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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 computationWed, 29 Dec 2010 12:55:17 +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/2010/Dec/29/t129362720488qolyitvomk06r.htm/, Retrieved Fri, 03 May 2024 12:41:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116775, Retrieved Fri, 03 May 2024 12:41:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact193
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-   PD                [(Partial) Autocorrelation Function] [] [2010-12-29 12:55:17] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataseries X:
00.521505
00.424828
00.425031
00.477194
00.828021
00.615619
00.366627
00.430888
00.281029
00.464625
00.269395
00.577905
00.566115
00.507758
00.750718
00.680840
00.766109
00.456147
00.497750
00.419327
00.609551
00.457337
00.570548
00.347900
00.387499
00.582429
00.239103
00.236745
00.262616
00.424093
00.365275
00.375076
00.409006
00.389168
00.240261
00.158950
00.439337
00.509468
00.374347
00.433983
00.413056
00.328893
00.518665
00.548650
00.546911
00.496349
00.530893
00.595776
00.557058
00.573133
00.500542
00.543127
00.559366
00.691169
00.440349
00.567666
00.596911
00.473554
00.592394
00.597556
00.633413
00.605712
00.704611
00.480526
00.702686
00.700902
00.603085
00.698092
00.597656
00.802342
00.601711
00.599313
00.602563
00.701663
00.499571
00.498092
00.497569
00.600183
00.333954
00.274437
00.320943
00.540667
00.405021
00.288596
00.327594
00.313261
00.257556
00.213839
00.186186
00.159271




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&T=0

As an alternative you can also use a 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' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.515895-4.5271.1e-05
20.1585761.39150.084041
3-0.161575-1.41780.080139
40.0950750.83430.203352
5-0.046465-0.40770.342302
6-0.074434-0.65320.257801
70.1987871.74440.042544
8-0.170806-1.49880.069005
90.1961781.72150.044592
10-0.27953-2.45290.008217
110.4417173.87610.000111
12-0.462379-4.05745.9e-05
130.1470461.29030.1004
14-0.030961-0.27170.393296
150.0465830.40880.341923
16-0.053914-0.47310.318741
170.0611480.53660.296555
180.0815450.71560.238214
19-0.17395-1.52640.065503
200.1311231.15060.12673
21-0.239711-2.10350.019346
220.2985782.620.005294
23-0.186112-1.63310.053263
240.1037320.91020.182767
25-0.022009-0.19310.423683
260.0103960.09120.463775
27-0.059022-0.51790.303
280.0552110.48450.314711
290.0244090.21420.415483
30-0.119472-1.04840.148876
310.2069331.81580.036645
32-0.242982-2.13220.018091
330.2510242.20270.015303
34-0.17809-1.56270.061108
350.0830040.72840.234303
36-0.097995-0.85990.196255

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.515895 & -4.527 & 1.1e-05 \tabularnewline
2 & 0.158576 & 1.3915 & 0.084041 \tabularnewline
3 & -0.161575 & -1.4178 & 0.080139 \tabularnewline
