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Description of Statistical Computation

Author's title

Isabelle Regnard oef 6bis Koffie, thee, cacao:autocorelation, non seizoenal...

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 03 Apr 2011 16:15:46 +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/2011/Apr/03/t1301847625zhb7kzfm0old4kt.htm/, Retrieved Thu, 09 May 2024 08:18:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=120015, Retrieved Thu, 09 May 2024 08:18:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact93

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] [Isabelle Regnard ...] [2011-04-03 16:15:46] [ed119c57c1c7f005ddf1bbf80b03ea1e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106.42
106.22
106.32
105.81
105.92
107.54
107.34
107.24
107.74
105.71
105.41
106.22
106.32
106.12
106.22
105.92
105.71
105.71
105.92
105.71
105.41
104.49
101.35
99.72
99.01
97.89
95.86
94.95
95.35
95.15
95.46
95.56
95.05
94.64
93.63
93.12
93.53
97.18
96.27
95.15
97.08
101.95
103.07
103.68
102.87
102.56
103.38
103.27
102.89
102.69
101.54
102.9
101.53
101.96
101.99
101.11
101.75
101.71
104.11
103.57
103.32
103.64
103.68
103.79
103.01
101.54
101.9
103.68
104.62
104.11
105.04
104.83
105.05
104.68
107.32
109.9
109.77
110.69
110.54
110.89
110.95
109.73
110.85
110.39
110.58
110.4
111.07
110.86
111.38
111.44
110.36
110.06
108.34
107.94
107.39
107.1
107.61
107.74
106.9
106.71
106.6
108.21
110.54
110.91
109.51
110.27
111.39
112.13
111.64

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120015&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120015&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120015&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2258182.34680.01038
2-0.030704-0.31910.375139
30.0137580.1430.443286
40.1513031.57240.059393
50.1749621.81830.035898
6-0.007929-0.08240.467241
7-0.013757-0.1430.443291
8-0.058623-0.60920.271826
9-0.0205-0.2130.415847
10-0.002007-0.02090.491701
11-0.085413-0.88760.188354
120.0467920.48630.313879
130.0028170.02930.48835
14-0.070466-0.73230.232785
15-0.245005-2.54620.006151
160.02320.24110.404966
170.0427420.44420.328899
18-0.174487-1.81330.03628
19-0.131122-1.36270.087913
20-0.125212-1.30120.097973
210.0627030.65160.258011
22-0.081246-0.84430.200174
23-0.056129-0.58330.280451
24-0.085386-0.88740.188428
25-0.031806-0.33050.370816
260.1636291.70050.045959
270.0687710.71470.238173
28-0.010673-0.11090.455945
290.045710.4750.317863
300.0715290.74340.229442
310.0340970.35430.361884
32-0.044089-0.45820.32387
330.1327621.37970.085264
340.0353780.36770.356925
350.0763190.79310.21472
36-0.058399-0.60690.272594
