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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 computationMon, 21 Nov 2011 02:48:21 -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/21/t13218617860cluy2nxihlt3ym.htm/, Retrieved Fri, 19 Apr 2024 07:52:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145684, Retrieved Fri, 19 Apr 2024 07:52:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact112

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] [T1P2D2] [2011-11-21 07:48:21] [53dd883843ca194f19e2952e03e3e0b7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.7
0.7
0.68
0.68
0.69
0.69
0.7
0.7
0.7
0.7
0.7
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.76
0.77
0.78
0.85
0.89
0.9
0.91
0.91
0.91
0.9
0.89
0.88
0.87
0.86
0.87
0.87
0.87
0.85
0.84
0.84
0.84
0.84
0.84
0.82
0.87
0.92
0.92
0.92
0.93
0.94
0.87
0.84
0.83
0.81
0.81
0.81
0.8
0.8
0.8
0.8
0.8
0.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145684&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145684&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3659253.08330.001457
20.0941390.79320.215143
30.2622752.210.015166
40.1069390.90110.185294
5-0.117404-0.98930.162947
6-0.230157-1.93930.028217
7-0.143967-1.21310.114558
8-0.13541-1.1410.128854
9-0.106382-0.89640.186536
10-0.004034-0.0340.48649
11-0.04456-0.37550.354215
12-0.053863-0.45390.325658
13-0.005943-0.05010.480102
14-0.043735-0.36850.356791
15-0.069682-0.58720.279481
16-0.043327-0.36510.358068
17-0.023411-0.19730.422092
18-0.007808-0.06580.473864
190.0600370.50590.307255
200.0772190.65070.258683
210.2113991.78130.039572
220.1423221.19920.117214
23-0.02164-0.18230.427917
240.0941940.79370.21501
250.0930310.78390.217855
26-0.131312-1.10650.136132
27-0.278022-2.34270.010977
28-0.122278-1.03030.153175
29-0.088391-0.74480.229428
30-0.224288-1.88990.031428
31-0.086342-0.72750.234646
32-0.073473-0.61910.268919
33-0.061636-0.51940.302565
340.0051760.04360.482667
350.0099670.0840.466654
36-0.014887-0.12540.450265
370.0028420.02390.49048
380.0308380.25980.397869
39-0.013394-0.11290.45523
400.0124140.10460.458492
410.0382230.32210.374172
42-0.041606-0.35060.363472
43-0.02497-0.21040.416979
44-0.041744-0.35170.363036
45-0.028875-0.24330.404236
46-0.03757-0.31660.376249
47-0.025794-0.21730.414282
480.0555360.4680.320624

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.365925 & 3.0833 & 0.001457 \tabularnewline
2 & 0.094139 & 0.7932 & 0.215143 \tabularnewline
3 & 0.262275 & 2.21 & 0.015166 \tabularnewline
4 & 0.106939 & 0.9011 & 0.185294 \tabularnewline
5 & -0.117404 & -0.9893 & 0.162947 \tabularnewline
6 & -0.230157 & -1.9393 & 0.028217 \tabularnewline
7 & -0.143967 & -1.2131 & 0.114558 \tabularnewline
8 & -0.13541 & -1.141 & 0.128854 \tabularnewline
9 & -0.106382 & -0.8964 & 0.186536 \tabularnewline
10 & -0.004034 & -0.034 & 0.48649 \tabularnewline
11 & -0.04456 & -0.3755 & 0.354215 \tabularnewline
12 & -0.053863 & -0.4539 & 0.325658 \tabularnewline
