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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 computationThu, 22 Oct 2015 14:20:01 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Oct/22/t1445520059gap2cdewdls2mi4.htm/, Retrieved Sat, 25 May 2024 17:33:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=282757, Retrieved Sat, 25 May 2024 17:33:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156

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] [] [2015-10-22 13:20:01] [2c14a834423fb5dcfbeb4b507321e1ef] [Current]
- R  D    [(Partial) Autocorrelation Function] [] [2016-01-11 20:12:44] [bd4e4aa6178eab1df445b78d9e683708]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92,09
93,77
94,44
94,91
94,78
94,51
94,36
96,6
96,72
96,71
97,44
97,83
98,92
97,98
98,76
99,76
99,87
100,09
100,07
99,46
100,4
101,25
102,29
102,1
105,91
108,95
110,07
109,92
109,87
110,54
110,79
110,32
110,76
110,24
110,27
110,11
110,39
111,05
110,85
110,24
108,7
109,93
109,53
109,83
107,86
104,61
103,61
103,11
102,59
102,91
101,94
101,8
102,25
102,6
102,49
102,13
100,76
100,86
101,12
100,74
99,99
99,39
99,52
99,21
99,38
99,37
99,38
99,26
99,36
99,2
98,53
98,65
99,15
100,17
99,98
100,07
99,94
100,05
99,13
98,74
98,64
98,44
98,81
98,88
99,63
100,08
100,07
100,55
99,98
99,89
99,86
99,61
100,12
100,24
100,1
99,86
97,99
97,57
98,28
97,97
97,99
97,84
97,33
96,7
96,79
96,76
96,23
96,29

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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282757&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282757&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282757&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3391433.50810.000331
20.1393031.4410.076258
30.0797540.8250.205609
40.1308181.35320.089423
50.2313522.39310.009224
60.1119511.1580.124716
70.0244030.25240.400597
80.0458240.4740.318229
90.0584450.60460.273375
100.1654821.71180.044919
110.1196091.23720.109351
120.0775570.80230.21209
130.0775040.80170.212249
140.0975311.00890.157656
150.0356560.36880.356494
160.0038350.03970.484215
170.1777771.83890.034348
180.0300370.31070.378315
19-0.081266-0.84060.201217
20-0.209896-2.17120.016064
21-0.128716-1.33140.092936
22-0.025417-0.26290.396561
230.0061680.06380.474622
24-0.069165-0.71540.237946
25-0.005237-0.05420.478452
26-0.051611-0.53390.297269
270.0113060.11690.453561
28-0.060308-0.62380.267033
29-0.031867-0.32960.371162
30-0.10028-1.03730.150965
31-0.069375-0.71760.237278
32-0.058755-0.60780.272314
33-0.067179-0.69490.24431
34-0.00657-0.0680.472973
35-0.083122-0.85980.195905
36-0.039474-0.40830.341925
37-0.113075-1.16970.12237
