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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 computationSat, 28 Dec 2013 08:18:20 -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/2013/Dec/28/t1388236817kaiprsj7bluwezf.htm/, Retrieved Tue, 23 Apr 2024 11:54:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232645, Retrieved Tue, 23 Apr 2024 11:54:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

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] [] [2013-11-18 08:20:21] [9fb2675916b8773bb0a74f31adc60d44]
- R PD    [(Partial) Autocorrelation Function] [] [2013-12-28 13:18:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.44
100.47
100.49
100.52
100.47
100.48
100.48
100.53
100.62
100.89
100.97
101.01
101.02
100.92
100.93
100.98
101.07
101.1
101.11
101.19
101.31
101.52
101.61
101.65
101.66
101.56
101.75
101.83
101.98
102.06
102.07
102.1
102.42
102.91
103.14
103.23
103.23
102.91
103.11
103.14
103.26
103.3
103.32
103.44
103.54
103.98
104.24
104.29
104.29
103.98
103.98
103.89
103.86
103.88
103.88
104.31
104.41
104.8
104.89
104.9
104.9
104.54
104.67
104.87
105.04
105.09
105.1
105.46
105.83
106.27
106.46
106.52
106.53
105.96
106
106.15
106.32
106.41
106.41
106.81
106.99
107.35
107.53
107.56

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 6 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232645&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232645&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232645&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 time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2975062.71040.004082
20.1177151.07240.143316
3-0.202081-1.8410.034594
4-0.344142-3.13530.001187
5-0.052836-0.48140.315765
6-0.278962-2.54150.006449
7-0.016052-0.14620.442045
8-0.272477-2.48240.007533
9-0.154367-1.40640.081676
100.1283261.16910.122853
110.1784061.62540.053939
120.6668476.07530
130.2288522.08490.020074
140.0606810.55280.290933
15-0.176435-1.60740.055882
16-0.330399-3.01010.001729
17-0.013151-0.11980.452461
18-0.26875-2.44840.008227
19-0.055296-0.50380.307877
20-0.231753-2.11140.018874
21-0.096752-0.88140.19031
220.1884381.71670.044878
230.175461.59850.056864
240.4906154.46971.2e-05
250.121561.10750.135647
26-0.023635-0.21530.415021
27-0.187634-1.70940.045554
28-0.318202-2.8990.002394
29-0.020499-0.18680.426153
30-0.111852-1.0190.155577
31-0.024552-0.22370.411778
32-0.172186-1.56870.060262
33-0.088243-0.80390.211867
340.1456891.32730.094025
350.1514251.37950.085716
360.3873573.5290.000342
370.1265941.15330.126044
38-0.025071-0.22840.409945
39-0.108105-0.98490.163771
40-0.209183-1.90570.030073
41-0.038522-0.35090.363258
42-0.061361-0.5590.288826
430.0092850.08460.466395
44-0.091792-0.83630.202703
45-0.061098-0.55660.289639
460.1130671.03010.15298
470.1173291.06890.144103
480.2133381.94360.027666

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.297506 & 2.7104 & 0.004082 \tabularnewline
2 & 0.117715 & 1.0724 & 0.143316 \tabularnewline
3 & -0.202081 & -1.841 & 0.034594 \tabularnewline
4 & -0.344142 & -3.1353 & 0.001187 \tabularnewline