13 & -0.005943 & -0.0501 & 0.480102 \tabularnewline
14 & -0.043735 & -0.3685 & 0.356791 \tabularnewline
15 & -0.069682 & -0.5872 & 0.279481 \tabularnewline
16 & -0.043327 & -0.3651 & 0.358068 \tabularnewline
17 & -0.023411 & -0.1973 & 0.422092 \tabularnewline
18 & -0.007808 & -0.0658 & 0.473864 \tabularnewline
19 & 0.060037 & 0.5059 & 0.307255 \tabularnewline
20 & 0.077219 & 0.6507 & 0.258683 \tabularnewline
21 & 0.211399 & 1.7813 & 0.039572 \tabularnewline
22 & 0.142322 & 1.1992 & 0.117214 \tabularnewline
23 & -0.02164 & -0.1823 & 0.427917 \tabularnewline
24 & 0.094194 & 0.7937 & 0.21501 \tabularnewline
25 & 0.093031 & 0.7839 & 0.217855 \tabularnewline
26 & -0.131312 & -1.1065 & 0.136132 \tabularnewline
27 & -0.278022 & -2.3427 & 0.010977 \tabularnewline
28 & -0.122278 & -1.0303 & 0.153175 \tabularnewline
29 & -0.088391 & -0.7448 & 0.229428 \tabularnewline
30 & -0.224288 & -1.8899 & 0.031428 \tabularnewline
31 & -0.086342 & -0.7275 & 0.234646 \tabularnewline
32 & -0.073473 & -0.6191 & 0.268919 \tabularnewline
33 & -0.061636 & -0.5194 & 0.302565 \tabularnewline
34 & 0.005176 & 0.0436 & 0.482667 \tabularnewline
35 & 0.009967 & 0.084 & 0.466654 \tabularnewline
36 & -0.014887 & -0.1254 & 0.450265 \tabularnewline
37 & 0.002842 & 0.0239 & 0.49048 \tabularnewline
38 & 0.030838 & 0.2598 & 0.397869 \tabularnewline
39 & -0.013394 & -0.1129 & 0.45523 \tabularnewline
40 & 0.012414 & 0.1046 & 0.458492 \tabularnewline
41 & 0.038223 & 0.3221 & 0.374172 \tabularnewline
42 & -0.041606 & -0.3506 & 0.363472 \tabularnewline
43 & -0.02497 & -0.2104 & 0.416979 \tabularnewline
44 & -0.041744 & -0.3517 & 0.363036 \tabularnewline
45 & -0.028875 & -0.2433 & 0.404236 \tabularnewline
46 & -0.03757 & -0.3166 & 0.376249 \tabularnewline
47 & -0.025794 & -0.2173 & 0.414282 \tabularnewline
48 & 0.055536 & 0.468 & 0.320624 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145684&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]0.365925[/C][C]3.0833[/C][C]0.001457[/C][/ROW]
[ROW][C]2[/C][C]0.094139[/C][C]0.7932[/C][C]0.215143[/C][/ROW]
[ROW][C]3[/C][C]0.262275[/C][C]2.21[/C][C]0.015166[/C][/ROW]
[ROW][C]4[/C][C]0.106939[/C][C]0.9011[/C][C]0.185294[/C][/ROW]
[ROW][C]5[/C][C]-0.117404[/C][C]-0.9893[/C][C]0.162947[/C][/ROW]
[ROW][C]6[/C][C]-0.230157[/C][C]-1.9393[/C][C]0.028217[/C][/ROW]
[ROW][C]7[/C][C]-0.143967[/C][C]-1.2131[/C][C]0.114558[/C][/ROW]
[ROW][C]8[/C][C]-0.13541[/C][C]-1.141[/C][C]0.128854[/C][/ROW]
[ROW][C]9[/C][C]-0.106382[/C][C]-0.8964[/C][C]0.186536[/C][/ROW]
[ROW][C]10[/C][C]-0.004034[/C][C]-0.034[/C][C]0.48649[/C][/ROW]
[ROW][C]11[/C][C]-0.04456[/C][C]-0.3755[/C][C]0.354215[/C][/ROW]
[ROW][C]12[/C][C]-0.053863[/C][C]-0.4539[/C][C]0.325658[/C][/ROW]
[ROW][C]13[/C][C]-0.005943[/C][C]-0.0501[/C][C]0.480102[/C][/ROW]
[ROW][C]14[/C][C]-0.043735[/C][C]-0.3685[/C][C]0.356791[/C][/ROW]
[ROW][C]15[/C][C]-0.069682[/C][C]-0.5872[/C][C]0.279481[/C][/ROW]
[ROW][C]16[/C][C]-0.043327[/C][C]-0.3651[/C][C]0.358068[/C][/ROW]
