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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 computationSun, 29 Nov 2009 05:13:58 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/29/t12594968945sdselzbhuj9ked.htm/, Retrieved Fri, 29 Mar 2024 08:00:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61564, Retrieved Fri, 29 Mar 2024 08:00:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-25 16:49:12] [cf890101a20378422561610e0d41fd9c]
-   PD            [(Partial) Autocorrelation Function] [WS8 d=1] [2009-11-29 12:13:58] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Dataseries X:
6.3
6.1
6.1
6.3
6.3
6
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8
8.1
8.2
8.3
8.2
8
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61564&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]1 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=61564&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61564&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3529443.45810.000406
2-0.199805-1.95770.026585
3-0.47784-4.68195e-06
4-0.381284-3.73580.000159
50.0372780.36530.357864
60.3369023.30090.000677
70.1599221.56690.060213
8-0.120491-1.18060.120347
9-0.189022-1.8520.033547
10-0.132033-1.29370.099444
110.0969020.94940.17239
120.4479654.38911.5e-05
130.0982470.96260.169078
14-0.070675-0.69250.245156
15-0.151486-1.48430.070509
16-0.147338-1.44360.076051
17-0.00185-0.01810.492787
180.1306391.280.101815
19-0.011346-0.11120.455857
20-0.102021-0.99960.160009
21-0.072964-0.71490.238203
22-0.03644-0.3570.360922
230.0600040.58790.278983
240.2849022.79150.003166
250.0114210.11190.455565
26-0.071159-0.69720.243676
27-0.101526-0.99470.16118
28-0.081706-0.80060.212683
29-0.004731-0.04640.481562
300.0544340.53330.297516
31-0.015112-0.14810.4413
32-0.081892-0.80240.212159
33-0.019335-0.18940.425073
340.0176870.17330.431393
350.0540810.52990.298706
360.1933931.89490.03056

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.352944 & 3.4581 & 0.000406 \tabularnewline
2 & -0.199805 & -1.9577 & 0.026585 \tabularnewline
3 & -0.47784 & -4.6819 & 5e-06 \tabularnewline
4 & -0.381284 & -3.7358 & 0.000159 \tabularnewline
5 & 0.037278 & 0.3653 & 0.357864 \tabularnewline
6 & 0.336902 & 3.3009 & 0.000677 \tabularnewline
7 & 0.159922 & 1.5669 & 0.060213 \tabularnewline
8 & -0.120491 & -1.1806 & 0.120347 \tabularnewline
9 & -0.189022 & -1.852 & 0.033547 \tabularnewline
10 & -0.132033 & -1.2937 & 0.099444 \tabularnewline
11 & 0.096902 & 0.9494 & 0.17239 \tabularnewline
12 & 0.447965 & 4.3891 & 1.5e-05 \tabularnewline
13 & 0.098247 & 0.9626 & 0.169078 \tabularnewline
14 & -0.070675 & -0.6925 & 0.245156 \tabularnewline
15 & -0.151486 & -1.4843 & 0.070509 \tabularnewline
