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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 01 Dec 2011 08:48:23 -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/Dec/01/t1322747369jkoa0xzsd5wxwek.htm/, Retrieved Mon, 29 Apr 2024 11:32:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=149599, Retrieved Mon, 29 Apr 2024 11:32:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [WS 9 Autocorrelatie ] [2010-12-03 12:44:11] [8081b8996d5947580de3eb171e82db4f]
-   P       [(Partial) Autocorrelation Function] [Verbetering WS9] [2010-12-14 19:15:43] [3635fb7041b1998c5a1332cf9de22bce]
- R PD        [(Partial) Autocorrelation Function] [] [2011-12-01 13:26:13] [d6b4d011b409693eac2700c83288e3e7]
- R PD            [(Partial) Autocorrelation Function] [] [2011-12-01 13:48:23] [e232377fd09030116200e3da7df6eeaf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9 676
8 642
9 402
9 610
9 294
9 448
10 319
9 548
9 801
9 596
8 923
9 746
9 829
9 125
9 782
9 441
9 162
9 915
10 444
10 209
9 985
9 842
9 429
10 132
9 849
9 172
10 313
9 819
9 955
10 048
10 082
10 541
10 208
10 233
9 439
9 963
10 158
9 225
10 474
9 757
10 490
10 281
10 444
10 640
10 695
10 786
9 832
9 747
10 411
9 511
10 402
9 701
10 540
10 112
10 915
11 183
10 384
10 834
9 886
10 216
10 943
9 867
10 203
10 837
10 573
10 647
11 502
10 656
10 866
10 835
9 945
10 331

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149599&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149599&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149599&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'Gwilym Jenkins' @ jenkins.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.160339-1.2420.109538
2-0.078908-0.61120.271681
30.017230.13350.447137
4-0.097943-0.75870.225511
50.2261311.75160.042476
60.0142670.11050.456186
7-0.311718-2.41460.00941
8-0.092488-0.71640.238259
90.154081.19350.118687
10-0.13747-1.06480.145607
11-0.05245-0.40630.342994
12-0.14879-1.15250.12684
13-0.105796-0.81950.207875
140.1842091.42690.0794
150.0453130.3510.36341
16-0.145938-1.13040.131397
170.1230.95280.172269
180.0800340.61990.268823
190.1008980.78160.218776
200.0228510.1770.430051
210.0529650.41030.341536
22-0.01279-0.09910.460707
230.1590791.23220.111337
24-0.125158-0.96950.168101
25-0.179272-1.38860.085039
260.0296520.22970.40956
270.0745140.57720.282987
28-0.051741-0.40080.345
29-0.127443-0.98720.163762
30-0.133397-1.03330.152807
31-0.064912-0.50280.308471
320.2352081.82190.036727
33-0.053533-0.41470.339932
34-0.109978-0.85190.198832
350.1220730.94560.174078
36-0.053958-0.4180.338734

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.160339 & -1.242 & 0.109538 \tabularnewline
2 & -0.078908 & -0.6112 & 0.271681 \tabularnewline
3 & 0.01723 & 0.1335 & 0.447137 \tabularnewline
4 & -0.097943 & -0.7587 & 0.225511 \tabularnewline
5 & 0.226131 & 1.7516 & 0.042476 \tabularnewline