[ROW][C]17[/C][C]-0.023411[/C][C]-0.1973[/C][C]0.422092[/C][/ROW]
[ROW][C]18[/C][C]-0.007808[/C][C]-0.0658[/C][C]0.473864[/C][/ROW]
[ROW][C]19[/C][C]0.060037[/C][C]0.5059[/C][C]0.307255[/C][/ROW]
[ROW][C]20[/C][C]0.077219[/C][C]0.6507[/C][C]0.258683[/C][/ROW]
[ROW][C]21[/C][C]0.211399[/C][C]1.7813[/C][C]0.039572[/C][/ROW]
[ROW][C]22[/C][C]0.142322[/C][C]1.1992[/C][C]0.117214[/C][/ROW]
[ROW][C]23[/C][C]-0.02164[/C][C]-0.1823[/C][C]0.427917[/C][/ROW]
[ROW][C]24[/C][C]0.094194[/C][C]0.7937[/C][C]0.21501[/C][/ROW]
[ROW][C]25[/C][C]0.093031[/C][C]0.7839[/C][C]0.217855[/C][/ROW]
[ROW][C]26[/C][C]-0.131312[/C][C]-1.1065[/C][C]0.136132[/C][/ROW]
[ROW][C]27[/C][C]-0.278022[/C][C]-2.3427[/C][C]0.010977[/C][/ROW]
[ROW][C]28[/C][C]-0.122278[/C][C]-1.0303[/C][C]0.153175[/C][/ROW]
[ROW][C]29[/C][C]-0.088391[/C][C]-0.7448[/C][C]0.229428[/C][/ROW]
[ROW][C]30[/C][C]-0.224288[/C][C]-1.8899[/C][C]0.031428[/C][/ROW]
[ROW][C]31[/C][C]-0.086342[/C][C]-0.7275[/C][C]0.234646[/C][/ROW]
[ROW][C]32[/C][C]-0.073473[/C][C]-0.6191[/C][C]0.268919[/C][/ROW]
[ROW][C]33[/C][C]-0.061636[/C][C]-0.5194[/C][C]0.302565[/C][/ROW]
[ROW][C]34[/C][C]0.005176[/C][C]0.0436[/C][C]0.482667[/C][/ROW]
[ROW][C]35[/C][C]0.009967[/C][C]0.084[/C][C]0.466654[/C][/ROW]
[ROW][C]36[/C][C]-0.014887[/C][C]-0.1254[/C][C]0.450265[/C][/ROW]
[ROW][C]37[/C][C]0.002842[/C][C]0.0239[/C][C]0.49048[/C][/ROW]
[ROW][C]38[/C][C]0.030838[/C][C]0.2598[/C][C]0.397869[/C][/ROW]
[ROW][C]39[/C][C]-0.013394[/C][C]-0.1129[/C][C]0.45523[/C][/ROW]
[ROW][C]40[/C][C]0.012414[/C][C]0.1046[/C][C]0.458492[/C][/ROW]
[ROW][C]41[/C][C]0.038223[/C][C]0.3221[/C][C]0.374172[/C][/ROW]
[ROW][C]42[/C][C]-0.041606[/C][C]-0.3506[/C][C]0.363472[/C][/ROW]
[ROW][C]43[/C][C]-0.02497[/C][C]-0.2104[/C][C]0.416979[/C][/ROW]
[ROW][C]44[/C][C]-0.041744[/C][C]-0.3517[/C][C]0.363036[/C][/ROW]
[ROW][C]45[/C][C]-0.028875[/C][C]-0.2433[/C][C]0.404236[/C][/ROW]
[ROW][C]46[/C][C]-0.03757[/C][C]-0.3166[/C][C]0.376249[/C][/ROW]
[ROW][C]47[/C][C]-0.025794[/C][C]-0.2173[/C][C]0.414282[/C][/ROW]
[ROW][C]48[/C][C]0.055536[/C][C]0.468[/C][C]0.320624[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145684&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
10.3659253.08330.001457
20.0941390.79320.215143
30.2622752.210.015166
40.1069390.90110.185294
5-0.117404-0.98930.162947
6-0.230157-1.93930.028217
7-0.143967-1.21310.114558
8-0.13541-1.1410.128854
9-0.106382-0.89640.186536
10-0.004034-0.0340.48649
11-0.04456-0.37550.354215
12-0.053863-0.45390.325658
13-0.005943-0.05010.480102
14-0.043735-0.36850.356791
15-0.069682-0.58720.279481
16-0.043327-0.36510.358068
17-0.023411-0.19730.422092
18-0.007808-0.06580.473864
190.0600370.50590.307255
200.0772190.65070.258683
210.2113991.78130.039572
220.1423221.19920.117214
23-0.02164-0.18230.427917
240.0941940.79370.21501
250.0930310.78390.217855
26-0.131312-1.10650.136132
27-0.278022-2.34270.010977
28-0.122278-1.03030.153175
29-0.088391-0.74480.229428
30-0.224288-1.88990.031428