16 & -0.147338 & -1.4436 & 0.076051 \tabularnewline
17 & -0.00185 & -0.0181 & 0.492787 \tabularnewline
18 & 0.130639 & 1.28 & 0.101815 \tabularnewline
19 & -0.011346 & -0.1112 & 0.455857 \tabularnewline
20 & -0.102021 & -0.9996 & 0.160009 \tabularnewline
21 & -0.072964 & -0.7149 & 0.238203 \tabularnewline
22 & -0.03644 & -0.357 & 0.360922 \tabularnewline
23 & 0.060004 & 0.5879 & 0.278983 \tabularnewline
24 & 0.284902 & 2.7915 & 0.003166 \tabularnewline
25 & 0.011421 & 0.1119 & 0.455565 \tabularnewline
26 & -0.071159 & -0.6972 & 0.243676 \tabularnewline
27 & -0.101526 & -0.9947 & 0.16118 \tabularnewline
28 & -0.081706 & -0.8006 & 0.212683 \tabularnewline
29 & -0.004731 & -0.0464 & 0.481562 \tabularnewline
30 & 0.054434 & 0.5333 & 0.297516 \tabularnewline
31 & -0.015112 & -0.1481 & 0.4413 \tabularnewline
32 & -0.081892 & -0.8024 & 0.212159 \tabularnewline
33 & -0.019335 & -0.1894 & 0.425073 \tabularnewline
34 & 0.017687 & 0.1733 & 0.431393 \tabularnewline
35 & 0.054081 & 0.5299 & 0.298706 \tabularnewline
36 & 0.193393 & 1.8949 & 0.03056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61564&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]0.352944[/C][C]3.4581[/C][C]0.000406[/C][/ROW]
[ROW][C]2[/C][C]-0.199805[/C][C]-1.9577[/C][C]0.026585[/C][/ROW]
[ROW][C]3[/C][C]-0.47784[/C][C]-4.6819[/C][C]5e-06[/C][/ROW]
[ROW][C]4[/C][C]-0.381284[/C][C]-3.7358[/C][C]0.000159[/C][/ROW]
[ROW][C]5[/C][C]0.037278[/C][C]0.3653[/C][C]0.357864[/C][/ROW]
[ROW][C]6[/C][C]0.336902[/C][C]3.3009[/C][C]0.000677[/C][/ROW]
[ROW][C]7[/C][C]0.159922[/C][C]1.5669[/C][C]0.060213[/C][/ROW]
[ROW][C]8[/C][C]-0.120491[/C][C]-1.1806[/C][C]0.120347[/C][/ROW]
[ROW][C]9[/C][C]-0.189022[/C][C]-1.852[/C][C]0.033547[/C][/ROW]
[ROW][C]10[/C][C]-0.132033[/C][C]-1.2937[/C][C]0.099444[/C][/ROW]
[ROW][C]11[/C][C]0.096902[/C][C]0.9494[/C][C]0.17239[/C][/ROW]
[ROW][C]12[/C][C]0.447965[/C][C]4.3891[/C][C]1.5e-05[/C][/ROW]
[ROW][C]13[/C][C]0.098247[/C][C]0.9626[/C][C]0.169078[/C][/ROW]
[ROW][C]14[/C][C]-0.070675[/C][C]-0.6925[/C][C]0.245156[/C][/ROW]
[ROW][C]15[/C][C]-0.151486[/C][C]-1.4843[/C][C]0.070509[/C][/ROW]
[ROW][C]16[/C][C]-0.147338[/C][C]-1.4436[/C][C]0.076051[/C][/ROW]
[ROW][C]17[/C][C]-0.00185[/C][C]-0.0181[/C][C]0.492787[/C][/ROW]
[ROW][C]18[/C][C]0.130639[/C][C]1.28[/C][C]0.101815[/C][/ROW]
[ROW][C]19[/C][C]-0.011346[/C][C]-0.1112[/C][C]0.455857[/C][/ROW]
[ROW][C]20[/C][C]-0.102021[/C][C]-0.9996[/C][C]0.160009[/C][/ROW]
[ROW][C]21[/C][C]-0.072964[/C][C]-0.7149[/C][C]0.238203[/C][/ROW]
[ROW][C]22[/C][C]-0.03644[/C][C]-0.357[/C][C]0.360922[/C][/ROW]
[ROW][C]23[/C][C]0.060004[/C][C]0.5879[/C][C]0.278983[/C][/ROW]
[ROW][C]24[/C][C]0.284902[/C][C]2.7915[/C][C]0.003166[/C][/ROW]
[ROW][C]25[/C][C]0.011421[/C][C]0.1119[/C][C]0.455565[/C][/ROW]