4 & 0.095075 & 0.8343 & 0.203352 \tabularnewline
5 & -0.046465 & -0.4077 & 0.342302 \tabularnewline
6 & -0.074434 & -0.6532 & 0.257801 \tabularnewline
7 & 0.198787 & 1.7444 & 0.042544 \tabularnewline
8 & -0.170806 & -1.4988 & 0.069005 \tabularnewline
9 & 0.196178 & 1.7215 & 0.044592 \tabularnewline
10 & -0.27953 & -2.4529 & 0.008217 \tabularnewline
11 & 0.441717 & 3.8761 & 0.000111 \tabularnewline
12 & -0.462379 & -4.0574 & 5.9e-05 \tabularnewline
13 & 0.147046 & 1.2903 & 0.1004 \tabularnewline
14 & -0.030961 & -0.2717 & 0.393296 \tabularnewline
15 & 0.046583 & 0.4088 & 0.341923 \tabularnewline
16 & -0.053914 & -0.4731 & 0.318741 \tabularnewline
17 & 0.061148 & 0.5366 & 0.296555 \tabularnewline
18 & 0.081545 & 0.7156 & 0.238214 \tabularnewline
19 & -0.17395 & -1.5264 & 0.065503 \tabularnewline
20 & 0.131123 & 1.1506 & 0.12673 \tabularnewline
21 & -0.239711 & -2.1035 & 0.019346 \tabularnewline
22 & 0.298578 & 2.62 & 0.005294 \tabularnewline
23 & -0.186112 & -1.6331 & 0.053263 \tabularnewline
24 & 0.103732 & 0.9102 & 0.182767 \tabularnewline
25 & -0.022009 & -0.1931 & 0.423683 \tabularnewline
26 & 0.010396 & 0.0912 & 0.463775 \tabularnewline
27 & -0.059022 & -0.5179 & 0.303 \tabularnewline
28 & 0.055211 & 0.4845 & 0.314711 \tabularnewline
29 & 0.024409 & 0.2142 & 0.415483 \tabularnewline
30 & -0.119472 & -1.0484 & 0.148876 \tabularnewline
31 & 0.206933 & 1.8158 & 0.036645 \tabularnewline
32 & -0.242982 & -2.1322 & 0.018091 \tabularnewline
33 & 0.251024 & 2.2027 & 0.015303 \tabularnewline
34 & -0.17809 & -1.5627 & 0.061108 \tabularnewline
35 & 0.083004 & 0.7284 & 0.234303 \tabularnewline
36 & -0.097995 & -0.8599 & 0.196255 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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]-0.515895[/C][C]-4.527[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.158576[/C][C]1.3915[/C][C]0.084041[/C][/ROW]
[ROW][C]3[/C][C]-0.161575[/C][C]-1.4178[/C][C]0.080139[/C][/ROW]
[ROW][C]4[/C][C]0.095075[/C][C]0.8343[/C][C]0.203352[/C][/ROW]
[ROW][C]5[/C][C]-0.046465[/C][C]-0.4077[/C][C]0.342302[/C][/ROW]
[ROW][C]6[/C][C]-0.074434[/C][C]-0.6532[/C][C]0.257801[/C][/ROW]
[ROW][C]7[/C][C]0.198787[/C][C]1.7444[/C][C]0.042544[/C][/ROW]
[ROW][C]8[/C][C]-0.170806[/C][C]-1.4988[/C][C]0.069005[/C][/ROW]
[ROW][C]9[/C][C]0.196178[/C][C]1.7215[/C][C]0.044592[/C][/ROW]
[ROW][C]10[/C][C]-0.27953[/C][C]-2.4529[/C][C]0.008217[/C][/ROW]
[ROW][C]11[/C][C]0.441717[/C][C]3.8761[/C][C]0.000111[/C][/ROW]
[ROW][C]12[/C][C]-0.462379[/C][C]-4.0574[/C][C]5.9e-05[/C][/ROW]
[ROW][C]13[/C][C]0.147046[/C][C]1.2903[/C][C]0.1004[/C][/ROW]
[ROW][C]14[/C][C]-0.030961[/C][C]-0.2717[/C][C]0.393296[/C][/ROW]
[ROW][C]15[/C][C]0.046583[/C][C]0.4088[/C][C]0.341923[/C][/ROW]
[ROW][C]16[/C][C]-0.053914[/C][C]-0.4731[/C][C]0.318741[/C][/ROW]
[ROW][C]17[/C][C]0.061148[/C][C]0.5366[/C][C]0.296555[/C][/ROW]