31-0.086342-0.72750.234646
32-0.073473-0.61910.268919
33-0.061636-0.51940.302565
340.0051760.04360.482667
350.0099670.0840.466654
36-0.014887-0.12540.450265
370.0028420.02390.49048
380.0308380.25980.397869
39-0.013394-0.11290.45523
400.0124140.10460.458492
410.0382230.32210.374172
42-0.041606-0.35060.363472
43-0.02497-0.21040.416979
44-0.041744-0.35170.363036
45-0.028875-0.24330.404236
46-0.03757-0.31660.376249
47-0.025794-0.21730.414282
480.0555360.4680.320624






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3659253.08330.001457
2-0.045909-0.38680.350016
30.2812142.36950.010266
4-0.10714-0.90280.184849
5-0.139313-1.17390.122184
6-0.248532-2.09420.019908
70.0022780.01920.492371
8-0.038406-0.32360.373592
90.1126740.94940.172818
100.0612310.51590.303749
11-0.088737-0.74770.228552
12-0.097984-0.82560.205891
13-0.066299-0.55860.289082
14-0.062779-0.5290.299232
150.0098510.0830.467039
160.029710.25030.401524
170.0039910.03360.486633
180.0026470.02230.491134
190.0495520.41750.338775
20-0.009393-0.07910.46857
210.2285951.92620.029043
22-0.06174-0.52020.302262
23-0.118353-0.99730.161012
240.0327420.27590.391716
250.0265480.22370.411817
26-0.10656-0.89790.18614
27-0.168622-1.42080.079871
280.0247790.20880.417605
29-0.035348-0.29780.383346
30-0.032906-0.27730.391189
310.0554990.46760.320735
32-0.169558-1.42870.078735
330.0102670.08650.465651
34-0.070348-0.59280.277612
350.023380.1970.422195
36-0.020775-0.17510.430768
370.0569660.480.316351
38-0.089058-0.75040.227741
39-0.045607-0.38430.350954
40-0.003843-0.03240.487128
41-0.041833-0.35250.362758
42-0.095283-0.80290.212366
43-0.01822-0.15350.43921
44-0.118875-1.00170.159954
450.0171460.14450.442769
46-0.058229-0.49060.312594
470.0957660.80690.211199
480.130181.09690.138192

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.365925 & 3.0833 & 0.001457 \tabularnewline
2 & -0.045909 & -0.3868 & 0.350016 \tabularnewline
3 & 0.281214 & 2.3695 & 0.010266 \tabularnewline
4 & -0.10714 & -0.9028 & 0.184849 \tabularnewline
5 & -0.139313 & -1.1739 & 0.122184 \tabularnewline
6 & -0.248532 & -2.0942 & 0.019908 \tabularnewline
7 & 0.002278 & 0.0192 & 0.492371 \tabularnewline
8 & -0.038406 & -0.3236 & 0.373592 \tabularnewline
9 & 0.112674 & 0.9494 & 0.172818 \tabularnewline
10 & 0.061231 & 0.5159 & 0.303749 \tabularnewline
11 & -0.088737 & -0.7477 & 0.228552 \tabularnewline
12 & -0.097984 & -0.8256 & 0.205891 \tabularnewline
13 & -0.066299 & -0.5586 & 0.289082 \tabularnewline
14 & -0.062779 & -0.529 & 0.299232 \tabularnewline
15 & 0.009851 & 0.083 & 0.467039 \tabularnewline
16 & 0.02971 & 0.2503 & 0.401524 \tabularnewline
17 & 0.003991 & 0.0336 & 0.486633 \tabularnewline
18 & 0.002647 & 0.0223 & 0.491134 \tabularnewline
19 & 0.049552 & 0.4175 & 0.338775 \tabularnewline
20 & -0.009393 & -0.0791 & 0.46857 \tabularnewline
21 & 0.228595 & 1.9262 & 0.029043 \tabularnewline
22 & -0.06174 & -0.5202 & 0.302262 \tabularnewline
23 & -0.118353 & -0.9973 & 0.161012 \tabularnewline