38-0.146337-1.51370.066523
39-0.103852-1.07430.142563
400.0148630.15370.439052
41-0.022303-0.23070.408993
42-0.052968-0.54790.29245
43-0.054599-0.56480.286705
44-0.111343-1.15170.125997
45-0.071113-0.73560.231793
460.0056590.05850.476715
470.0079160.08190.467447
480.0310570.32130.37432

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.339143 & 3.5081 & 0.000331 \tabularnewline
2 & 0.139303 & 1.441 & 0.076258 \tabularnewline
3 & 0.079754 & 0.825 & 0.205609 \tabularnewline
4 & 0.130818 & 1.3532 & 0.089423 \tabularnewline
5 & 0.231352 & 2.3931 & 0.009224 \tabularnewline
6 & 0.111951 & 1.158 & 0.124716 \tabularnewline
7 & 0.024403 & 0.2524 & 0.400597 \tabularnewline
8 & 0.045824 & 0.474 & 0.318229 \tabularnewline
9 & 0.058445 & 0.6046 & 0.273375 \tabularnewline
10 & 0.165482 & 1.7118 & 0.044919 \tabularnewline
11 & 0.119609 & 1.2372 & 0.109351 \tabularnewline
12 & 0.077557 & 0.8023 & 0.21209 \tabularnewline
13 & 0.077504 & 0.8017 & 0.212249 \tabularnewline
14 & 0.097531 & 1.0089 & 0.157656 \tabularnewline
15 & 0.035656 & 0.3688 & 0.356494 \tabularnewline
16 & 0.003835 & 0.0397 & 0.484215 \tabularnewline
17 & 0.177777 & 1.8389 & 0.034348 \tabularnewline
18 & 0.030037 & 0.3107 & 0.378315 \tabularnewline
19 & -0.081266 & -0.8406 & 0.201217 \tabularnewline
20 & -0.209896 & -2.1712 & 0.016064 \tabularnewline
21 & -0.128716 & -1.3314 & 0.092936 \tabularnewline
22 & -0.025417 & -0.2629 & 0.396561 \tabularnewline
23 & 0.006168 & 0.0638 & 0.474622 \tabularnewline
24 & -0.069165 & -0.7154 & 0.237946 \tabularnewline
25 & -0.005237 & -0.0542 & 0.478452 \tabularnewline
26 & -0.051611 & -0.5339 & 0.297269 \tabularnewline
27 & 0.011306 & 0.1169 & 0.453561 \tabularnewline
28 & -0.060308 & -0.6238 & 0.267033 \tabularnewline
29 & -0.031867 & -0.3296 & 0.371162 \tabularnewline
30 & -0.10028 & -1.0373 & 0.150965 \tabularnewline
31 & -0.069375 & -0.7176 & 0.237278 \tabularnewline
32 & -0.058755 & -0.6078 & 0.272314 \tabularnewline
33 & -0.067179 & -0.6949 & 0.24431 \tabularnewline
34 & -0.00657 & -0.068 & 0.472973 \tabularnewline
35 & -0.083122 & -0.8598 & 0.195905 \tabularnewline
36 & -0.039474 & -0.4083 & 0.341925 \tabularnewline
37 & -0.113075 & -1.1697 & 0.12237 \tabularnewline
38 & -0.146337 & -1.5137 & 0.066523 \tabularnewline
39 & -0.103852 & -1.0743 & 0.142563 \tabularnewline
40 & 0.014863 & 0.1537 & 0.439052 \tabularnewline
41 & -0.022303 & -0.2307 & 0.408993 \tabularnewline
42 & -0.052968 & -0.5479 & 0.29245 \tabularnewline
43 & -0.054599 & -0.5648 & 0.286705 \tabularnewline
44 & -0.111343 & -1.1517 & 0.125997 \tabularnewline
45 & -0.071113 & -0.7356 & 0.231793 \tabularnewline