5 & -0.052836 & -0.4814 & 0.315765 \tabularnewline
6 & -0.278962 & -2.5415 & 0.006449 \tabularnewline
7 & -0.016052 & -0.1462 & 0.442045 \tabularnewline
8 & -0.272477 & -2.4824 & 0.007533 \tabularnewline
9 & -0.154367 & -1.4064 & 0.081676 \tabularnewline
10 & 0.128326 & 1.1691 & 0.122853 \tabularnewline
11 & 0.178406 & 1.6254 & 0.053939 \tabularnewline
12 & 0.666847 & 6.0753 & 0 \tabularnewline
13 & 0.228852 & 2.0849 & 0.020074 \tabularnewline
14 & 0.060681 & 0.5528 & 0.290933 \tabularnewline
15 & -0.176435 & -1.6074 & 0.055882 \tabularnewline
16 & -0.330399 & -3.0101 & 0.001729 \tabularnewline
17 & -0.013151 & -0.1198 & 0.452461 \tabularnewline
18 & -0.26875 & -2.4484 & 0.008227 \tabularnewline
19 & -0.055296 & -0.5038 & 0.307877 \tabularnewline
20 & -0.231753 & -2.1114 & 0.018874 \tabularnewline
21 & -0.096752 & -0.8814 & 0.19031 \tabularnewline
22 & 0.188438 & 1.7167 & 0.044878 \tabularnewline
23 & 0.17546 & 1.5985 & 0.056864 \tabularnewline
24 & 0.490615 & 4.4697 & 1.2e-05 \tabularnewline
25 & 0.12156 & 1.1075 & 0.135647 \tabularnewline
26 & -0.023635 & -0.2153 & 0.415021 \tabularnewline
27 & -0.187634 & -1.7094 & 0.045554 \tabularnewline
28 & -0.318202 & -2.899 & 0.002394 \tabularnewline
29 & -0.020499 & -0.1868 & 0.426153 \tabularnewline
30 & -0.111852 & -1.019 & 0.155577 \tabularnewline
31 & -0.024552 & -0.2237 & 0.411778 \tabularnewline
32 & -0.172186 & -1.5687 & 0.060262 \tabularnewline
33 & -0.088243 & -0.8039 & 0.211867 \tabularnewline
34 & 0.145689 & 1.3273 & 0.094025 \tabularnewline
35 & 0.151425 & 1.3795 & 0.085716 \tabularnewline
36 & 0.387357 & 3.529 & 0.000342 \tabularnewline
37 & 0.126594 & 1.1533 & 0.126044 \tabularnewline
38 & -0.025071 & -0.2284 & 0.409945 \tabularnewline
39 & -0.108105 & -0.9849 & 0.163771 \tabularnewline
40 & -0.209183 & -1.9057 & 0.030073 \tabularnewline
41 & -0.038522 & -0.3509 & 0.363258 \tabularnewline
42 & -0.061361 & -0.559 & 0.288826 \tabularnewline
43 & 0.009285 & 0.0846 & 0.466395 \tabularnewline
44 & -0.091792 & -0.8363 & 0.202703 \tabularnewline
45 & -0.061098 & -0.5566 & 0.289639 \tabularnewline
46 & 0.113067 & 1.0301 & 0.15298 \tabularnewline
47 & 0.117329 & 1.0689 & 0.144103 \tabularnewline
48 & 0.213338 & 1.9436 & 0.027666 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232645&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]0.297506[/C][C]2.7104[/C][C]0.004082[/C][/ROW]
[ROW][C]2[/C][C]0.117715[/C][C]1.0724[/C][C]0.143316[/C][/ROW]
[ROW][C]3[/C][C]-0.202081[/C][C]-1.841[/C][C]0.034594[/C][/ROW]
[ROW][C]4[/C][C]-0.344142[/C][C]-3.1353[/C][C]0.001187[/C][/ROW]
[ROW][C]5[/C][C]-0.052836[/C][C]-0.4814[/C][C]0.315765[/C][/ROW]
[ROW][C]6[/C][C]-0.278962[/C][C]-2.5415[/C][C]0.006449[/C][/ROW]
[ROW][C]7[/C][C]-0.016052[/C][C]-0.1462[/C][C]0.442045[/C][/ROW]
[ROW][C]8[/C][C]-0.272477[/C][C]-2.4824[/C][C]0.007533[/C][/ROW]
[ROW][C]9[/C][C]-0.154367[/C][C]-1.4064[/C][C]0.081676[/C][/ROW]
[ROW][C]10[/C][C]0.128326[/C][C]1.1691[/C][C]0.122853[/C][/ROW]
[ROW][C]11[/C][C]0.178406[/C][C]1.6254[/C][C]0.053939[/C][/ROW]