370.0184830.19210.424021
380.0870750.90490.183765
390.0351390.36520.357847
40-0.015015-0.1560.438145
41-0.060001-0.62350.26712
42-0.0267-0.27750.390974
430.0500990.52060.301839
44-0.033976-0.35310.362356
450.0064550.06710.473321
46-0.019727-0.2050.418976
47-0.022562-0.23450.407531
48-0.068322-0.710.23961

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.225818 & 2.3468 & 0.01038 \tabularnewline
2 & -0.030704 & -0.3191 & 0.375139 \tabularnewline
3 & 0.013758 & 0.143 & 0.443286 \tabularnewline
4 & 0.151303 & 1.5724 & 0.059393 \tabularnewline
5 & 0.174962 & 1.8183 & 0.035898 \tabularnewline
6 & -0.007929 & -0.0824 & 0.467241 \tabularnewline
7 & -0.013757 & -0.143 & 0.443291 \tabularnewline
8 & -0.058623 & -0.6092 & 0.271826 \tabularnewline
9 & -0.0205 & -0.213 & 0.415847 \tabularnewline
10 & -0.002007 & -0.0209 & 0.491701 \tabularnewline
11 & -0.085413 & -0.8876 & 0.188354 \tabularnewline
12 & 0.046792 & 0.4863 & 0.313879 \tabularnewline
13 & 0.002817 & 0.0293 & 0.48835 \tabularnewline
14 & -0.070466 & -0.7323 & 0.232785 \tabularnewline
15 & -0.245005 & -2.5462 & 0.006151 \tabularnewline
16 & 0.0232 & 0.2411 & 0.404966 \tabularnewline
17 & 0.042742 & 0.4442 & 0.328899 \tabularnewline
18 & -0.174487 & -1.8133 & 0.03628 \tabularnewline
19 & -0.131122 & -1.3627 & 0.087913 \tabularnewline
20 & -0.125212 & -1.3012 & 0.097973 \tabularnewline
21 & 0.062703 & 0.6516 & 0.258011 \tabularnewline
22 & -0.081246 & -0.8443 & 0.200174 \tabularnewline
23 & -0.056129 & -0.5833 & 0.280451 \tabularnewline
24 & -0.085386 & -0.8874 & 0.188428 \tabularnewline
25 & -0.031806 & -0.3305 & 0.370816 \tabularnewline
26 & 0.163629 & 1.7005 & 0.045959 \tabularnewline
27 & 0.068771 & 0.7147 & 0.238173 \tabularnewline
28 & -0.010673 & -0.1109 & 0.455945 \tabularnewline
29 & 0.04571 & 0.475 & 0.317863 \tabularnewline
30 & 0.071529 & 0.7434 & 0.229442 \tabularnewline
31 & 0.034097 & 0.3543 & 0.361884 \tabularnewline
32 & -0.044089 & -0.4582 & 0.32387 \tabularnewline
33 & 0.132762 & 1.3797 & 0.085264 \tabularnewline
34 & 0.035378 & 0.3677 & 0.356925 \tabularnewline
35 & 0.076319 & 0.7931 & 0.21472 \tabularnewline
36 & -0.058399 & -0.6069 & 0.272594 \tabularnewline
37 & 0.018483 & 0.1921 & 0.424021 \tabularnewline
38 & 0.087075 & 0.9049 & 0.183765 \tabularnewline
39 & 0.035139 & 0.3652 & 0.357847 \tabularnewline
40 & -0.015015 & -0.156 & 0.438145 \tabularnewline
41 & -0.060001 & -0.6235 & 0.26712 \tabularnewline
42 & -0.0267 & -0.2775 & 0.390974 \tabularnewline
43 & 0.050099 & 0.5206 & 0.301839 \tabularnewline
44 & -0.033976 & -0.3531 & 0.362356 \tabularnewline
45 & 0.006455 & 0.0671 & 0.473321 \tabularnewline
