.021378
20.1369551.56750.059702
30.0189080.21640.414503
4-0.158108-1.80960.036323
50.0236320.27050.393607
6-0.350589-4.01275e-05
70.0317150.3630.358598
8-0.174536-1.99770.023913
90.0709040.81150.209264
100.0836660.95760.170013
11-0.080661-0.92320.178799
120.5944466.80370
13-0.078833-0.90230.184281
140.078120.89410.186448
15-0.019846-0.22710.410332
16-0.113557-1.29970.09799
17-0.062367-0.71380.238303
18-0.371808-4.25552e-05
190.001310.0150.494031
20-0.13729-1.57140.059256
210.0482460.55220.290878
220.0234410.26830.394449
23-0.060245-0.68950.245852
240.4698475.37760
250.0139810.160.436557
260.0456130.52210.301255
27-0.024324-0.27840.390573
28-0.14588-1.66970.048687
29-0.031741-0.36330.358488
30-0.313688-3.59030.000233
31-0.024382-0.27910.390319
32-0.112269-1.2850.100534
330.0578520.66210.254522
340.046440.53150.297974
35-0.081568-0.93360.176118
360.4871695.57590
37-0.080155-0.91740.180307
380.1002951.14790.126546
39-0.003719-0.04260.483055
40-0.153838-1.76080.040307
410.0206170.2360.406912
42-0.306916-3.51280.000305
43-0.002247-0.02570.48976
44-0.094241-1.07860.141365
450.0776370.88860.187924
460.0197430.2260.410788
47-0.079915-0.91470.181022
480.4001754.58025e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.178762-2.0460.021378
20.1084661.24140.108329
30.0628480.71930.236609
4-0.167868-1.92130.028431
5-0.041453-0.47450.317983
6-0.334199-3.82510.000101
7-0.082444-0.94360.173551
8-0.156977-1.79670.037345
90.0342450.3920.347865
100.0371590.42530.335658
11-0.108172-1.23810.10895
120.4976735.69610
130.1472031.68480.047203
14-0.075479-0.86390.19461
15-0.050146-0.5740.283492
160.0023390.02680.48934
17-0.102496-1.17310.121439
18-0.217489-2.48930.007027
19-0.109665-1.25520.105826
20-0.000714-0.00820.496747
21-0.057099-0.65350.25728
22-0.137144-1.56970.059451
23-0.137555-1.57440.058905
240.1136221.30050.097864
250.1377211.57630.058686
26-0.03029-0.34670.364693
27-0.0251-0.28730.387174
28-0.099526-1.13910.128364
290.0135580.15520.43846
300.0166310.19040.424663
31-0.042675-0.48840.313029
32-0.07362-0.84260.20049
33-0.000544-0.00620.49752
340.0053090.06080.475819
35-0.168253-1.92570.028152
360.0998541.14290.127585
37-0.125051-1.43130.077367
38-0.018843-0.21570.414793
390.0397360.45480.325004
40-0.080947-0.92650.177949
41-0.019919-0.2280.410009
420.0225370.25790.398427
430.0118210.13530.446291
440.0069420.07950.468394
45-0.045452-0.52020.301895
46-0.098833-1.13120.13002
47-0.049767-0.56960.284958
48-0.061113-0.69950.242748

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.178762 & -2.046 & 0.021378 \tabularnewline
2 & 0.108466 & 1.2414 & 0.108329 \tabularnewline
3 & 0.062848 & 0.7193 & 0.236609 \tabularnewline
4 & -0.167868 & -1.9213 & 0.028431 \tabularnewline
5 & -0.041453 & -0.4745 & 0.317983 \tabularnewline
6 & -0.334199 & -3.8251 & 0.000101 \tabularnewline
7 & -0.082444 & -0.9436 & 0.173551 \tabularnewline
8 & -0.156977 & -1.7967 & 0.037345 \tabularnewline
9 & 0.034245 & 0.392 & 0.347865 \tabularnewline
10 & 0.037159 & 0.4253 & 0.335658 \tabularnewline
11 & -0.108172 & -1.2381 & 0.10895 \tabularnewline
12 & 0.497673 & 5.6961 & 0 \tabularnewline
13 & 0.147203 & 1.6848 & 0.047203 \tabularnewline
14 & -0.075479 & -0.8639 & 0.19461 \tabularnewline