46 & 0.005659 & 0.0585 & 0.476715 \tabularnewline
47 & 0.007916 & 0.0819 & 0.467447 \tabularnewline
48 & 0.031057 & 0.3213 & 0.37432 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282757&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]0.339143[/C][C]3.5081[/C][C]0.000331[/C][/ROW]
[ROW][C]2[/C][C]0.139303[/C][C]1.441[/C][C]0.076258[/C][/ROW]
[ROW][C]3[/C][C]0.079754[/C][C]0.825[/C][C]0.205609[/C][/ROW]
[ROW][C]4[/C][C]0.130818[/C][C]1.3532[/C][C]0.089423[/C][/ROW]
[ROW][C]5[/C][C]0.231352[/C][C]2.3931[/C][C]0.009224[/C][/ROW]
[ROW][C]6[/C][C]0.111951[/C][C]1.158[/C][C]0.124716[/C][/ROW]
[ROW][C]7[/C][C]0.024403[/C][C]0.2524[/C][C]0.400597[/C][/ROW]
[ROW][C]8[/C][C]0.045824[/C][C]0.474[/C][C]0.318229[/C][/ROW]
[ROW][C]9[/C][C]0.058445[/C][C]0.6046[/C][C]0.273375[/C][/ROW]
[ROW][C]10[/C][C]0.165482[/C][C]1.7118[/C][C]0.044919[/C][/ROW]
[ROW][C]11[/C][C]0.119609[/C][C]1.2372[/C][C]0.109351[/C][/ROW]
[ROW][C]12[/C][C]0.077557[/C][C]0.8023[/C][C]0.21209[/C][/ROW]
[ROW][C]13[/C][C]0.077504[/C][C]0.8017[/C][C]0.212249[/C][/ROW]
[ROW][C]14[/C][C]0.097531[/C][C]1.0089[/C][C]0.157656[/C][/ROW]
[ROW][C]15[/C][C]0.035656[/C][C]0.3688[/C][C]0.356494[/C][/ROW]
[ROW][C]16[/C][C]0.003835[/C][C]0.0397[/C][C]0.484215[/C][/ROW]
[ROW][C]17[/C][C]0.177777[/C][C]1.8389[/C][C]0.034348[/C][/ROW]
[ROW][C]18[/C][C]0.030037[/C][C]0.3107[/C][C]0.378315[/C][/ROW]
[ROW][C]19[/C][C]-0.081266[/C][C]-0.8406[/C][C]0.201217[/C][/ROW]
[ROW][C]20[/C][C]-0.209896[/C][C]-2.1712[/C][C]0.016064[/C][/ROW]
[ROW][C]21[/C][C]-0.128716[/C][C]-1.3314[/C][C]0.092936[/C][/ROW]
[ROW][C]22[/C][C]-0.025417[/C][C]-0.2629[/C][C]0.396561[/C][/ROW]
[ROW][C]23[/C][C]0.006168[/C][C]0.0638[/C][C]0.474622[/C][/ROW]
[ROW][C]24[/C][C]-0.069165[/C][C]-0.7154[/C][C]0.237946[/C][/ROW]
[ROW][C]25[/C][C]-0.005237[/C][C]-0.0542[/C][C]0.478452[/C][/ROW]
[ROW][C]26[/C][C]-0.051611[/C][C]-0.5339[/C][C]0.297269[/C][/ROW]
[ROW][C]27[/C][C]0.011306[/C][C]0.1169[/C][C]0.453561[/C][/ROW]
[ROW][C]28[/C][C]-0.060308[/C][C]-0.6238[/C][C]0.267033[/C][/ROW]
[ROW][C]29[/C][C]-0.031867[/C][C]-0.3296[/C][C]0.371162[/C][/ROW]
[ROW][C]30[/C][C]-0.10028[/C][C]-1.0373[/C][C]0.150965[/C][/ROW]
[ROW][C]31[/C][C]-0.069375[/C][C]-0.7176[/C][C]0.237278[/C][/ROW]
[ROW][C]32[/C][C]-0.058755[/C][C]-0.6078[/C][C]0.272314[/C][/ROW]
[ROW][C]33[/C][C]-0.067179[/C][C]-0.6949[/C][C]0.24431[/C][/ROW]
[ROW][C]34[/C][C]-0.00657[/C][C]-0.068[/C][C]0.472973[/C][/ROW]
[ROW][C]35[/C][C]-0.083122[/C][C]-0.8598[/C][C]0.195905[/C][/ROW]
[ROW][C]36[/C][C]-0.039474[/C][C]-0.4083[/C][C]0.341925[/C][/ROW]
[ROW][C]37[/C][C]-0.113075[/C][C]-1.1697[/C][C]0.12237[/C][/ROW]