[ROW][C]12[/C][C]0.666847[/C][C]6.0753[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.228852[/C][C]2.0849[/C][C]0.020074[/C][/ROW]
[ROW][C]14[/C][C]0.060681[/C][C]0.5528[/C][C]0.290933[/C][/ROW]
[ROW][C]15[/C][C]-0.176435[/C][C]-1.6074[/C][C]0.055882[/C][/ROW]
[ROW][C]16[/C][C]-0.330399[/C][C]-3.0101[/C][C]0.001729[/C][/ROW]
[ROW][C]17[/C][C]-0.013151[/C][C]-0.1198[/C][C]0.452461[/C][/ROW]
[ROW][C]18[/C][C]-0.26875[/C][C]-2.4484[/C][C]0.008227[/C][/ROW]
[ROW][C]19[/C][C]-0.055296[/C][C]-0.5038[/C][C]0.307877[/C][/ROW]
[ROW][C]20[/C][C]-0.231753[/C][C]-2.1114[/C][C]0.018874[/C][/ROW]
[ROW][C]21[/C][C]-0.096752[/C][C]-0.8814[/C][C]0.19031[/C][/ROW]
[ROW][C]22[/C][C]0.188438[/C][C]1.7167[/C][C]0.044878[/C][/ROW]
[ROW][C]23[/C][C]0.17546[/C][C]1.5985[/C][C]0.056864[/C][/ROW]
[ROW][C]24[/C][C]0.490615[/C][C]4.4697[/C][C]1.2e-05[/C][/ROW]
[ROW][C]25[/C][C]0.12156[/C][C]1.1075[/C][C]0.135647[/C][/ROW]
[ROW][C]26[/C][C]-0.023635[/C][C]-0.2153[/C][C]0.415021[/C][/ROW]
[ROW][C]27[/C][C]-0.187634[/C][C]-1.7094[/C][C]0.045554[/C][/ROW]
[ROW][C]28[/C][C]-0.318202[/C][C]-2.899[/C][C]0.002394[/C][/ROW]
[ROW][C]29[/C][C]-0.020499[/C][C]-0.1868[/C][C]0.426153[/C][/ROW]
[ROW][C]30[/C][C]-0.111852[/C][C]-1.019[/C][C]0.155577[/C][/ROW]
[ROW][C]31[/C][C]-0.024552[/C][C]-0.2237[/C][C]0.411778[/C][/ROW]
[ROW][C]32[/C][C]-0.172186[/C][C]-1.5687[/C][C]0.060262[/C][/ROW]
[ROW][C]33[/C][C]-0.088243[/C][C]-0.8039[/C][C]0.211867[/C][/ROW]
[ROW][C]34[/C][C]0.145689[/C][C]1.3273[/C][C]0.094025[/C][/ROW]
[ROW][C]35[/C][C]0.151425[/C][C]1.3795[/C][C]0.085716[/C][/ROW]
[ROW][C]36[/C][C]0.387357[/C][C]3.529[/C][C]0.000342[/C][/ROW]
[ROW][C]37[/C][C]0.126594[/C][C]1.1533[/C][C]0.126044[/C][/ROW]
[ROW][C]38[/C][C]-0.025071[/C][C]-0.2284[/C][C]0.409945[/C][/ROW]
[ROW][C]39[/C][C]-0.108105[/C][C]-0.9849[/C][C]0.163771[/C][/ROW]
[ROW][C]40[/C][C]-0.209183[/C][C]-1.9057[/C][C]0.030073[/C][/ROW]
[ROW][C]41[/C][C]-0.038522[/C][C]-0.3509[/C][C]0.363258[/C][/ROW]
[ROW][C]42[/C][C]-0.061361[/C][C]-0.559[/C][C]0.288826[/C][/ROW]
[ROW][C]43[/C][C]0.009285[/C][C]0.0846[/C][C]0.466395[/C][/ROW]
[ROW][C]44[/C][C]-0.091792[/C][C]-0.8363[/C][C]0.202703[/C][/ROW]
[ROW][C]45[/C][C]-0.061098[/C][C]-0.5566[/C][C]0.289639[/C][/ROW]
[ROW][C]46[/C][C]0.113067[/C][C]1.0301[/C][C]0.15298[/C][/ROW]
[ROW][C]47[/C][C]0.117329[/C][C]1.0689[/C][C]0.144103[/C][/ROW]
[ROW][C]48[/C][C]0.213338[/C][C]1.9436[/C][C]0.027666[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232645&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232645&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
10.2975062.71040.004082
20.1177151.07240.143316
3-0.202081-1.8410.034594
4-0.344142-3.13530.001187
5-0.052836-0.48140.315765
6-0.278962-2.54150.006449
7-0.016052-0.14620.442045
8-0.272477-2.48240.007533
9-0.154367-1.40640.081676
100.1283261.16910.122853
110.1784061.62540.053939
120.6668476.07530
130.2288522.08490.020074
140.0606810.55280.290933
15-0.176435-1.60740.055882
16-0.330399-3.01010.001729
17-0.013151-0.11980.452461
18-0.26875-2.44840.008227
19-0.055296-0.50380.307877