6 & 0.014267 & 0.1105 & 0.456186 \tabularnewline
7 & -0.311718 & -2.4146 & 0.00941 \tabularnewline
8 & -0.092488 & -0.7164 & 0.238259 \tabularnewline
9 & 0.15408 & 1.1935 & 0.118687 \tabularnewline
10 & -0.13747 & -1.0648 & 0.145607 \tabularnewline
11 & -0.05245 & -0.4063 & 0.342994 \tabularnewline
12 & -0.14879 & -1.1525 & 0.12684 \tabularnewline
13 & -0.105796 & -0.8195 & 0.207875 \tabularnewline
14 & 0.184209 & 1.4269 & 0.0794 \tabularnewline
15 & 0.045313 & 0.351 & 0.36341 \tabularnewline
16 & -0.145938 & -1.1304 & 0.131397 \tabularnewline
17 & 0.123 & 0.9528 & 0.172269 \tabularnewline
18 & 0.080034 & 0.6199 & 0.268823 \tabularnewline
19 & 0.100898 & 0.7816 & 0.218776 \tabularnewline
20 & 0.022851 & 0.177 & 0.430051 \tabularnewline
21 & 0.052965 & 0.4103 & 0.341536 \tabularnewline
22 & -0.01279 & -0.0991 & 0.460707 \tabularnewline
23 & 0.159079 & 1.2322 & 0.111337 \tabularnewline
24 & -0.125158 & -0.9695 & 0.168101 \tabularnewline
25 & -0.179272 & -1.3886 & 0.085039 \tabularnewline
26 & 0.029652 & 0.2297 & 0.40956 \tabularnewline
27 & 0.074514 & 0.5772 & 0.282987 \tabularnewline
28 & -0.051741 & -0.4008 & 0.345 \tabularnewline
29 & -0.127443 & -0.9872 & 0.163762 \tabularnewline
30 & -0.133397 & -1.0333 & 0.152807 \tabularnewline
31 & -0.064912 & -0.5028 & 0.308471 \tabularnewline
32 & 0.235208 & 1.8219 & 0.036727 \tabularnewline
33 & -0.053533 & -0.4147 & 0.339932 \tabularnewline
34 & -0.109978 & -0.8519 & 0.198832 \tabularnewline
35 & 0.122073 & 0.9456 & 0.174078 \tabularnewline
36 & -0.053958 & -0.418 & 0.338734 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149599&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]-0.160339[/C][C]-1.242[/C][C]0.109538[/C][/ROW]
[ROW][C]2[/C][C]-0.078908[/C][C]-0.6112[/C][C]0.271681[/C][/ROW]
[ROW][C]3[/C][C]0.01723[/C][C]0.1335[/C][C]0.447137[/C][/ROW]
[ROW][C]4[/C][C]-0.097943[/C][C]-0.7587[/C][C]0.225511[/C][/ROW]
[ROW][C]5[/C][C]0.226131[/C][C]1.7516[/C][C]0.042476[/C][/ROW]
[ROW][C]6[/C][C]0.014267[/C][C]0.1105[/C][C]0.456186[/C][/ROW]
[ROW][C]7[/C][C]-0.311718[/C][C]-2.4146[/C][C]0.00941[/C][/ROW]
[ROW][C]8[/C][C]-0.092488[/C][C]-0.7164[/C][C]0.238259[/C][/ROW]
[ROW][C]9[/C][C]0.15408[/C][C]1.1935[/C][C]0.118687[/C][/ROW]
[ROW][C]10[/C][C]-0.13747[/C][C]-1.0648[/C][C]0.145607[/C][/ROW]
[ROW][C]11[/C][C]-0.05245[/C][C]-0.4063[/C][C]0.342994[/C][/ROW]
[ROW][C]12[/C][C]-0.14879[/C][C]-1.1525[/C][C]0.12684[/C][/ROW]
[ROW][C]13[/C][C]-0.105796[/C][C]-0.8195[/C][C]0.207875[/C][/ROW]
[ROW][C]14[/C][C]0.184209[/C][C]1.4269[/C][C]0.0794[/C][/ROW]
[ROW][C]15[/C][C]0.045313[/C][C]0.351[/C][C]0.36341[/C][/ROW]
[ROW][C]16[/C][C]-0.145938[/C][C]-1.1304[/C][C]0.131397[/C][/ROW]
[ROW][C]17[/C][C]0.123[/C][C]0.9528[/C][C]0.172269[/C][/ROW]
[ROW][C]18[/C][C]0.080034[/C][C]0.6199[/C][C]0.268823[/C][/ROW]
[ROW][C]19[/C][C]0.100898[/C][C]0.7816[/C][C]0.218776[/C][/ROW]