[ROW][C]18[/C][C]0.081545[/C][C]0.7156[/C][C]0.238214[/C][/ROW]
[ROW][C]19[/C][C]-0.17395[/C][C]-1.5264[/C][C]0.065503[/C][/ROW]
[ROW][C]20[/C][C]0.131123[/C][C]1.1506[/C][C]0.12673[/C][/ROW]
[ROW][C]21[/C][C]-0.239711[/C][C]-2.1035[/C][C]0.019346[/C][/ROW]
[ROW][C]22[/C][C]0.298578[/C][C]2.62[/C][C]0.005294[/C][/ROW]
[ROW][C]23[/C][C]-0.186112[/C][C]-1.6331[/C][C]0.053263[/C][/ROW]
[ROW][C]24[/C][C]0.103732[/C][C]0.9102[/C][C]0.182767[/C][/ROW]
[ROW][C]25[/C][C]-0.022009[/C][C]-0.1931[/C][C]0.423683[/C][/ROW]
[ROW][C]26[/C][C]0.010396[/C][C]0.0912[/C][C]0.463775[/C][/ROW]
[ROW][C]27[/C][C]-0.059022[/C][C]-0.5179[/C][C]0.303[/C][/ROW]
[ROW][C]28[/C][C]0.055211[/C][C]0.4845[/C][C]0.314711[/C][/ROW]
[ROW][C]29[/C][C]0.024409[/C][C]0.2142[/C][C]0.415483[/C][/ROW]
[ROW][C]30[/C][C]-0.119472[/C][C]-1.0484[/C][C]0.148876[/C][/ROW]
[ROW][C]31[/C][C]0.206933[/C][C]1.8158[/C][C]0.036645[/C][/ROW]
[ROW][C]32[/C][C]-0.242982[/C][C]-2.1322[/C][C]0.018091[/C][/ROW]
[ROW][C]33[/C][C]0.251024[/C][C]2.2027[/C][C]0.015303[/C][/ROW]
[ROW][C]34[/C][C]-0.17809[/C][C]-1.5627[/C][C]0.061108[/C][/ROW]
[ROW][C]35[/C][C]0.083004[/C][C]0.7284[/C][C]0.234303[/C][/ROW]
[ROW][C]36[/C][C]-0.097995[/C][C]-0.8599[/C][C]0.196255[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.515895-4.5271.1e-05
20.1585761.39150.084041
3-0.161575-1.41780.080139
40.0950750.83430.203352
5-0.046465-0.40770.342302
6-0.074434-0.65320.257801
70.1987871.74440.042544
8-0.170806-1.49880.069005
90.1961781.72150.044592
10-0.27953-2.45290.008217
110.4417173.87610.000111
12-0.462379-4.05745.9e-05
130.1470461.29030.1004
14-0.030961-0.27170.393296
150.0465830.40880.341923
16-0.053914-0.47310.318741
170.0611480.53660.296555
180.0815450.71560.238214
19-0.17395-1.52640.065503
200.1311231.15060.12673
21-0.239711-2.10350.019346
220.2985782.620.005294
23-0.186112-1.63310.053263
240.1037320.91020.182767
25-0.022009-0.19310.423683
260.0103960.09120.463775
27-0.059022-0.51790.303
280.0552110.48450.314711
290.0244090.21420.415483
30-0.119472-1.04840.148876
310.2069331.81580.036645
32-0.242982-2.13220.018091
330.2510242.20270.015303
34-0.17809-1.56270.061108
350.0830040.72840.234303
36-0.097995-0.85990.196255







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.515895-4.5271.1e-05
2-0.146586-1.28630.101099
3-0.199695-1.75230.04185
4-0.096127-0.84350.200777
5-0.059967-0.52620.300128
6-0.190562-1.67220.049275
70.0996650.87460.192266
8-0.02995-0.26280.396701
90.1306711.14660.127543
10-0.128667-1.1290.131191
110.3484823.05790.001532
12-0.133622-1.17250.122301
13-0.182912-1.6050.056289
14-0.063438-0.55670.289685
15-0.061901-0.54320.294288
16-0.169691-1.4890.070282
170.0837150.73460.232409
180.0113190.09930.460571
19-0.002494-0.02190.4913
200.0119670.1050.45832
21-0.129763-1.13870.129187
22-0.025197-0.22110.412799
230.1905911.67240.049249
24-0.015126-0.13270.447376
25-0.025014-0.21950.413422
260.0374670.32880.371612