20-0.231753-2.11140.018874
21-0.096752-0.88140.19031
220.1884381.71670.044878
230.175461.59850.056864
240.4906154.46971.2e-05
250.121561.10750.135647
26-0.023635-0.21530.415021
27-0.187634-1.70940.045554
28-0.318202-2.8990.002394
29-0.020499-0.18680.426153
30-0.111852-1.0190.155577
31-0.024552-0.22370.411778
32-0.172186-1.56870.060262
33-0.088243-0.80390.211867
340.1456891.32730.094025
350.1514251.37950.085716
360.3873573.5290.000342
370.1265941.15330.126044
38-0.025071-0.22840.409945
39-0.108105-0.98490.163771
40-0.209183-1.90570.030073
41-0.038522-0.35090.363258
42-0.061361-0.5590.288826
430.0092850.08460.466395
44-0.091792-0.83630.202703
45-0.061098-0.55660.289639
460.1130671.03010.15298
470.1173291.06890.144103
480.2133381.94360.027666






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2975062.71040.004082
20.0320420.29190.385541
3-0.269629-2.45640.008058
4-0.256879-2.34030.010835
50.1933181.76120.040943
6-0.356428-3.24720.000841
70.0072340.06590.473807
8-0.371886-3.3880.000539
9-0.070277-0.64030.261884
100.0874110.79640.21405
110.1027820.93640.175896
120.4561614.15583.9e-05
13-0.073959-0.67380.251156
14-0.104528-0.95230.171857
150.0406110.370.356167
16-0.018013-0.16410.435024
170.0890740.81150.209699
18-0.16218-1.47750.071659
19-0.080255-0.73120.23337
20-0.048252-0.43960.330685
210.1095430.9980.160594
220.0023820.02170.491368
230.0414950.3780.353184
24-0.072628-0.66170.255006
25-0.043879-0.39980.34518
26-0.070694-0.64410.260659
27-0.028921-0.26350.396416
28-0.075457-0.68740.246858
29-0.034256-0.31210.37788
300.1980611.80440.037396
31-0.100316-0.91390.181702
32-0.070421-0.64160.26146
330.0243420.22180.412519
34-0.116918-1.06520.144943
350.0404330.36840.35677
360.0305190.2780.390837
370.0198510.18090.428463
38-0.001282-0.01170.495355
390.1440831.31270.096459
400.0623180.56770.285871
41-0.042288-0.38530.350515
420.0322210.29350.384918
430.042590.3880.3495
440.0256280.23350.40798
450.0241460.220.413212
46-0.002212-0.02020.491984
47-0.052637-0.47950.316406
48-0.039541-0.36020.359794

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.297506 & 2.7104 & 0.004082 \tabularnewline
2 & 0.032042 & 0.2919 & 0.385541 \tabularnewline
3 & -0.269629 & -2.4564 & 0.008058 \tabularnewline
4 & -0.256879 & -2.3403 & 0.010835 \tabularnewline
5 & 0.193318 & 1.7612 & 0.040943 \tabularnewline
6 & -0.356428 & -3.2472 & 0.000841 \tabularnewline
7 & 0.007234 & 0.0659 & 0.473807 \tabularnewline
8 & -0.371886 & -3.388 & 0.000539 \tabularnewline
9 & -0.070277 & -0.6403 & 0.261884 \tabularnewline
10 & 0.087411 & 0.7964 & 0.21405 \tabularnewline
11 & 0.102782 & 0.9364 & 0.175896 \tabularnewline
12 & 0.456161 & 4.1558 & 3.9e-05 \tabularnewline
13 & -0.073959 & -0.6738 & 0.251156 \tabularnewline
14 & -0.104528 & -0.9523 & 0.171857 \tabularnewline
15 & 0.040611 & 0.37 & 0.356167 \tabularnewline
16 & -0.018013 & -0.1641 & 0.435024 \tabularnewline
17 & 0.089074 & 0.8115 & 0.209699 \tabularnewline
18 & -0.16218 & -1.4775 & 0.071659 \tabularnewline
19 & -0.080255 & -0.7312 & 0.23337 \tabularnewline