24 & 0.032742 & 0.2759 & 0.391716 \tabularnewline
25 & 0.026548 & 0.2237 & 0.411817 \tabularnewline
26 & -0.10656 & -0.8979 & 0.18614 \tabularnewline
27 & -0.168622 & -1.4208 & 0.079871 \tabularnewline
28 & 0.024779 & 0.2088 & 0.417605 \tabularnewline
29 & -0.035348 & -0.2978 & 0.383346 \tabularnewline
30 & -0.032906 & -0.2773 & 0.391189 \tabularnewline
31 & 0.055499 & 0.4676 & 0.320735 \tabularnewline
32 & -0.169558 & -1.4287 & 0.078735 \tabularnewline
33 & 0.010267 & 0.0865 & 0.465651 \tabularnewline
34 & -0.070348 & -0.5928 & 0.277612 \tabularnewline
35 & 0.02338 & 0.197 & 0.422195 \tabularnewline
36 & -0.020775 & -0.1751 & 0.430768 \tabularnewline
37 & 0.056966 & 0.48 & 0.316351 \tabularnewline
38 & -0.089058 & -0.7504 & 0.227741 \tabularnewline
39 & -0.045607 & -0.3843 & 0.350954 \tabularnewline
40 & -0.003843 & -0.0324 & 0.487128 \tabularnewline
41 & -0.041833 & -0.3525 & 0.362758 \tabularnewline
42 & -0.095283 & -0.8029 & 0.212366 \tabularnewline
43 & -0.01822 & -0.1535 & 0.43921 \tabularnewline
44 & -0.118875 & -1.0017 & 0.159954 \tabularnewline
45 & 0.017146 & 0.1445 & 0.442769 \tabularnewline
46 & -0.058229 & -0.4906 & 0.312594 \tabularnewline
47 & 0.095766 & 0.8069 & 0.211199 \tabularnewline
48 & 0.13018 & 1.0969 & 0.138192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145684&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]0.365925[/C][C]3.0833[/C][C]0.001457[/C][/ROW]
[ROW][C]2[/C][C]-0.045909[/C][C]-0.3868[/C][C]0.350016[/C][/ROW]
[ROW][C]3[/C][C]0.281214[/C][C]2.3695[/C][C]0.010266[/C][/ROW]
[ROW][C]4[/C][C]-0.10714[/C][C]-0.9028[/C][C]0.184849[/C][/ROW]
[ROW][C]5[/C][C]-0.139313[/C][C]-1.1739[/C][C]0.122184[/C][/ROW]
[ROW][C]6[/C][C]-0.248532[/C][C]-2.0942[/C][C]0.019908[/C][/ROW]
[ROW][C]7[/C][C]0.002278[/C][C]0.0192[/C][C]0.492371[/C][/ROW]
[ROW][C]8[/C][C]-0.038406[/C][C]-0.3236[/C][C]0.373592[/C][/ROW]
[ROW][C]9[/C][C]0.112674[/C][C]0.9494[/C][C]0.172818[/C][/ROW]
[ROW][C]10[/C][C]0.061231[/C][C]0.5159[/C][C]0.303749[/C][/ROW]
[ROW][C]11[/C][C]-0.088737[/C][C]-0.7477[/C][C]0.228552[/C][/ROW]
[ROW][C]12[/C][C]-0.097984[/C][C]-0.8256[/C][C]0.205891[/C][/ROW]
[ROW][C]13[/C][C]-0.066299[/C][C]-0.5586[/C][C]0.289082[/C][/ROW]
[ROW][C]14[/C][C]-0.062779[/C][C]-0.529[/C][C]0.299232[/C][/ROW]
[ROW][C]15[/C][C]0.009851[/C][C]0.083[/C][C]0.467039[/C][/ROW]
[ROW][C]16[/C][C]0.02971[/C][C]0.2503[/C][C]0.401524[/C][/ROW]
[ROW][C]17[/C][C]0.003991[/C][C]0.0336[/C][C]0.486633[/C][/ROW]
[ROW][C]18[/C][C]0.002647[/C][C]0.0223[/C][C]0.491134[/C][/ROW]
[ROW][C]19[/C][C]0.049552[/C][C]0.4175[/C][C]0.338775[/C][/ROW]
[ROW][C]20[/C][C]-0.009393[/C][C]-0.0791[/C][C]0.46857[/C][/ROW]
[ROW][C]21[/C][C]0.228595[/C][C]1.9262[/C][C]0.029043[/C][/ROW]
[ROW][C]22[/C][C]-0.06174[/C][C]-0.5202[/C][C]0.302262[/C][/ROW]
[ROW][C]23[/C][C]-0.118353[/C][C]-0.9973[/C][C]0.161012[/C][/ROW]
[ROW][C]24[/C][C]0.032742[/C][C]0.2759[/C][C]0.391716[/C][/ROW]
[ROW][C]25[/C][C]0.026548[/C][C]0.2237[/C][C]0.411817[/C][/ROW]