15 & -0.050146 & -0.574 & 0.283492 \tabularnewline
16 & 0.002339 & 0.0268 & 0.48934 \tabularnewline
17 & -0.102496 & -1.1731 & 0.121439 \tabularnewline
18 & -0.217489 & -2.4893 & 0.007027 \tabularnewline
19 & -0.109665 & -1.2552 & 0.105826 \tabularnewline
20 & -0.000714 & -0.0082 & 0.496747 \tabularnewline
21 & -0.057099 & -0.6535 & 0.25728 \tabularnewline
22 & -0.137144 & -1.5697 & 0.059451 \tabularnewline
23 & -0.137555 & -1.5744 & 0.058905 \tabularnewline
24 & 0.113622 & 1.3005 & 0.097864 \tabularnewline
25 & 0.137721 & 1.5763 & 0.058686 \tabularnewline
26 & -0.03029 & -0.3467 & 0.364693 \tabularnewline
27 & -0.0251 & -0.2873 & 0.387174 \tabularnewline
28 & -0.099526 & -1.1391 & 0.128364 \tabularnewline
29 & 0.013558 & 0.1552 & 0.43846 \tabularnewline
30 & 0.016631 & 0.1904 & 0.424663 \tabularnewline
31 & -0.042675 & -0.4884 & 0.313029 \tabularnewline
32 & -0.07362 & -0.8426 & 0.20049 \tabularnewline
33 & -0.000544 & -0.0062 & 0.49752 \tabularnewline
34 & 0.005309 & 0.0608 & 0.475819 \tabularnewline
35 & -0.168253 & -1.9257 & 0.028152 \tabularnewline
36 & 0.099854 & 1.1429 & 0.127585 \tabularnewline
37 & -0.125051 & -1.4313 & 0.077367 \tabularnewline
38 & -0.018843 & -0.2157 & 0.414793 \tabularnewline
39 & 0.039736 & 0.4548 & 0.325004 \tabularnewline
40 & -0.080947 & -0.9265 & 0.177949 \tabularnewline
41 & -0.019919 & -0.228 & 0.410009 \tabularnewline
42 & 0.022537 & 0.2579 & 0.398427 \tabularnewline
43 & 0.011821 & 0.1353 & 0.446291 \tabularnewline
44 & 0.006942 & 0.0795 & 0.468394 \tabularnewline
45 & -0.045452 & -0.5202 & 0.301895 \tabularnewline
46 & -0.098833 & -1.1312 & 0.13002 \tabularnewline
47 & -0.049767 & -0.5696 & 0.284958 \tabularnewline
48 & -0.061113 & -0.6995 & 0.242748 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142484&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]-0.178762[/C][C]-2.046[/C][C]0.021378[/C][/ROW]
[ROW][C]2[/C][C]0.108466[/C][C]1.2414[/C][C]0.108329[/C][/ROW]
[ROW][C]3[/C][C]0.062848[/C][C]0.7193[/C][C]0.236609[/C][/ROW]
[ROW][C]4[/C][C]-0.167868[/C][C]-1.9213[/C][C]0.028431[/C][/ROW]
[ROW][C]5[/C][C]-0.041453[/C][C]-0.4745[/C][C]0.317983[/C][/ROW]
[ROW][C]6[/C][C]-0.334199[/C][C]-3.8251[/C][C]0.000101[/C][/ROW]
[ROW][C]7[/C][C]-0.082444[/C][C]-0.9436[/C][C]0.173551[/C][/ROW]
[ROW][C]8[/C][C]-0.156977[/C][C]-1.7967[/C][C]0.037345[/C][/ROW]
[ROW][C]9[/C][C]0.034245[/C][C]0.392[/C][C]0.347865[/C][/ROW]
[ROW][C]10[/C][C]0.037159[/C][C]0.4253[/C][C]0.335658[/C][/ROW]
[ROW][C]11[/C][C]-0.108172[/C][C]-1.2381[/C][C]0.10895[/C][/ROW]
[ROW][C]12[/C][C]0.497673[/C][C]5.6961[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.147203[/C][C]1.6848[/C][C]0.047203[/C][/ROW]
[ROW][C]14[/C][C]-0.075479[/C][C]-0.8639[/C][C]0.19461[/C][/ROW]
[ROW][C]15[/C][C]-0.050146[/C][C]-0.574[/C][C]0.283492[/C][/ROW]
[ROW][C]16[/C][C]0.002339[/C][C]0.0268[/C][C]0.48934[/C][/ROW]
[ROW][C]17[/C][C]-0.102496[/C][C]-1.1731[/C][C]0.121439[/C][/ROW]
[ROW][C]18[/C][C]-0.217489[/C][C]-2.4893[/C][C]0.007027[/C][/ROW]
[ROW][C]19[/C][C]-0.109665[/C][C]-1.2552[/C][C]0.105826[/C][/ROW]
[ROW][C]20[/C][C]-0.000714[/C][C]-0.0082[/C][C]0.496747[/C][/ROW]
[ROW][C]21[/C][C]-0.057099[/C][C]-0.6535[/C][C]0.25728[/C][/ROW]
[ROW][C]22[/C][C]-0.137144[/C][C]-1.5697[/C][C]0.059451[/C][/ROW]