[ROW][C]26[/C][C]-0.071159[/C][C]-0.6972[/C][C]0.243676[/C][/ROW]
[ROW][C]27[/C][C]-0.101526[/C][C]-0.9947[/C][C]0.16118[/C][/ROW]
[ROW][C]28[/C][C]-0.081706[/C][C]-0.8006[/C][C]0.212683[/C][/ROW]
[ROW][C]29[/C][C]-0.004731[/C][C]-0.0464[/C][C]0.481562[/C][/ROW]
[ROW][C]30[/C][C]0.054434[/C][C]0.5333[/C][C]0.297516[/C][/ROW]
[ROW][C]31[/C][C]-0.015112[/C][C]-0.1481[/C][C]0.4413[/C][/ROW]
[ROW][C]32[/C][C]-0.081892[/C][C]-0.8024[/C][C]0.212159[/C][/ROW]
[ROW][C]33[/C][C]-0.019335[/C][C]-0.1894[/C][C]0.425073[/C][/ROW]
[ROW][C]34[/C][C]0.017687[/C][C]0.1733[/C][C]0.431393[/C][/ROW]
[ROW][C]35[/C][C]0.054081[/C][C]0.5299[/C][C]0.298706[/C][/ROW]
[ROW][C]36[/C][C]0.193393[/C][C]1.8949[/C][C]0.03056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61564&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61564&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
10.3529443.45810.000406
2-0.199805-1.95770.026585
3-0.47784-4.68195e-06
4-0.381284-3.73580.000159
50.0372780.36530.357864
60.3369023.30090.000677
70.1599221.56690.060213
8-0.120491-1.18060.120347
9-0.189022-1.8520.033547
10-0.132033-1.29370.099444
110.0969020.94940.17239
120.4479654.38911.5e-05
130.0982470.96260.169078
14-0.070675-0.69250.245156
15-0.151486-1.48430.070509
16-0.147338-1.44360.076051
17-0.00185-0.01810.492787
180.1306391.280.101815
19-0.011346-0.11120.455857
20-0.102021-0.99960.160009
21-0.072964-0.71490.238203
22-0.03644-0.3570.360922
230.0600040.58790.278983
240.2849022.79150.003166
250.0114210.11190.455565
26-0.071159-0.69720.243676
27-0.101526-0.99470.16118
28-0.081706-0.80060.212683
29-0.004731-0.04640.481562
300.0544340.53330.297516
31-0.015112-0.14810.4413
32-0.081892-0.80240.212159
33-0.019335-0.18940.425073
340.0176870.17330.431393
350.0540810.52990.298706
360.1933931.89490.03056







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3529443.45810.000406
2-0.370532-3.63050.000228
3-0.331567-3.24870.000799
4-0.199063-1.95040.027022
50.0738280.72340.235607
60.0797380.78130.218282
7-0.209957-2.05720.021192
8-0.136216-1.33460.092576
90.0552390.54120.294802
10-0.055416-0.5430.294205
110.0082810.08110.467751
120.4019413.93827.8e-05
13-0.270689-2.65220.004679
140.2503712.45310.007983
150.152611.49530.069062
160.0212320.2080.417825
17-0.015655-0.15340.439207
180.0528550.51790.302868
19-0.062035-0.60780.272372
20-0.036915-0.36170.359188
21-0.099009-0.97010.167221
22-0.005569-0.05460.4783
23-0.071239-0.6980.243433
240.0774790.75910.224814
25-0.105162-1.03040.152711
26-0.004602-0.04510.482065
27-0.00184-0.0180.492828
280.0459460.45020.3268
29-0.080946-0.79310.214835
30-0.070119-0.6870.246863
310.1102141.07990.141453
32-0.131963-1.2930.099563
330.0170760.16730.433739
340.0556580.54530.293395