[ROW][C]20[/C][C]0.022851[/C][C]0.177[/C][C]0.430051[/C][/ROW]
[ROW][C]21[/C][C]0.052965[/C][C]0.4103[/C][C]0.341536[/C][/ROW]
[ROW][C]22[/C][C]-0.01279[/C][C]-0.0991[/C][C]0.460707[/C][/ROW]
[ROW][C]23[/C][C]0.159079[/C][C]1.2322[/C][C]0.111337[/C][/ROW]
[ROW][C]24[/C][C]-0.125158[/C][C]-0.9695[/C][C]0.168101[/C][/ROW]
[ROW][C]25[/C][C]-0.179272[/C][C]-1.3886[/C][C]0.085039[/C][/ROW]
[ROW][C]26[/C][C]0.029652[/C][C]0.2297[/C][C]0.40956[/C][/ROW]
[ROW][C]27[/C][C]0.074514[/C][C]0.5772[/C][C]0.282987[/C][/ROW]
[ROW][C]28[/C][C]-0.051741[/C][C]-0.4008[/C][C]0.345[/C][/ROW]
[ROW][C]29[/C][C]-0.127443[/C][C]-0.9872[/C][C]0.163762[/C][/ROW]
[ROW][C]30[/C][C]-0.133397[/C][C]-1.0333[/C][C]0.152807[/C][/ROW]
[ROW][C]31[/C][C]-0.064912[/C][C]-0.5028[/C][C]0.308471[/C][/ROW]
[ROW][C]32[/C][C]0.235208[/C][C]1.8219[/C][C]0.036727[/C][/ROW]
[ROW][C]33[/C][C]-0.053533[/C][C]-0.4147[/C][C]0.339932[/C][/ROW]
[ROW][C]34[/C][C]-0.109978[/C][C]-0.8519[/C][C]0.198832[/C][/ROW]
[ROW][C]35[/C][C]0.122073[/C][C]0.9456[/C][C]0.174078[/C][/ROW]
[ROW][C]36[/C][C]-0.053958[/C][C]-0.418[/C][C]0.338734[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149599&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149599&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.160339-1.2420.109538
2-0.078908-0.61120.271681
30.017230.13350.447137
4-0.097943-0.75870.225511
50.2261311.75160.042476
60.0142670.11050.456186
7-0.311718-2.41460.00941
8-0.092488-0.71640.238259
90.154081.19350.118687
10-0.13747-1.06480.145607
11-0.05245-0.40630.342994
12-0.14879-1.15250.12684
13-0.105796-0.81950.207875
140.1842091.42690.0794
150.0453130.3510.36341
16-0.145938-1.13040.131397
170.1230.95280.172269
180.0800340.61990.268823
190.1008980.78160.218776
200.0228510.1770.430051
210.0529650.41030.341536
22-0.01279-0.09910.460707
230.1590791.23220.111337
24-0.125158-0.96950.168101
25-0.179272-1.38860.085039
260.0296520.22970.40956
270.0745140.57720.282987
28-0.051741-0.40080.345
29-0.127443-0.98720.163762
30-0.133397-1.03330.152807
31-0.064912-0.50280.308471
320.2352081.82190.036727
33-0.053533-0.41470.339932
34-0.109978-0.85190.198832
350.1220730.94560.174078
36-0.053958-0.4180.338734






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.160339-1.2420.109538
2-0.107377-0.83170.204426
3-0.014534-0.11260.455368
4-0.109948-0.85170.198896
50.1999591.54890.063335
60.071490.55380.290901
7-0.281799-2.18280.016487
8-0.222813-1.72590.044756
90.1193730.92470.179424
10-0.173298-1.34240.092269
11-0.202679-1.56990.060844
12-0.130346-1.00970.158357
13-0.094139-0.72920.23436
14-0.070146-0.54340.294451
15-0.011152-0.08640.465724
16-0.096524-0.74770.228789
170.0663610.5140.304559
180.0490050.37960.352796
190.042780.33140.370758
20-0.099225-0.76860.222574
210.182531.41390.081283
220.0420670.32580.372837
230.0549550.42570.335933
24-0.149348-1.15680.125961
25-0.106841-0.82760.205591