46 & -0.019727 & -0.205 & 0.418976 \tabularnewline
47 & -0.022562 & -0.2345 & 0.407531 \tabularnewline
48 & -0.068322 & -0.71 & 0.23961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120015&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]0.225818[/C][C]2.3468[/C][C]0.01038[/C][/ROW]
[ROW][C]2[/C][C]-0.030704[/C][C]-0.3191[/C][C]0.375139[/C][/ROW]
[ROW][C]3[/C][C]0.013758[/C][C]0.143[/C][C]0.443286[/C][/ROW]
[ROW][C]4[/C][C]0.151303[/C][C]1.5724[/C][C]0.059393[/C][/ROW]
[ROW][C]5[/C][C]0.174962[/C][C]1.8183[/C][C]0.035898[/C][/ROW]
[ROW][C]6[/C][C]-0.007929[/C][C]-0.0824[/C][C]0.467241[/C][/ROW]
[ROW][C]7[/C][C]-0.013757[/C][C]-0.143[/C][C]0.443291[/C][/ROW]
[ROW][C]8[/C][C]-0.058623[/C][C]-0.6092[/C][C]0.271826[/C][/ROW]
[ROW][C]9[/C][C]-0.0205[/C][C]-0.213[/C][C]0.415847[/C][/ROW]
[ROW][C]10[/C][C]-0.002007[/C][C]-0.0209[/C][C]0.491701[/C][/ROW]
[ROW][C]11[/C][C]-0.085413[/C][C]-0.8876[/C][C]0.188354[/C][/ROW]
[ROW][C]12[/C][C]0.046792[/C][C]0.4863[/C][C]0.313879[/C][/ROW]
[ROW][C]13[/C][C]0.002817[/C][C]0.0293[/C][C]0.48835[/C][/ROW]
[ROW][C]14[/C][C]-0.070466[/C][C]-0.7323[/C][C]0.232785[/C][/ROW]
[ROW][C]15[/C][C]-0.245005[/C][C]-2.5462[/C][C]0.006151[/C][/ROW]
[ROW][C]16[/C][C]0.0232[/C][C]0.2411[/C][C]0.404966[/C][/ROW]
[ROW][C]17[/C][C]0.042742[/C][C]0.4442[/C][C]0.328899[/C][/ROW]
[ROW][C]18[/C][C]-0.174487[/C][C]-1.8133[/C][C]0.03628[/C][/ROW]
[ROW][C]19[/C][C]-0.131122[/C][C]-1.3627[/C][C]0.087913[/C][/ROW]
[ROW][C]20[/C][C]-0.125212[/C][C]-1.3012[/C][C]0.097973[/C][/ROW]
[ROW][C]21[/C][C]0.062703[/C][C]0.6516[/C][C]0.258011[/C][/ROW]
[ROW][C]22[/C][C]-0.081246[/C][C]-0.8443[/C][C]0.200174[/C][/ROW]
[ROW][C]23[/C][C]-0.056129[/C][C]-0.5833[/C][C]0.280451[/C][/ROW]
[ROW][C]24[/C][C]-0.085386[/C][C]-0.8874[/C][C]0.188428[/C][/ROW]
[ROW][C]25[/C][C]-0.031806[/C][C]-0.3305[/C][C]0.370816[/C][/ROW]
[ROW][C]26[/C][C]0.163629[/C][C]1.7005[/C][C]0.045959[/C][/ROW]
[ROW][C]27[/C][C]0.068771[/C][C]0.7147[/C][C]0.238173[/C][/ROW]
[ROW][C]28[/C][C]-0.010673[/C][C]-0.1109[/C][C]0.455945[/C][/ROW]
[ROW][C]29[/C][C]0.04571[/C][C]0.475[/C][C]0.317863[/C][/ROW]
[ROW][C]30[/C][C]0.071529[/C][C]0.7434[/C][C]0.229442[/C][/ROW]
[ROW][C]31[/C][C]0.034097[/C][C]0.3543[/C][C]0.361884[/C][/ROW]
[ROW][C]32[/C][C]-0.044089[/C][C]-0.4582[/C][C]0.32387[/C][/ROW]
[ROW][C]33[/C][C]0.132762[/C][C]1.3797[/C][C]0.085264[/C][/ROW]
[ROW][C]34[/C][C]0.035378[/C][C]0.3677[/C][C]0.356925[/C][/ROW]
[ROW][C]35[/C][C]0.076319[/C][C]0.7931[/C][C]0.21472[/C][/ROW]
[ROW][C]36[/C][C]-0.058399[/C][C]-0.6069[/C][C]0.272594[/C][/ROW]
[ROW][C]37[/C][C]0.018483[/C][C]0.1921[/C][C]0.424021[/C][/ROW]