27-0.066329-0.5820.281121
28-0.019763-0.17340.431387
290.0709320.62240.267749
30-0.034654-0.30410.38094
310.146561.28610.101138
32-0.051269-0.44990.32703
33-0.024484-0.21480.415228
34-0.009631-0.08450.466434
350.0573660.50340.308065
36-0.140756-1.23510.110268

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.515895 & -4.527 & 1.1e-05 \tabularnewline
2 & -0.146586 & -1.2863 & 0.101099 \tabularnewline
3 & -0.199695 & -1.7523 & 0.04185 \tabularnewline
4 & -0.096127 & -0.8435 & 0.200777 \tabularnewline
5 & -0.059967 & -0.5262 & 0.300128 \tabularnewline
6 & -0.190562 & -1.6722 & 0.049275 \tabularnewline
7 & 0.099665 & 0.8746 & 0.192266 \tabularnewline
8 & -0.02995 & -0.2628 & 0.396701 \tabularnewline
9 & 0.130671 & 1.1466 & 0.127543 \tabularnewline
10 & -0.128667 & -1.129 & 0.131191 \tabularnewline
11 & 0.348482 & 3.0579 & 0.001532 \tabularnewline
12 & -0.133622 & -1.1725 & 0.122301 \tabularnewline
13 & -0.182912 & -1.605 & 0.056289 \tabularnewline
14 & -0.063438 & -0.5567 & 0.289685 \tabularnewline
15 & -0.061901 & -0.5432 & 0.294288 \tabularnewline
16 & -0.169691 & -1.489 & 0.070282 \tabularnewline
17 & 0.083715 & 0.7346 & 0.232409 \tabularnewline
18 & 0.011319 & 0.0993 & 0.460571 \tabularnewline
19 & -0.002494 & -0.0219 & 0.4913 \tabularnewline
20 & 0.011967 & 0.105 & 0.45832 \tabularnewline
21 & -0.129763 & -1.1387 & 0.129187 \tabularnewline
22 & -0.025197 & -0.2211 & 0.412799 \tabularnewline
23 & 0.190591 & 1.6724 & 0.049249 \tabularnewline
24 & -0.015126 & -0.1327 & 0.447376 \tabularnewline
25 & -0.025014 & -0.2195 & 0.413422 \tabularnewline
26 & 0.037467 & 0.3288 & 0.371612 \tabularnewline
27 & -0.066329 & -0.582 & 0.281121 \tabularnewline
28 & -0.019763 & -0.1734 & 0.431387 \tabularnewline
29 & 0.070932 & 0.6224 & 0.267749 \tabularnewline
30 & -0.034654 & -0.3041 & 0.38094 \tabularnewline
31 & 0.14656 & 1.2861 & 0.101138 \tabularnewline
32 & -0.051269 & -0.4499 & 0.32703 \tabularnewline
33 & -0.024484 & -0.2148 & 0.415228 \tabularnewline
34 & -0.009631 & -0.0845 & 0.466434 \tabularnewline
35 & 0.057366 & 0.5034 & 0.308065 \tabularnewline
36 & -0.140756 & -1.2351 & 0.110268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116775&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]-0.515895[/C][C]-4.527[/C][C]1.1e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.146586[/C][C]-1.2863[/C][C]0.101099[/C][/ROW]
[ROW][C]3[/C][C]-0.199695[/C][C]-1.7523[/C][C]0.04185[/C][/ROW]
[ROW][C]4[/C][C]-0.096127[/C][C]-0.8435[/C][C]0.200777[/C][/ROW]
[ROW][C]5[/C][C]-0.059967[/C][C]-0.5262[/C][C]0.300128[/C][/ROW]
[ROW][C]6[/C][C]-0.190562[/C][C]-1.6722[/C][C]0.049275[/C][/ROW]
[ROW][C]7[/C][C]0.099665[/C][C]0.8746[/C][C]0.192266[/C][/ROW]
[ROW][C]8[/C][C]-0.02995[/C][C]-0.2628[/C][C]0.396701[/C][/ROW]
[ROW][C]9[/C][C]0.130671[/C][C]1.1466[/C][C]0.127543[/C][/ROW]
[ROW][C]10[/C][C]-0.128667[/C][C]-1.129[/C][C]0.131191[/C][/ROW]