[ROW][C]23[/C][C]-0.137555[/C][C]-1.5744[/C][C]0.058905[/C][/ROW]
[ROW][C]24[/C][C]0.113622[/C][C]1.3005[/C][C]0.097864[/C][/ROW]
[ROW][C]25[/C][C]0.137721[/C][C]1.5763[/C][C]0.058686[/C][/ROW]
[ROW][C]26[/C][C]-0.03029[/C][C]-0.3467[/C][C]0.364693[/C][/ROW]
[ROW][C]27[/C][C]-0.0251[/C][C]-0.2873[/C][C]0.387174[/C][/ROW]
[ROW][C]28[/C][C]-0.099526[/C][C]-1.1391[/C][C]0.128364[/C][/ROW]
[ROW][C]29[/C][C]0.013558[/C][C]0.1552[/C][C]0.43846[/C][/ROW]
[ROW][C]30[/C][C]0.016631[/C][C]0.1904[/C][C]0.424663[/C][/ROW]
[ROW][C]31[/C][C]-0.042675[/C][C]-0.4884[/C][C]0.313029[/C][/ROW]
[ROW][C]32[/C][C]-0.07362[/C][C]-0.8426[/C][C]0.20049[/C][/ROW]
[ROW][C]33[/C][C]-0.000544[/C][C]-0.0062[/C][C]0.49752[/C][/ROW]
[ROW][C]34[/C][C]0.005309[/C][C]0.0608[/C][C]0.475819[/C][/ROW]
[ROW][C]35[/C][C]-0.168253[/C][C]-1.9257[/C][C]0.028152[/C][/ROW]
[ROW][C]36[/C][C]0.099854[/C][C]1.1429[/C][C]0.127585[/C][/ROW]
[ROW][C]37[/C][C]-0.125051[/C][C]-1.4313[/C][C]0.077367[/C][/ROW]
[ROW][C]38[/C][C]-0.018843[/C][C]-0.2157[/C][C]0.414793[/C][/ROW]
[ROW][C]39[/C][C]0.039736[/C][C]0.4548[/C][C]0.325004[/C][/ROW]
[ROW][C]40[/C][C]-0.080947[/C][C]-0.9265[/C][C]0.177949[/C][/ROW]
[ROW][C]41[/C][C]-0.019919[/C][C]-0.228[/C][C]0.410009[/C][/ROW]
[ROW][C]42[/C][C]0.022537[/C][C]0.2579[/C][C]0.398427[/C][/ROW]
[ROW][C]43[/C][C]0.011821[/C][C]0.1353[/C][C]0.446291[/C][/ROW]
[ROW][C]44[/C][C]0.006942[/C][C]0.0795[/C][C]0.468394[/C][/ROW]
[ROW][C]45[/C][C]-0.045452[/C][C]-0.5202[/C][C]0.301895[/C][/ROW]
[ROW][C]46[/C][C]-0.098833[/C][C]-1.1312[/C][C]0.13002[/C][/ROW]
[ROW][C]47[/C][C]-0.049767[/C][C]-0.5696[/C][C]0.284958[/C][/ROW]
[ROW][C]48[/C][C]-0.061113[/C][C]-0.6995[/C][C]0.242748[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142484&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142484&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
1-0.178762-2.0460.021378
20.1084661.24140.108329
30.0628480.71930.236609
4-0.167868-1.92130.028431
5-0.041453-0.47450.317983
6-0.334199-3.82510.000101
7-0.082444-0.94360.173551
8-0.156977-1.79670.037345
90.0342450.3920.347865
100.0371590.42530.335658
11-0.108172-1.23810.10895
120.4976735.69610
130.1472031.68480.047203
14-0.075479-0.86390.19461
15-0.050146-0.5740.283492
160.0023390.02680.48934
17-0.102496-1.17310.121439
18-0.217489-2.48930.007027
19-0.109665-1.25520.105826
20-0.000714-0.00820.496747
21-0.057099-0.65350.25728
22-0.137144-1.56970.059451
23-0.137555-1.57440.058905
240.1136221.30050.097864
250.1377211.57630.058686
26-0.03029-0.34670.364693
27-0.0251-0.28730.387174
28-0.099526-1.13910.128364
290.0135580.15520.43846
300.0166310.19040.424663
31-0.042675-0.48840.313029
32-0.07362-0.84260.20049
33-0.000544-0.00620.49752
340.0053090.06080.475819
35-0.168253-1.92570.028152
360.0998541.14290.127585
37-0.125051-1.43130.077367
38-0.018843-0.21570.414793
390.0397360.45480.325004
40-0.080947-0.92650.177949
41-0.019919-0.2280.410009
420.0225370.25790.398427
430.0118210.13530.446291
440.0069420.07950.468394
45-0.045452-0.52020.301895
46-0.098833-1.13120.13002
47-0.049767-0.56960.284958
48-0.061113-0.69950.242748


Figures (Output of Computation)

Input Parameters & R Code

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