350.0068790.06740.473201
360.0115490.11320.455071

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.352944 & 3.4581 & 0.000406 \tabularnewline
2 & -0.370532 & -3.6305 & 0.000228 \tabularnewline
3 & -0.331567 & -3.2487 & 0.000799 \tabularnewline
4 & -0.199063 & -1.9504 & 0.027022 \tabularnewline
5 & 0.073828 & 0.7234 & 0.235607 \tabularnewline
6 & 0.079738 & 0.7813 & 0.218282 \tabularnewline
7 & -0.209957 & -2.0572 & 0.021192 \tabularnewline
8 & -0.136216 & -1.3346 & 0.092576 \tabularnewline
9 & 0.055239 & 0.5412 & 0.294802 \tabularnewline
10 & -0.055416 & -0.543 & 0.294205 \tabularnewline
11 & 0.008281 & 0.0811 & 0.467751 \tabularnewline
12 & 0.401941 & 3.9382 & 7.8e-05 \tabularnewline
13 & -0.270689 & -2.6522 & 0.004679 \tabularnewline
14 & 0.250371 & 2.4531 & 0.007983 \tabularnewline
15 & 0.15261 & 1.4953 & 0.069062 \tabularnewline
16 & 0.021232 & 0.208 & 0.417825 \tabularnewline
17 & -0.015655 & -0.1534 & 0.439207 \tabularnewline
18 & 0.052855 & 0.5179 & 0.302868 \tabularnewline
19 & -0.062035 & -0.6078 & 0.272372 \tabularnewline
20 & -0.036915 & -0.3617 & 0.359188 \tabularnewline
21 & -0.099009 & -0.9701 & 0.167221 \tabularnewline
22 & -0.005569 & -0.0546 & 0.4783 \tabularnewline
23 & -0.071239 & -0.698 & 0.243433 \tabularnewline
24 & 0.077479 & 0.7591 & 0.224814 \tabularnewline
25 & -0.105162 & -1.0304 & 0.152711 \tabularnewline
26 & -0.004602 & -0.0451 & 0.482065 \tabularnewline
27 & -0.00184 & -0.018 & 0.492828 \tabularnewline
28 & 0.045946 & 0.4502 & 0.3268 \tabularnewline
29 & -0.080946 & -0.7931 & 0.214835 \tabularnewline
30 & -0.070119 & -0.687 & 0.246863 \tabularnewline
31 & 0.110214 & 1.0799 & 0.141453 \tabularnewline
32 & -0.131963 & -1.293 & 0.099563 \tabularnewline
33 & 0.017076 & 0.1673 & 0.433739 \tabularnewline
34 & 0.055658 & 0.5453 & 0.293395 \tabularnewline
35 & 0.006879 & 0.0674 & 0.473201 \tabularnewline
36 & 0.011549 & 0.1132 & 0.455071 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61564&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]0.352944[/C][C]3.4581[/C][C]0.000406[/C][/ROW]
[ROW][C]2[/C][C]-0.370532[/C][C]-3.6305[/C][C]0.000228[/C][/ROW]
[ROW][C]3[/C][C]-0.331567[/C][C]-3.2487[/C][C]0.000799[/C][/ROW]
[ROW][C]4[/C][C]-0.199063[/C][C]-1.9504[/C][C]0.027022[/C][/ROW]
[ROW][C]5[/C][C]0.073828[/C][C]0.7234[/C][C]0.235607[/C][/ROW]
[ROW][C]6[/C][C]0.079738[/C][C]0.7813[/C][C]0.218282[/C][/ROW]
[ROW][C]7[/C][C]-0.209957[/C][C]-2.0572[/C][C]0.021192[/C][/ROW]
[ROW][C]8[/C][C]-0.136216[/C][C]-1.3346[/C][C]0.092576[/C][/ROW]
[ROW][C]9[/C][C]0.055239[/C][C]0.5412[/C][C]0.294802[/C][/ROW]
[ROW][C]10[/C][C]-0.055416[/C][C]-0.543[/C][C]0.294205[/C][/ROW]
[ROW][C]11[/C][C]0.008281[/C][C]0.0811[/C][C]0.467751[/C][/ROW]