20 & -0.048252 & -0.4396 & 0.330685 \tabularnewline
21 & 0.109543 & 0.998 & 0.160594 \tabularnewline
22 & 0.002382 & 0.0217 & 0.491368 \tabularnewline
23 & 0.041495 & 0.378 & 0.353184 \tabularnewline
24 & -0.072628 & -0.6617 & 0.255006 \tabularnewline
25 & -0.043879 & -0.3998 & 0.34518 \tabularnewline
26 & -0.070694 & -0.6441 & 0.260659 \tabularnewline
27 & -0.028921 & -0.2635 & 0.396416 \tabularnewline
28 & -0.075457 & -0.6874 & 0.246858 \tabularnewline
29 & -0.034256 & -0.3121 & 0.37788 \tabularnewline
30 & 0.198061 & 1.8044 & 0.037396 \tabularnewline
31 & -0.100316 & -0.9139 & 0.181702 \tabularnewline
32 & -0.070421 & -0.6416 & 0.26146 \tabularnewline
33 & 0.024342 & 0.2218 & 0.412519 \tabularnewline
34 & -0.116918 & -1.0652 & 0.144943 \tabularnewline
35 & 0.040433 & 0.3684 & 0.35677 \tabularnewline
36 & 0.030519 & 0.278 & 0.390837 \tabularnewline
37 & 0.019851 & 0.1809 & 0.428463 \tabularnewline
38 & -0.001282 & -0.0117 & 0.495355 \tabularnewline
39 & 0.144083 & 1.3127 & 0.096459 \tabularnewline
40 & 0.062318 & 0.5677 & 0.285871 \tabularnewline
41 & -0.042288 & -0.3853 & 0.350515 \tabularnewline
42 & 0.032221 & 0.2935 & 0.384918 \tabularnewline
43 & 0.04259 & 0.388 & 0.3495 \tabularnewline
44 & 0.025628 & 0.2335 & 0.40798 \tabularnewline
45 & 0.024146 & 0.22 & 0.413212 \tabularnewline
46 & -0.002212 & -0.0202 & 0.491984 \tabularnewline
47 & -0.052637 & -0.4795 & 0.316406 \tabularnewline
48 & -0.039541 & -0.3602 & 0.359794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232645&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]0.297506[/C][C]2.7104[/C][C]0.004082[/C][/ROW]
[ROW][C]2[/C][C]0.032042[/C][C]0.2919[/C][C]0.385541[/C][/ROW]
[ROW][C]3[/C][C]-0.269629[/C][C]-2.4564[/C][C]0.008058[/C][/ROW]
[ROW][C]4[/C][C]-0.256879[/C][C]-2.3403[/C][C]0.010835[/C][/ROW]
[ROW][C]5[/C][C]0.193318[/C][C]1.7612[/C][C]0.040943[/C][/ROW]
[ROW][C]6[/C][C]-0.356428[/C][C]-3.2472[/C][C]0.000841[/C][/ROW]
[ROW][C]7[/C][C]0.007234[/C][C]0.0659[/C][C]0.473807[/C][/ROW]
[ROW][C]8[/C][C]-0.371886[/C][C]-3.388[/C][C]0.000539[/C][/ROW]
[ROW][C]9[/C][C]-0.070277[/C][C]-0.6403[/C][C]0.261884[/C][/ROW]
[ROW][C]10[/C][C]0.087411[/C][C]0.7964[/C][C]0.21405[/C][/ROW]
[ROW][C]11[/C][C]0.102782[/C][C]0.9364[/C][C]0.175896[/C][/ROW]
[ROW][C]12[/C][C]0.456161[/C][C]4.1558[/C][C]3.9e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.073959[/C][C]-0.6738[/C][C]0.251156[/C][/ROW]
[ROW][C]14[/C][C]-0.104528[/C][C]-0.9523[/C][C]0.171857[/C][/ROW]
[ROW][C]15[/C][C]0.040611[/C][C]0.37[/C][C]0.356167[/C][/ROW]
[ROW][C]16[/C][C]-0.018013[/C][C]-0.1641[/C][C]0.435024[/C][/ROW]
[ROW][C]17[/C][C]0.089074[/C][C]0.8115[/C][C]0.209699[/C][/ROW]
[ROW][C]18[/C][C]-0.16218[/C][C]-1.4775[/C][C]0.071659[/C][/ROW]
[ROW][C]19[/C][C]-0.080255[/C][C]-0.7312[/C][C]0.23337[/C][/ROW]
[ROW][C]20[/C][C]-0.048252[/C][C]-0.4396[/C][C]0.330685[/C][/ROW]
[ROW][C]21[/C][C]0.109543[/C][C]0.998[/C][C]0.160594[/C][/ROW]
[ROW][C]22[/C][C]0.002382[/C][C]0.0217[/C][C]0.491368[/C][/ROW]
[ROW][C]23[/C][C]0.041495[/C][C]0.378[/C][C]0.353184[/C][/ROW]