26-0.067852-0.52560.300558
270.1577151.22170.113308
28-0.066117-0.51210.305218
29-0.084204-0.65220.258367
30-0.045398-0.35170.363165
31-0.064129-0.49670.310592
320.0047580.03690.485363
330.044920.3480.364547
34-0.021364-0.16550.434559
350.1124880.87130.193523
36-0.199805-1.54770.063479

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.160339 & -1.242 & 0.109538 \tabularnewline
2 & -0.107377 & -0.8317 & 0.204426 \tabularnewline
3 & -0.014534 & -0.1126 & 0.455368 \tabularnewline
4 & -0.109948 & -0.8517 & 0.198896 \tabularnewline
5 & 0.199959 & 1.5489 & 0.063335 \tabularnewline
6 & 0.07149 & 0.5538 & 0.290901 \tabularnewline
7 & -0.281799 & -2.1828 & 0.016487 \tabularnewline
8 & -0.222813 & -1.7259 & 0.044756 \tabularnewline
9 & 0.119373 & 0.9247 & 0.179424 \tabularnewline
10 & -0.173298 & -1.3424 & 0.092269 \tabularnewline
11 & -0.202679 & -1.5699 & 0.060844 \tabularnewline
12 & -0.130346 & -1.0097 & 0.158357 \tabularnewline
13 & -0.094139 & -0.7292 & 0.23436 \tabularnewline
14 & -0.070146 & -0.5434 & 0.294451 \tabularnewline
15 & -0.011152 & -0.0864 & 0.465724 \tabularnewline
16 & -0.096524 & -0.7477 & 0.228789 \tabularnewline
17 & 0.066361 & 0.514 & 0.304559 \tabularnewline
18 & 0.049005 & 0.3796 & 0.352796 \tabularnewline
19 & 0.04278 & 0.3314 & 0.370758 \tabularnewline
20 & -0.099225 & -0.7686 & 0.222574 \tabularnewline
21 & 0.18253 & 1.4139 & 0.081283 \tabularnewline
22 & 0.042067 & 0.3258 & 0.372837 \tabularnewline
23 & 0.054955 & 0.4257 & 0.335933 \tabularnewline
24 & -0.149348 & -1.1568 & 0.125961 \tabularnewline
25 & -0.106841 & -0.8276 & 0.205591 \tabularnewline
26 & -0.067852 & -0.5256 & 0.300558 \tabularnewline
27 & 0.157715 & 1.2217 & 0.113308 \tabularnewline
28 & -0.066117 & -0.5121 & 0.305218 \tabularnewline
29 & -0.084204 & -0.6522 & 0.258367 \tabularnewline
30 & -0.045398 & -0.3517 & 0.363165 \tabularnewline
31 & -0.064129 & -0.4967 & 0.310592 \tabularnewline
32 & 0.004758 & 0.0369 & 0.485363 \tabularnewline
33 & 0.04492 & 0.348 & 0.364547 \tabularnewline
34 & -0.021364 & -0.1655 & 0.434559 \tabularnewline
35 & 0.112488 & 0.8713 & 0.193523 \tabularnewline
36 & -0.199805 & -1.5477 & 0.063479 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149599&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]-0.160339[/C][C]-1.242[/C][C]0.109538[/C][/ROW]
[ROW][C]2[/C][C]-0.107377[/C][C]-0.8317[/C][C]0.204426[/C][/ROW]
[ROW][C]3[/C][C]-0.014534[/C][C]-0.1126[/C][C]0.455368[/C][/ROW]
[ROW][C]4[/C][C]-0.109948[/C][C]-0.8517[/C][C]0.198896[/C][/ROW]
[ROW][C]5[/C][C]0.199959[/C][C]1.5489[/C][C]0.063335[/C][/ROW]
[ROW][C]6[/C][C]0.07149[/C][C]0.5538[/C][C]0.290901[/C][/ROW]
[ROW][C]7[/C][C]-0.281799[/C][C]-2.1828[/C][C]0.016487[/C][/ROW]
[ROW][C]8[/C][C]-0.222813[/C][C]-1.7259[/C][C]0.044756[/C][/ROW]
[ROW][C]9[/C][C]0.119373[/C][C]0.9247[/C][C]0.179424[/C][/ROW]
[ROW][C]10[/C][C]-0.173298[/C][C]-1.3424[/C][C]0.092269[/C][/ROW]