[ROW][C]38[/C][C]0.087075[/C][C]0.9049[/C][C]0.183765[/C][/ROW]
[ROW][C]39[/C][C]0.035139[/C][C]0.3652[/C][C]0.357847[/C][/ROW]
[ROW][C]40[/C][C]-0.015015[/C][C]-0.156[/C][C]0.438145[/C][/ROW]
[ROW][C]41[/C][C]-0.060001[/C][C]-0.6235[/C][C]0.26712[/C][/ROW]
[ROW][C]42[/C][C]-0.0267[/C][C]-0.2775[/C][C]0.390974[/C][/ROW]
[ROW][C]43[/C][C]0.050099[/C][C]0.5206[/C][C]0.301839[/C][/ROW]
[ROW][C]44[/C][C]-0.033976[/C][C]-0.3531[/C][C]0.362356[/C][/ROW]
[ROW][C]45[/C][C]0.006455[/C][C]0.0671[/C][C]0.473321[/C][/ROW]
[ROW][C]46[/C][C]-0.019727[/C][C]-0.205[/C][C]0.418976[/C][/ROW]
[ROW][C]47[/C][C]-0.022562[/C][C]-0.2345[/C][C]0.407531[/C][/ROW]
[ROW][C]48[/C][C]-0.068322[/C][C]-0.71[/C][C]0.23961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120015&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120015&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
10.2258182.34680.01038
2-0.030704-0.31910.375139
30.0137580.1430.443286
40.1513031.57240.059393
50.1749621.81830.035898
6-0.007929-0.08240.467241
7-0.013757-0.1430.443291
8-0.058623-0.60920.271826
9-0.0205-0.2130.415847
10-0.002007-0.02090.491701
11-0.085413-0.88760.188354
120.0467920.48630.313879
130.0028170.02930.48835
14-0.070466-0.73230.232785
15-0.245005-2.54620.006151
160.02320.24110.404966
170.0427420.44420.328899
18-0.174487-1.81330.03628
19-0.131122-1.36270.087913
20-0.125212-1.30120.097973
210.0627030.65160.258011
22-0.081246-0.84430.200174
23-0.056129-0.58330.280451
24-0.085386-0.88740.188428
25-0.031806-0.33050.370816
260.1636291.70050.045959
270.0687710.71470.238173
28-0.010673-0.11090.455945
290.045710.4750.317863
300.0715290.74340.229442
310.0340970.35430.361884
32-0.044089-0.45820.32387
330.1327621.37970.085264
340.0353780.36770.356925
350.0763190.79310.21472
36-0.058399-0.60690.272594
370.0184830.19210.424021
380.0870750.90490.183765
390.0351390.36520.357847
40-0.015015-0.1560.438145
41-0.060001-0.62350.26712
42-0.0267-0.27750.390974
430.0500990.52060.301839
44-0.033976-0.35310.362356
450.0064550.06710.473321
46-0.019727-0.2050.418976
47-0.022562-0.23450.407531
48-0.068322-0.710.23961






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2258182.34680.01038
2-0.086087-0.89460.186483
30.0432380.44930.327043
40.1437391.49380.069075
50.1163571.20920.11461
6-0.063616-0.66110.254973
70.0172010.17880.429232
8-0.09207-0.95680.170397
9-0.028753-0.29880.382828
10-0.011355-0.1180.453141
11-0.080608-0.83770.202025
120.1112721.15640.12504
13-0.014001-0.14550.442291
14-0.061761-0.64180.26117
15-0.221022-2.29690.011776
160.1438341.49480.068946
17-0.062157-0.6460.259839
18-0.165733-1.72240.043934