[ROW][C]38[/C][C]-0.146337[/C][C]-1.5137[/C][C]0.066523[/C][/ROW]
[ROW][C]39[/C][C]-0.103852[/C][C]-1.0743[/C][C]0.142563[/C][/ROW]
[ROW][C]40[/C][C]0.014863[/C][C]0.1537[/C][C]0.439052[/C][/ROW]
[ROW][C]41[/C][C]-0.022303[/C][C]-0.2307[/C][C]0.408993[/C][/ROW]
[ROW][C]42[/C][C]-0.052968[/C][C]-0.5479[/C][C]0.29245[/C][/ROW]
[ROW][C]43[/C][C]-0.054599[/C][C]-0.5648[/C][C]0.286705[/C][/ROW]
[ROW][C]44[/C][C]-0.111343[/C][C]-1.1517[/C][C]0.125997[/C][/ROW]
[ROW][C]45[/C][C]-0.071113[/C][C]-0.7356[/C][C]0.231793[/C][/ROW]
[ROW][C]46[/C][C]0.005659[/C][C]0.0585[/C][C]0.476715[/C][/ROW]
[ROW][C]47[/C][C]0.007916[/C][C]0.0819[/C][C]0.467447[/C][/ROW]
[ROW][C]48[/C][C]0.031057[/C][C]0.3213[/C][C]0.37432[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282757&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282757&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
10.3391433.50810.000331
20.1393031.4410.076258
30.0797540.8250.205609
40.1308181.35320.089423
50.2313522.39310.009224
60.1119511.1580.124716
70.0244030.25240.400597
80.0458240.4740.318229
90.0584450.60460.273375
100.1654821.71180.044919
110.1196091.23720.109351
120.0775570.80230.21209
130.0775040.80170.212249
140.0975311.00890.157656
150.0356560.36880.356494
160.0038350.03970.484215
170.1777771.83890.034348
180.0300370.31070.378315
19-0.081266-0.84060.201217
20-0.209896-2.17120.016064
21-0.128716-1.33140.092936
22-0.025417-0.26290.396561
230.0061680.06380.474622
24-0.069165-0.71540.237946
25-0.005237-0.05420.478452
26-0.051611-0.53390.297269
270.0113060.11690.453561
28-0.060308-0.62380.267033
29-0.031867-0.32960.371162
30-0.10028-1.03730.150965
31-0.069375-0.71760.237278
32-0.058755-0.60780.272314
33-0.067179-0.69490.24431
34-0.00657-0.0680.472973
35-0.083122-0.85980.195905
36-0.039474-0.40830.341925
37-0.113075-1.16970.12237
38-0.146337-1.51370.066523
39-0.103852-1.07430.142563
400.0148630.15370.439052
41-0.022303-0.23070.408993
42-0.052968-0.54790.29245
43-0.054599-0.56480.286705
44-0.111343-1.15170.125997
45-0.071113-0.73560.231793
460.0056590.05850.476715
470.0079160.08190.467447
480.0310570.32130.37432






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3391433.50810.000331
20.0274420.28390.388534
30.0277050.28660.387493
40.1048251.08430.14033
50.174811.80820.036688
6-0.031567-0.32650.372328
7-0.038572-0.3990.345348
80.0377340.39030.348537
90.0071080.07350.470762
100.1158291.19810.116754
110.0263880.2730.392705
120.0240750.2490.401907
130.0314670.32550.37272
140.0415550.42980.334086
15-0.077838-0.80520.211255
16-0.035317-0.36530.357796
170.2137422.2110.014583
18-0.129537-1.33990.091552