[ROW][C]26[/C][C]-0.10656[/C][C]-0.8979[/C][C]0.18614[/C][/ROW]
[ROW][C]27[/C][C]-0.168622[/C][C]-1.4208[/C][C]0.079871[/C][/ROW]
[ROW][C]28[/C][C]0.024779[/C][C]0.2088[/C][C]0.417605[/C][/ROW]
[ROW][C]29[/C][C]-0.035348[/C][C]-0.2978[/C][C]0.383346[/C][/ROW]
[ROW][C]30[/C][C]-0.032906[/C][C]-0.2773[/C][C]0.391189[/C][/ROW]
[ROW][C]31[/C][C]0.055499[/C][C]0.4676[/C][C]0.320735[/C][/ROW]
[ROW][C]32[/C][C]-0.169558[/C][C]-1.4287[/C][C]0.078735[/C][/ROW]
[ROW][C]33[/C][C]0.010267[/C][C]0.0865[/C][C]0.465651[/C][/ROW]
[ROW][C]34[/C][C]-0.070348[/C][C]-0.5928[/C][C]0.277612[/C][/ROW]
[ROW][C]35[/C][C]0.02338[/C][C]0.197[/C][C]0.422195[/C][/ROW]
[ROW][C]36[/C][C]-0.020775[/C][C]-0.1751[/C][C]0.430768[/C][/ROW]
[ROW][C]37[/C][C]0.056966[/C][C]0.48[/C][C]0.316351[/C][/ROW]
[ROW][C]38[/C][C]-0.089058[/C][C]-0.7504[/C][C]0.227741[/C][/ROW]
[ROW][C]39[/C][C]-0.045607[/C][C]-0.3843[/C][C]0.350954[/C][/ROW]
[ROW][C]40[/C][C]-0.003843[/C][C]-0.0324[/C][C]0.487128[/C][/ROW]
[ROW][C]41[/C][C]-0.041833[/C][C]-0.3525[/C][C]0.362758[/C][/ROW]
[ROW][C]42[/C][C]-0.095283[/C][C]-0.8029[/C][C]0.212366[/C][/ROW]
[ROW][C]43[/C][C]-0.01822[/C][C]-0.1535[/C][C]0.43921[/C][/ROW]
[ROW][C]44[/C][C]-0.118875[/C][C]-1.0017[/C][C]0.159954[/C][/ROW]
[ROW][C]45[/C][C]0.017146[/C][C]0.1445[/C][C]0.442769[/C][/ROW]
[ROW][C]46[/C][C]-0.058229[/C][C]-0.4906[/C][C]0.312594[/C][/ROW]
[ROW][C]47[/C][C]0.095766[/C][C]0.8069[/C][C]0.211199[/C][/ROW]
[ROW][C]48[/C][C]0.13018[/C][C]1.0969[/C][C]0.138192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145684&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145684&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
10.3659253.08330.001457
2-0.045909-0.38680.350016
30.2812142.36950.010266
4-0.10714-0.90280.184849
5-0.139313-1.17390.122184
6-0.248532-2.09420.019908
70.0022780.01920.492371
8-0.038406-0.32360.373592
90.1126740.94940.172818
100.0612310.51590.303749
11-0.088737-0.74770.228552
12-0.097984-0.82560.205891
13-0.066299-0.55860.289082
14-0.062779-0.5290.299232
150.0098510.0830.467039
160.029710.25030.401524
170.0039910.03360.486633
180.0026470.02230.491134
190.0495520.41750.338775
20-0.009393-0.07910.46857
210.2285951.92620.029043
22-0.06174-0.52020.302262
23-0.118353-0.99730.161012
240.0327420.27590.391716
250.0265480.22370.411817
26-0.10656-0.89790.18614
27-0.168622-1.42080.079871
280.0247790.20880.417605
29-0.035348-0.29780.383346
30-0.032906-0.27730.391189
310.0554990.46760.320735
32-0.169558-1.42870.078735
330.0102670.08650.465651
34-0.070348-0.59280.277612
350.023380.1970.422195
36-0.020775-0.17510.430768
370.0569660.480.316351
38-0.089058-0.75040.227741
39-0.045607-0.38430.350954
40-0.003843-0.03240.487128
41-0.041833-0.35250.362758
42-0.095283-0.80290.212366
43-0.01822-0.15350.43921
44-0.118875-1.00170.159954
450.0171460.14450.442769
46-0.058229-0.49060.312594
470.0957660.80690.211199
480.130181.09690.138192


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')