[ROW][C]11[/C][C]-0.202679[/C][C]-1.5699[/C][C]0.060844[/C][/ROW]
[ROW][C]12[/C][C]-0.130346[/C][C]-1.0097[/C][C]0.158357[/C][/ROW]
[ROW][C]13[/C][C]-0.094139[/C][C]-0.7292[/C][C]0.23436[/C][/ROW]
[ROW][C]14[/C][C]-0.070146[/C][C]-0.5434[/C][C]0.294451[/C][/ROW]
[ROW][C]15[/C][C]-0.011152[/C][C]-0.0864[/C][C]0.465724[/C][/ROW]
[ROW][C]16[/C][C]-0.096524[/C][C]-0.7477[/C][C]0.228789[/C][/ROW]
[ROW][C]17[/C][C]0.066361[/C][C]0.514[/C][C]0.304559[/C][/ROW]
[ROW][C]18[/C][C]0.049005[/C][C]0.3796[/C][C]0.352796[/C][/ROW]
[ROW][C]19[/C][C]0.04278[/C][C]0.3314[/C][C]0.370758[/C][/ROW]
[ROW][C]20[/C][C]-0.099225[/C][C]-0.7686[/C][C]0.222574[/C][/ROW]
[ROW][C]21[/C][C]0.18253[/C][C]1.4139[/C][C]0.081283[/C][/ROW]
[ROW][C]22[/C][C]0.042067[/C][C]0.3258[/C][C]0.372837[/C][/ROW]
[ROW][C]23[/C][C]0.054955[/C][C]0.4257[/C][C]0.335933[/C][/ROW]
[ROW][C]24[/C][C]-0.149348[/C][C]-1.1568[/C][C]0.125961[/C][/ROW]
[ROW][C]25[/C][C]-0.106841[/C][C]-0.8276[/C][C]0.205591[/C][/ROW]
[ROW][C]26[/C][C]-0.067852[/C][C]-0.5256[/C][C]0.300558[/C][/ROW]
[ROW][C]27[/C][C]0.157715[/C][C]1.2217[/C][C]0.113308[/C][/ROW]
[ROW][C]28[/C][C]-0.066117[/C][C]-0.5121[/C][C]0.305218[/C][/ROW]
[ROW][C]29[/C][C]-0.084204[/C][C]-0.6522[/C][C]0.258367[/C][/ROW]
[ROW][C]30[/C][C]-0.045398[/C][C]-0.3517[/C][C]0.363165[/C][/ROW]
[ROW][C]31[/C][C]-0.064129[/C][C]-0.4967[/C][C]0.310592[/C][/ROW]
[ROW][C]32[/C][C]0.004758[/C][C]0.0369[/C][C]0.485363[/C][/ROW]
[ROW][C]33[/C][C]0.04492[/C][C]0.348[/C][C]0.364547[/C][/ROW]
[ROW][C]34[/C][C]-0.021364[/C][C]-0.1655[/C][C]0.434559[/C][/ROW]
[ROW][C]35[/C][C]0.112488[/C][C]0.8713[/C][C]0.193523[/C][/ROW]
[ROW][C]36[/C][C]-0.199805[/C][C]-1.5477[/C][C]0.063479[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149599&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149599&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.160339-1.2420.109538
2-0.107377-0.83170.204426
3-0.014534-0.11260.455368
4-0.109948-0.85170.198896
50.1999591.54890.063335
60.071490.55380.290901
7-0.281799-2.18280.016487
8-0.222813-1.72590.044756
90.1193730.92470.179424
10-0.173298-1.34240.092269
11-0.202679-1.56990.060844
12-0.130346-1.00970.158357
13-0.094139-0.72920.23436
14-0.070146-0.54340.294451
15-0.011152-0.08640.465724
16-0.096524-0.74770.228789
170.0663610.5140.304559
180.0490050.37960.352796
190.042780.33140.370758
20-0.099225-0.76860.222574
210.182531.41390.081283
220.0420670.32580.372837
230.0549550.42570.335933
24-0.149348-1.15680.125961
25-0.106841-0.82760.205591
26-0.067852-0.52560.300558
270.1577151.22170.113308
28-0.066117-0.51210.305218
29-0.084204-0.65220.258367
30-0.045398-0.35170.363165
31-0.064129-0.49670.310592
320.0047580.03690.485363
330.044920.3480.364547
34-0.021364-0.16550.434559
350.1124880.87130.193523
36-0.199805-1.54770.063479


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')