[ROW][C]24[/C][C]-0.072628[/C][C]-0.6617[/C][C]0.255006[/C][/ROW]
[ROW][C]25[/C][C]-0.043879[/C][C]-0.3998[/C][C]0.34518[/C][/ROW]
[ROW][C]26[/C][C]-0.070694[/C][C]-0.6441[/C][C]0.260659[/C][/ROW]
[ROW][C]27[/C][C]-0.028921[/C][C]-0.2635[/C][C]0.396416[/C][/ROW]
[ROW][C]28[/C][C]-0.075457[/C][C]-0.6874[/C][C]0.246858[/C][/ROW]
[ROW][C]29[/C][C]-0.034256[/C][C]-0.3121[/C][C]0.37788[/C][/ROW]
[ROW][C]30[/C][C]0.198061[/C][C]1.8044[/C][C]0.037396[/C][/ROW]
[ROW][C]31[/C][C]-0.100316[/C][C]-0.9139[/C][C]0.181702[/C][/ROW]
[ROW][C]32[/C][C]-0.070421[/C][C]-0.6416[/C][C]0.26146[/C][/ROW]
[ROW][C]33[/C][C]0.024342[/C][C]0.2218[/C][C]0.412519[/C][/ROW]
[ROW][C]34[/C][C]-0.116918[/C][C]-1.0652[/C][C]0.144943[/C][/ROW]
[ROW][C]35[/C][C]0.040433[/C][C]0.3684[/C][C]0.35677[/C][/ROW]
[ROW][C]36[/C][C]0.030519[/C][C]0.278[/C][C]0.390837[/C][/ROW]
[ROW][C]37[/C][C]0.019851[/C][C]0.1809[/C][C]0.428463[/C][/ROW]
[ROW][C]38[/C][C]-0.001282[/C][C]-0.0117[/C][C]0.495355[/C][/ROW]
[ROW][C]39[/C][C]0.144083[/C][C]1.3127[/C][C]0.096459[/C][/ROW]
[ROW][C]40[/C][C]0.062318[/C][C]0.5677[/C][C]0.285871[/C][/ROW]
[ROW][C]41[/C][C]-0.042288[/C][C]-0.3853[/C][C]0.350515[/C][/ROW]
[ROW][C]42[/C][C]0.032221[/C][C]0.2935[/C][C]0.384918[/C][/ROW]
[ROW][C]43[/C][C]0.04259[/C][C]0.388[/C][C]0.3495[/C][/ROW]
[ROW][C]44[/C][C]0.025628[/C][C]0.2335[/C][C]0.40798[/C][/ROW]
[ROW][C]45[/C][C]0.024146[/C][C]0.22[/C][C]0.413212[/C][/ROW]
[ROW][C]46[/C][C]-0.002212[/C][C]-0.0202[/C][C]0.491984[/C][/ROW]
[ROW][C]47[/C][C]-0.052637[/C][C]-0.4795[/C][C]0.316406[/C][/ROW]
[ROW][C]48[/C][C]-0.039541[/C][C]-0.3602[/C][C]0.359794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232645&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232645&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
10.2975062.71040.004082
20.0320420.29190.385541
3-0.269629-2.45640.008058
4-0.256879-2.34030.010835
50.1933181.76120.040943
6-0.356428-3.24720.000841
70.0072340.06590.473807
8-0.371886-3.3880.000539
9-0.070277-0.64030.261884
100.0874110.79640.21405
110.1027820.93640.175896
120.4561614.15583.9e-05
13-0.073959-0.67380.251156
14-0.104528-0.95230.171857
150.0406110.370.356167
16-0.018013-0.16410.435024
170.0890740.81150.209699
18-0.16218-1.47750.071659
19-0.080255-0.73120.23337
20-0.048252-0.43960.330685
210.1095430.9980.160594
220.0023820.02170.491368
230.0414950.3780.353184
24-0.072628-0.66170.255006
25-0.043879-0.39980.34518
26-0.070694-0.64410.260659
27-0.028921-0.26350.396416
28-0.075457-0.68740.246858
29-0.034256-0.31210.37788
300.1980611.80440.037396
31-0.100316-0.91390.181702
32-0.070421-0.64160.26146
330.0243420.22180.412519
34-0.116918-1.06520.144943
350.0404330.36840.35677
360.0305190.2780.390837
370.0198510.18090.428463
38-0.001282-0.01170.495355
390.1440831.31270.096459
400.0623180.56770.285871
41-0.042288-0.38530.350515
420.0322210.29350.384918
430.042590.3880.3495
440.0256280.23350.40798
450.0241460.220.413212
46-0.002212-0.02020.491984
47-0.052637-0.47950.316406
48-0.039541-0.36020.359794


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')