19-0.137708-1.42450.078611
20-0.185103-1.91470.0291
21-0.016011-0.16560.434384
22-0.03374-0.3490.363885
230.0389310.40270.343986
24-0.031926-0.33020.370929
250.1196021.23720.109366
26-0.037078-0.38350.35104
27-0.035186-0.3640.358301
28-0.101227-1.04710.148706
290.0809770.83760.202052
30-0.064311-0.66520.253666
31-0.005792-0.05990.47617
320.018320.18950.425029
330.0323810.3350.369159
340.0303630.31410.377038
35-0.101298-1.04780.148539
360.055370.57270.284009
37-0.042326-0.43780.331197
38-0.074557-0.77120.221138
39-0.110874-1.14690.126993
400.0973251.00670.158166
41-0.007484-0.07740.46922
42-0.060046-0.62110.267922
430.0422380.43690.331528
44-0.117928-1.21990.112601
450.0653050.67550.250403
460.0115940.11990.452383
470.0842350.87130.192761
480.0249730.25830.398329

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.339143 & 3.5081 & 0.000331 \tabularnewline
2 & 0.027442 & 0.2839 & 0.388534 \tabularnewline
3 & 0.027705 & 0.2866 & 0.387493 \tabularnewline
4 & 0.104825 & 1.0843 & 0.14033 \tabularnewline
5 & 0.17481 & 1.8082 & 0.036688 \tabularnewline
6 & -0.031567 & -0.3265 & 0.372328 \tabularnewline
7 & -0.038572 & -0.399 & 0.345348 \tabularnewline
8 & 0.037734 & 0.3903 & 0.348537 \tabularnewline
9 & 0.007108 & 0.0735 & 0.470762 \tabularnewline
10 & 0.115829 & 1.1981 & 0.116754 \tabularnewline
11 & 0.026388 & 0.273 & 0.392705 \tabularnewline
12 & 0.024075 & 0.249 & 0.401907 \tabularnewline
13 & 0.031467 & 0.3255 & 0.37272 \tabularnewline
14 & 0.041555 & 0.4298 & 0.334086 \tabularnewline
15 & -0.077838 & -0.8052 & 0.211255 \tabularnewline
16 & -0.035317 & -0.3653 & 0.357796 \tabularnewline
17 & 0.213742 & 2.211 & 0.014583 \tabularnewline
18 & -0.129537 & -1.3399 & 0.091552 \tabularnewline
19 & -0.137708 & -1.4245 & 0.078611 \tabularnewline
20 & -0.185103 & -1.9147 & 0.0291 \tabularnewline
21 & -0.016011 & -0.1656 & 0.434384 \tabularnewline
22 & -0.03374 & -0.349 & 0.363885 \tabularnewline
23 & 0.038931 & 0.4027 & 0.343986 \tabularnewline
24 & -0.031926 & -0.3302 & 0.370929 \tabularnewline
25 & 0.119602 & 1.2372 & 0.109366 \tabularnewline
26 & -0.037078 & -0.3835 & 0.35104 \tabularnewline
27 & -0.035186 & -0.364 & 0.358301 \tabularnewline
28 & -0.101227 & -1.0471 & 0.148706 \tabularnewline
29 & 0.080977 & 0.8376 & 0.202052 \tabularnewline
30 & -0.064311 & -0.6652 & 0.253666 \tabularnewline
31 & -0.005792 & -0.0599 & 0.47617 \tabularnewline
32 & 0.01832 & 0.1895 & 0.425029 \tabularnewline
33 & 0.032381 & 0.335 & 0.369159 \tabularnewline
34 & 0.030363 & 0.3141 & 0.377038 \tabularnewline
35 & -0.101298 & -1.0478 & 0.148539 \tabularnewline
36 & 0.05537 & 0.5727 & 0.284009 \tabularnewline