190.0129930.1350.446422
20-0.072793-0.75650.225502
210.0841320.87430.191941
22-0.127549-1.32550.093897
230.0584190.60710.272528
24-0.100818-1.04770.14855
250.0379180.39410.347159
260.1126751.1710.122097
270.0699040.72650.234565
28-0.031744-0.32990.371059
290.0456590.47450.31805
30-0.01279-0.13290.447252
31-0.022776-0.23670.406671
32-0.038806-0.40330.343769
330.0523260.54380.293855
340.0025860.02690.489305
350.0781780.81240.209161
36-0.082507-0.85740.196552
370.0145260.1510.440144
380.0235750.2450.403461
39-0.034698-0.36060.359555
40-0.054225-0.56350.287124
410.0715630.74370.229336
42-0.098577-1.02440.153958
430.0510170.53020.298537
440.0023240.02420.490387
450.0767830.79790.213326
46-0.023122-0.24030.40528
47-0.056946-0.59180.27761
480.0205560.21360.41562

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.225818 & 2.3468 & 0.01038 \tabularnewline
2 & -0.086087 & -0.8946 & 0.186483 \tabularnewline
3 & 0.043238 & 0.4493 & 0.327043 \tabularnewline
4 & 0.143739 & 1.4938 & 0.069075 \tabularnewline
5 & 0.116357 & 1.2092 & 0.11461 \tabularnewline
6 & -0.063616 & -0.6611 & 0.254973 \tabularnewline
7 & 0.017201 & 0.1788 & 0.429232 \tabularnewline
8 & -0.09207 & -0.9568 & 0.170397 \tabularnewline
9 & -0.028753 & -0.2988 & 0.382828 \tabularnewline
10 & -0.011355 & -0.118 & 0.453141 \tabularnewline
11 & -0.080608 & -0.8377 & 0.202025 \tabularnewline
12 & 0.111272 & 1.1564 & 0.12504 \tabularnewline
13 & -0.014001 & -0.1455 & 0.442291 \tabularnewline
14 & -0.061761 & -0.6418 & 0.26117 \tabularnewline
15 & -0.221022 & -2.2969 & 0.011776 \tabularnewline
16 & 0.143834 & 1.4948 & 0.068946 \tabularnewline
17 & -0.062157 & -0.646 & 0.259839 \tabularnewline
18 & -0.165733 & -1.7224 & 0.043934 \tabularnewline
19 & 0.012993 & 0.135 & 0.446422 \tabularnewline
20 & -0.072793 & -0.7565 & 0.225502 \tabularnewline
21 & 0.084132 & 0.8743 & 0.191941 \tabularnewline
22 & -0.127549 & -1.3255 & 0.093897 \tabularnewline
23 & 0.058419 & 0.6071 & 0.272528 \tabularnewline
24 & -0.100818 & -1.0477 & 0.14855 \tabularnewline
25 & 0.037918 & 0.3941 & 0.347159 \tabularnewline
26 & 0.112675 & 1.171 & 0.122097 \tabularnewline
27 & 0.069904 & 0.7265 & 0.234565 \tabularnewline
28 & -0.031744 & -0.3299 & 0.371059 \tabularnewline
29 & 0.045659 & 0.4745 & 0.31805 \tabularnewline
30 & -0.01279 & -0.1329 & 0.447252 \tabularnewline
31 & -0.022776 & -0.2367 & 0.406671 \tabularnewline
32 & -0.038806 & -0.4033 & 0.343769 \tabularnewline
33 & 0.052326 & 0.5438 & 0.293855 \tabularnewline
34 & 0.002586 & 0.0269 & 0.489305 \tabularnewline
35 & 0.078178 & 0.8124 & 0.209161 \tabularnewline
36 & -0.082507 & -0.8574 & 0.196552 \tabularnewline