[ROW][C]12[/C][C]0.401941[/C][C]3.9382[/C][C]7.8e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.270689[/C][C]-2.6522[/C][C]0.004679[/C][/ROW]
[ROW][C]14[/C][C]0.250371[/C][C]2.4531[/C][C]0.007983[/C][/ROW]
[ROW][C]15[/C][C]0.15261[/C][C]1.4953[/C][C]0.069062[/C][/ROW]
[ROW][C]16[/C][C]0.021232[/C][C]0.208[/C][C]0.417825[/C][/ROW]
[ROW][C]17[/C][C]-0.015655[/C][C]-0.1534[/C][C]0.439207[/C][/ROW]
[ROW][C]18[/C][C]0.052855[/C][C]0.5179[/C][C]0.302868[/C][/ROW]
[ROW][C]19[/C][C]-0.062035[/C][C]-0.6078[/C][C]0.272372[/C][/ROW]
[ROW][C]20[/C][C]-0.036915[/C][C]-0.3617[/C][C]0.359188[/C][/ROW]
[ROW][C]21[/C][C]-0.099009[/C][C]-0.9701[/C][C]0.167221[/C][/ROW]
[ROW][C]22[/C][C]-0.005569[/C][C]-0.0546[/C][C]0.4783[/C][/ROW]
[ROW][C]23[/C][C]-0.071239[/C][C]-0.698[/C][C]0.243433[/C][/ROW]
[ROW][C]24[/C][C]0.077479[/C][C]0.7591[/C][C]0.224814[/C][/ROW]
[ROW][C]25[/C][C]-0.105162[/C][C]-1.0304[/C][C]0.152711[/C][/ROW]
[ROW][C]26[/C][C]-0.004602[/C][C]-0.0451[/C][C]0.482065[/C][/ROW]
[ROW][C]27[/C][C]-0.00184[/C][C]-0.018[/C][C]0.492828[/C][/ROW]
[ROW][C]28[/C][C]0.045946[/C][C]0.4502[/C][C]0.3268[/C][/ROW]
[ROW][C]29[/C][C]-0.080946[/C][C]-0.7931[/C][C]0.214835[/C][/ROW]
[ROW][C]30[/C][C]-0.070119[/C][C]-0.687[/C][C]0.246863[/C][/ROW]
[ROW][C]31[/C][C]0.110214[/C][C]1.0799[/C][C]0.141453[/C][/ROW]
[ROW][C]32[/C][C]-0.131963[/C][C]-1.293[/C][C]0.099563[/C][/ROW]
[ROW][C]33[/C][C]0.017076[/C][C]0.1673[/C][C]0.433739[/C][/ROW]
[ROW][C]34[/C][C]0.055658[/C][C]0.5453[/C][C]0.293395[/C][/ROW]
[ROW][C]35[/C][C]0.006879[/C][C]0.0674[/C][C]0.473201[/C][/ROW]
[ROW][C]36[/C][C]0.011549[/C][C]0.1132[/C][C]0.455071[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61564&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61564&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
10.3529443.45810.000406
2-0.370532-3.63050.000228
3-0.331567-3.24870.000799
4-0.199063-1.95040.027022
50.0738280.72340.235607
60.0797380.78130.218282
7-0.209957-2.05720.021192
8-0.136216-1.33460.092576
90.0552390.54120.294802
10-0.055416-0.5430.294205
110.0082810.08110.467751
120.4019413.93827.8e-05
13-0.270689-2.65220.004679
140.2503712.45310.007983
150.152611.49530.069062
160.0212320.2080.417825
17-0.015655-0.15340.439207
180.0528550.51790.302868
19-0.062035-0.60780.272372
20-0.036915-0.36170.359188
21-0.099009-0.97010.167221
22-0.005569-0.05460.4783
23-0.071239-0.6980.243433
240.0774790.75910.224814
25-0.105162-1.03040.152711
26-0.004602-0.04510.482065
27-0.00184-0.0180.492828
280.0459460.45020.3268
29-0.080946-0.79310.214835
30-0.070119-0.6870.246863
310.1102141.07990.141453
32-0.131963-1.2930.099563
330.0170760.16730.433739
340.0556580.54530.293395
350.0068790.06740.473201
360.0115490.11320.455071



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')