37 & -0.042326 & -0.4378 & 0.331197 \tabularnewline
38 & -0.074557 & -0.7712 & 0.221138 \tabularnewline
39 & -0.110874 & -1.1469 & 0.126993 \tabularnewline
40 & 0.097325 & 1.0067 & 0.158166 \tabularnewline
41 & -0.007484 & -0.0774 & 0.46922 \tabularnewline
42 & -0.060046 & -0.6211 & 0.267922 \tabularnewline
43 & 0.042238 & 0.4369 & 0.331528 \tabularnewline
44 & -0.117928 & -1.2199 & 0.112601 \tabularnewline
45 & 0.065305 & 0.6755 & 0.250403 \tabularnewline
46 & 0.011594 & 0.1199 & 0.452383 \tabularnewline
47 & 0.084235 & 0.8713 & 0.192761 \tabularnewline
48 & 0.024973 & 0.2583 & 0.398329 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282757&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]0.339143[/C][C]3.5081[/C][C]0.000331[/C][/ROW]
[ROW][C]2[/C][C]0.027442[/C][C]0.2839[/C][C]0.388534[/C][/ROW]
[ROW][C]3[/C][C]0.027705[/C][C]0.2866[/C][C]0.387493[/C][/ROW]
[ROW][C]4[/C][C]0.104825[/C][C]1.0843[/C][C]0.14033[/C][/ROW]
[ROW][C]5[/C][C]0.17481[/C][C]1.8082[/C][C]0.036688[/C][/ROW]
[ROW][C]6[/C][C]-0.031567[/C][C]-0.3265[/C][C]0.372328[/C][/ROW]
[ROW][C]7[/C][C]-0.038572[/C][C]-0.399[/C][C]0.345348[/C][/ROW]
[ROW][C]8[/C][C]0.037734[/C][C]0.3903[/C][C]0.348537[/C][/ROW]
[ROW][C]9[/C][C]0.007108[/C][C]0.0735[/C][C]0.470762[/C][/ROW]
[ROW][C]10[/C][C]0.115829[/C][C]1.1981[/C][C]0.116754[/C][/ROW]
[ROW][C]11[/C][C]0.026388[/C][C]0.273[/C][C]0.392705[/C][/ROW]
[ROW][C]12[/C][C]0.024075[/C][C]0.249[/C][C]0.401907[/C][/ROW]
[ROW][C]13[/C][C]0.031467[/C][C]0.3255[/C][C]0.37272[/C][/ROW]
[ROW][C]14[/C][C]0.041555[/C][C]0.4298[/C][C]0.334086[/C][/ROW]
[ROW][C]15[/C][C]-0.077838[/C][C]-0.8052[/C][C]0.211255[/C][/ROW]
[ROW][C]16[/C][C]-0.035317[/C][C]-0.3653[/C][C]0.357796[/C][/ROW]
[ROW][C]17[/C][C]0.213742[/C][C]2.211[/C][C]0.014583[/C][/ROW]
[ROW][C]18[/C][C]-0.129537[/C][C]-1.3399[/C][C]0.091552[/C][/ROW]
[ROW][C]19[/C][C]-0.137708[/C][C]-1.4245[/C][C]0.078611[/C][/ROW]
[ROW][C]20[/C][C]-0.185103[/C][C]-1.9147[/C][C]0.0291[/C][/ROW]
[ROW][C]21[/C][C]-0.016011[/C][C]-0.1656[/C][C]0.434384[/C][/ROW]
[ROW][C]22[/C][C]-0.03374[/C][C]-0.349[/C][C]0.363885[/C][/ROW]
[ROW][C]23[/C][C]0.038931[/C][C]0.4027[/C][C]0.343986[/C][/ROW]
[ROW][C]24[/C][C]-0.031926[/C][C]-0.3302[/C][C]0.370929[/C][/ROW]
[ROW][C]25[/C][C]0.119602[/C][C]1.2372[/C][C]0.109366[/C][/ROW]
[ROW][C]26[/C][C]-0.037078[/C][C]-0.3835[/C][C]0.35104[/C][/ROW]
[ROW][C]27[/C][C]-0.035186[/C][C]-0.364[/C][C]0.358301[/C][/ROW]
[ROW][C]28[/C][C]-0.101227[/C][C]-1.0471[/C][C]0.148706[/C][/ROW]
[ROW][C]29[/C][C]0.080977[/C][C]0.8376[/C][C]0.202052[/C][/ROW]
[ROW][C]30[/C][C]-0.064311[/C][C]-0.6652[/C][C]0.253666[/C][/ROW]