37 & 0.014526 & 0.151 & 0.440144 \tabularnewline
38 & 0.023575 & 0.245 & 0.403461 \tabularnewline
39 & -0.034698 & -0.3606 & 0.359555 \tabularnewline
40 & -0.054225 & -0.5635 & 0.287124 \tabularnewline
41 & 0.071563 & 0.7437 & 0.229336 \tabularnewline
42 & -0.098577 & -1.0244 & 0.153958 \tabularnewline
43 & 0.051017 & 0.5302 & 0.298537 \tabularnewline
44 & 0.002324 & 0.0242 & 0.490387 \tabularnewline
45 & 0.076783 & 0.7979 & 0.213326 \tabularnewline
46 & -0.023122 & -0.2403 & 0.40528 \tabularnewline
47 & -0.056946 & -0.5918 & 0.27761 \tabularnewline
48 & 0.020556 & 0.2136 & 0.41562 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120015&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]0.225818[/C][C]2.3468[/C][C]0.01038[/C][/ROW]
[ROW][C]2[/C][C]-0.086087[/C][C]-0.8946[/C][C]0.186483[/C][/ROW]
[ROW][C]3[/C][C]0.043238[/C][C]0.4493[/C][C]0.327043[/C][/ROW]
[ROW][C]4[/C][C]0.143739[/C][C]1.4938[/C][C]0.069075[/C][/ROW]
[ROW][C]5[/C][C]0.116357[/C][C]1.2092[/C][C]0.11461[/C][/ROW]
[ROW][C]6[/C][C]-0.063616[/C][C]-0.6611[/C][C]0.254973[/C][/ROW]
[ROW][C]7[/C][C]0.017201[/C][C]0.1788[/C][C]0.429232[/C][/ROW]
[ROW][C]8[/C][C]-0.09207[/C][C]-0.9568[/C][C]0.170397[/C][/ROW]
[ROW][C]9[/C][C]-0.028753[/C][C]-0.2988[/C][C]0.382828[/C][/ROW]
[ROW][C]10[/C][C]-0.011355[/C][C]-0.118[/C][C]0.453141[/C][/ROW]
[ROW][C]11[/C][C]-0.080608[/C][C]-0.8377[/C][C]0.202025[/C][/ROW]
[ROW][C]12[/C][C]0.111272[/C][C]1.1564[/C][C]0.12504[/C][/ROW]
[ROW][C]13[/C][C]-0.014001[/C][C]-0.1455[/C][C]0.442291[/C][/ROW]
[ROW][C]14[/C][C]-0.061761[/C][C]-0.6418[/C][C]0.26117[/C][/ROW]
[ROW][C]15[/C][C]-0.221022[/C][C]-2.2969[/C][C]0.011776[/C][/ROW]
[ROW][C]16[/C][C]0.143834[/C][C]1.4948[/C][C]0.068946[/C][/ROW]
[ROW][C]17[/C][C]-0.062157[/C][C]-0.646[/C][C]0.259839[/C][/ROW]
[ROW][C]18[/C][C]-0.165733[/C][C]-1.7224[/C][C]0.043934[/C][/ROW]
[ROW][C]19[/C][C]0.012993[/C][C]0.135[/C][C]0.446422[/C][/ROW]
[ROW][C]20[/C][C]-0.072793[/C][C]-0.7565[/C][C]0.225502[/C][/ROW]
[ROW][C]21[/C][C]0.084132[/C][C]0.8743[/C][C]0.191941[/C][/ROW]
[ROW][C]22[/C][C]-0.127549[/C][C]-1.3255[/C][C]0.093897[/C][/ROW]
[ROW][C]23[/C][C]0.058419[/C][C]0.6071[/C][C]0.272528[/C][/ROW]
[ROW][C]24[/C][C]-0.100818[/C][C]-1.0477[/C][C]0.14855[/C][/ROW]
[ROW][C]25[/C][C]0.037918[/C][C]0.3941[/C][C]0.347159[/C][/ROW]
[ROW][C]26[/C][C]0.112675[/C][C]1.171[/C][C]0.122097[/C][/ROW]
[ROW][C]27[/C][C]0.069904[/C][C]0.7265[/C][C]0.234565[/C][/ROW]
[ROW][C]28[/C][C]-0.031744[/C][C]-0.3299[/C][C]0.371059[/C][/ROW]
[ROW][C]29[/C][C]0.045659[/C][C]0.4745[/C][C]0.31805[/C][/ROW]
[ROW][C]30[/C][C]-0.01279[/C][C]-0.1329[/C][C]0.447252[/C][/ROW]