[ROW][C]11[/C][C]0.348482[/C][C]3.0579[/C][C]0.001532[/C][/ROW]
[ROW][C]12[/C][C]-0.133622[/C][C]-1.1725[/C][C]0.122301[/C][/ROW]
[ROW][C]13[/C][C]-0.182912[/C][C]-1.605[/C][C]0.056289[/C][/ROW]
[ROW][C]14[/C][C]-0.063438[/C][C]-0.5567[/C][C]0.289685[/C][/ROW]
[ROW][C]15[/C][C]-0.061901[/C][C]-0.5432[/C][C]0.294288[/C][/ROW]
[ROW][C]16[/C][C]-0.169691[/C][C]-1.489[/C][C]0.070282[/C][/ROW]
[ROW][C]17[/C][C]0.083715[/C][C]0.7346[/C][C]0.232409[/C][/ROW]
[ROW][C]18[/C][C]0.011319[/C][C]0.0993[/C][C]0.460571[/C][/ROW]
[ROW][C]19[/C][C]-0.002494[/C][C]-0.0219[/C][C]0.4913[/C][/ROW]
[ROW][C]20[/C][C]0.011967[/C][C]0.105[/C][C]0.45832[/C][/ROW]
[ROW][C]21[/C][C]-0.129763[/C][C]-1.1387[/C][C]0.129187[/C][/ROW]
[ROW][C]22[/C][C]-0.025197[/C][C]-0.2211[/C][C]0.412799[/C][/ROW]
[ROW][C]23[/C][C]0.190591[/C][C]1.6724[/C][C]0.049249[/C][/ROW]
[ROW][C]24[/C][C]-0.015126[/C][C]-0.1327[/C][C]0.447376[/C][/ROW]
[ROW][C]25[/C][C]-0.025014[/C][C]-0.2195[/C][C]0.413422[/C][/ROW]
[ROW][C]26[/C][C]0.037467[/C][C]0.3288[/C][C]0.371612[/C][/ROW]
[ROW][C]27[/C][C]-0.066329[/C][C]-0.582[/C][C]0.281121[/C][/ROW]
[ROW][C]28[/C][C]-0.019763[/C][C]-0.1734[/C][C]0.431387[/C][/ROW]
[ROW][C]29[/C][C]0.070932[/C][C]0.6224[/C][C]0.267749[/C][/ROW]
[ROW][C]30[/C][C]-0.034654[/C][C]-0.3041[/C][C]0.38094[/C][/ROW]
[ROW][C]31[/C][C]0.14656[/C][C]1.2861[/C][C]0.101138[/C][/ROW]
[ROW][C]32[/C][C]-0.051269[/C][C]-0.4499[/C][C]0.32703[/C][/ROW]
[ROW][C]33[/C][C]-0.024484[/C][C]-0.2148[/C][C]0.415228[/C][/ROW]
[ROW][C]34[/C][C]-0.009631[/C][C]-0.0845[/C][C]0.466434[/C][/ROW]
[ROW][C]35[/C][C]0.057366[/C][C]0.5034[/C][C]0.308065[/C][/ROW]
[ROW][C]36[/C][C]-0.140756[/C][C]-1.2351[/C][C]0.110268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116775&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116775&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.515895-4.5271.1e-05
2-0.146586-1.28630.101099
3-0.199695-1.75230.04185
4-0.096127-0.84350.200777
5-0.059967-0.52620.300128
6-0.190562-1.67220.049275
70.0996650.87460.192266
8-0.02995-0.26280.396701
90.1306711.14660.127543
10-0.128667-1.1290.131191
110.3484823.05790.001532
12-0.133622-1.17250.122301
13-0.182912-1.6050.056289
14-0.063438-0.55670.289685
15-0.061901-0.54320.294288
16-0.169691-1.4890.070282
170.0837150.73460.232409
180.0113190.09930.460571
19-0.002494-0.02190.4913
200.0119670.1050.45832
21-0.129763-1.13870.129187
22-0.025197-0.22110.412799
230.1905911.67240.049249
24-0.015126-0.13270.447376
25-0.025014-0.21950.413422
260.0374670.32880.371612
27-0.066329-0.5820.281121
28-0.019763-0.17340.431387
290.0709320.62240.267749
30-0.034654-0.30410.38094
310.146561.28610.101138
32-0.051269-0.44990.32703
33-0.024484-0.21480.415228
34-0.009631-0.08450.466434
350.0573660.50340.308065
36-0.140756-1.23510.110268



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