[ROW][C]31[/C][C]-0.005792[/C][C]-0.0599[/C][C]0.47617[/C][/ROW]
[ROW][C]32[/C][C]0.01832[/C][C]0.1895[/C][C]0.425029[/C][/ROW]
[ROW][C]33[/C][C]0.032381[/C][C]0.335[/C][C]0.369159[/C][/ROW]
[ROW][C]34[/C][C]0.030363[/C][C]0.3141[/C][C]0.377038[/C][/ROW]
[ROW][C]35[/C][C]-0.101298[/C][C]-1.0478[/C][C]0.148539[/C][/ROW]
[ROW][C]36[/C][C]0.05537[/C][C]0.5727[/C][C]0.284009[/C][/ROW]
[ROW][C]37[/C][C]-0.042326[/C][C]-0.4378[/C][C]0.331197[/C][/ROW]
[ROW][C]38[/C][C]-0.074557[/C][C]-0.7712[/C][C]0.221138[/C][/ROW]
[ROW][C]39[/C][C]-0.110874[/C][C]-1.1469[/C][C]0.126993[/C][/ROW]
[ROW][C]40[/C][C]0.097325[/C][C]1.0067[/C][C]0.158166[/C][/ROW]
[ROW][C]41[/C][C]-0.007484[/C][C]-0.0774[/C][C]0.46922[/C][/ROW]
[ROW][C]42[/C][C]-0.060046[/C][C]-0.6211[/C][C]0.267922[/C][/ROW]
[ROW][C]43[/C][C]0.042238[/C][C]0.4369[/C][C]0.331528[/C][/ROW]
[ROW][C]44[/C][C]-0.117928[/C][C]-1.2199[/C][C]0.112601[/C][/ROW]
[ROW][C]45[/C][C]0.065305[/C][C]0.6755[/C][C]0.250403[/C][/ROW]
[ROW][C]46[/C][C]0.011594[/C][C]0.1199[/C][C]0.452383[/C][/ROW]
[ROW][C]47[/C][C]0.084235[/C][C]0.8713[/C][C]0.192761[/C][/ROW]
[ROW][C]48[/C][C]0.024973[/C][C]0.2583[/C][C]0.398329[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282757&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282757&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
10.3391433.50810.000331
20.0274420.28390.388534
30.0277050.28660.387493
40.1048251.08430.14033
50.174811.80820.036688
6-0.031567-0.32650.372328
7-0.038572-0.3990.345348
80.0377340.39030.348537
90.0071080.07350.470762
100.1158291.19810.116754
110.0263880.2730.392705
120.0240750.2490.401907
130.0314670.32550.37272
140.0415550.42980.334086
15-0.077838-0.80520.211255
16-0.035317-0.36530.357796
170.2137422.2110.014583
18-0.129537-1.33990.091552
19-0.137708-1.42450.078611
20-0.185103-1.91470.0291
21-0.016011-0.16560.434384
22-0.03374-0.3490.363885
230.0389310.40270.343986
24-0.031926-0.33020.370929
250.1196021.23720.109366
26-0.037078-0.38350.35104
27-0.035186-0.3640.358301
28-0.101227-1.04710.148706
290.0809770.83760.202052
30-0.064311-0.66520.253666
31-0.005792-0.05990.47617
320.018320.18950.425029
330.0323810.3350.369159
340.0303630.31410.377038
35-0.101298-1.04780.148539
360.055370.57270.284009
37-0.042326-0.43780.331197
38-0.074557-0.77120.221138
39-0.110874-1.14690.126993
400.0973251.00670.158166
41-0.007484-0.07740.46922
42-0.060046-0.62110.267922
430.0422380.43690.331528
44-0.117928-1.21990.112601
450.0653050.67550.250403
460.0115940.11990.452383
470.0842350.87130.192761
480.0249730.25830.398329


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')