[ROW][C]31[/C][C]-0.022776[/C][C]-0.2367[/C][C]0.406671[/C][/ROW]
[ROW][C]32[/C][C]-0.038806[/C][C]-0.4033[/C][C]0.343769[/C][/ROW]
[ROW][C]33[/C][C]0.052326[/C][C]0.5438[/C][C]0.293855[/C][/ROW]
[ROW][C]34[/C][C]0.002586[/C][C]0.0269[/C][C]0.489305[/C][/ROW]
[ROW][C]35[/C][C]0.078178[/C][C]0.8124[/C][C]0.209161[/C][/ROW]
[ROW][C]36[/C][C]-0.082507[/C][C]-0.8574[/C][C]0.196552[/C][/ROW]
[ROW][C]37[/C][C]0.014526[/C][C]0.151[/C][C]0.440144[/C][/ROW]
[ROW][C]38[/C][C]0.023575[/C][C]0.245[/C][C]0.403461[/C][/ROW]
[ROW][C]39[/C][C]-0.034698[/C][C]-0.3606[/C][C]0.359555[/C][/ROW]
[ROW][C]40[/C][C]-0.054225[/C][C]-0.5635[/C][C]0.287124[/C][/ROW]
[ROW][C]41[/C][C]0.071563[/C][C]0.7437[/C][C]0.229336[/C][/ROW]
[ROW][C]42[/C][C]-0.098577[/C][C]-1.0244[/C][C]0.153958[/C][/ROW]
[ROW][C]43[/C][C]0.051017[/C][C]0.5302[/C][C]0.298537[/C][/ROW]
[ROW][C]44[/C][C]0.002324[/C][C]0.0242[/C][C]0.490387[/C][/ROW]
[ROW][C]45[/C][C]0.076783[/C][C]0.7979[/C][C]0.213326[/C][/ROW]
[ROW][C]46[/C][C]-0.023122[/C][C]-0.2403[/C][C]0.40528[/C][/ROW]
[ROW][C]47[/C][C]-0.056946[/C][C]-0.5918[/C][C]0.27761[/C][/ROW]
[ROW][C]48[/C][C]0.020556[/C][C]0.2136[/C][C]0.41562[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120015&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120015&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
10.2258182.34680.01038
2-0.086087-0.89460.186483
30.0432380.44930.327043
40.1437391.49380.069075
50.1163571.20920.11461
6-0.063616-0.66110.254973
70.0172010.17880.429232
8-0.09207-0.95680.170397
9-0.028753-0.29880.382828
10-0.011355-0.1180.453141
11-0.080608-0.83770.202025
120.1112721.15640.12504
13-0.014001-0.14550.442291
14-0.061761-0.64180.26117
15-0.221022-2.29690.011776
160.1438341.49480.068946
17-0.062157-0.6460.259839
18-0.165733-1.72240.043934
190.0129930.1350.446422
20-0.072793-0.75650.225502
210.0841320.87430.191941
22-0.127549-1.32550.093897
230.0584190.60710.272528
24-0.100818-1.04770.14855
250.0379180.39410.347159
260.1126751.1710.122097
270.0699040.72650.234565
28-0.031744-0.32990.371059
290.0456590.47450.31805
30-0.01279-0.13290.447252
31-0.022776-0.23670.406671
32-0.038806-0.40330.343769
330.0523260.54380.293855
340.0025860.02690.489305
350.0781780.81240.209161
36-0.082507-0.85740.196552
370.0145260.1510.440144
380.0235750.2450.403461
39-0.034698-0.36060.359555
40-0.054225-0.56350.287124
410.0715630.74370.229336
42-0.098577-1.02440.153958
430.0510170.53020.298537
440.0023240.02420.490387
450.0767830.79790.213326
46-0.023122-0.24030.40528
47-0.056946-0.59180.27761
480.0205560.21360.41562


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')