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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 computationMon, 21 Dec 2009 13:51:18 -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/Dec/21/t1261428703omrwi3n1qkn0p1m.htm/, Retrieved Sun, 05 May 2024 12:11:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70376, Retrieved Sun, 05 May 2024 12:11:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Paper] [2009-12-21 20:51:18] [e339dd08bcbfc073ac7494f09a949034] [Current]
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Dataseries X:
25.6
23.7
22
21.3
20.7
20.4
20.3
20.4
19.8
19.5
23.1
23.5
23.5
22.9
21.9
21.5
20.5
20.2
19.4
19.2
18.8
18.8
22.6
23.3
23
21.4
19.9
18.8
18.6
18.4
18.6
19.9
19.2
18.4
21.1
20.5
19.1
18.1
17
17.1
17.4
16.8
15.3
14.3
13.4
15.3
22.1
23.7
22.2
19.5
16.6
17.3
19.8
21.2
21.5
20.6
19.1
19.6
23.5
24




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=70376&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=70376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70376&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
10.8305364.98328e-06
20.4795152.87710.003354
30.153310.91990.181884
4-0.005278-0.03170.487455
50.0290580.17440.431284
60.1795351.07720.144276
70.3111991.86720.035017
80.3099871.85990.035541
90.1432360.85940.197899
10-0.118823-0.71290.24024
11-0.33934-2.0360.024578
12-0.409689-2.45810.009455
13-0.304626-1.82780.037942
14-0.115147-0.69090.247035
150.0367390.22040.413389
160.0694630.41680.339657
17-0.004525-0.02710.489245
18-0.118641-0.71180.240575
19-0.217518-1.30510.100069
20-0.250348-1.50210.070898
21-0.205728-1.23440.112531
22-0.12157-0.72940.235233
23-0.046621-0.27970.390644
24-0.027925-0.16760.433937
25-0.063209-0.37930.353363
26-0.123422-0.74050.231889
27-0.175293-1.05180.14996
28-0.183578-1.10150.139002
29-0.145252-0.87150.194624
30-0.087511-0.52510.301379
31-0.027902-0.16740.433991
320.0168540.10110.460006
330.0241560.14490.442785
340.0107590.06460.474443
35-0.002403-0.01440.494288
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.830536 & 4.9832 & 8e-06 \tabularnewline
2 & 0.479515 & 2.8771 & 0.003354 \tabularnewline
3 & 0.15331 & 0.9199 & 0.181884 \tabularnewline
4 & -0.005278 & -0.0317 & 0.487455 \tabularnewline
5 & 0.029058 & 0.1744 & 0.431284 \tabularnewline
6 & 0.179535 & 1.0772 & 0.144276 \tabularnewline
7 & 0.311199 & 1.8672 & 0.035017 \tabularnewline
8 & 0.309987 & 1.8599 & 0.035541 \tabularnewline
9 & 0.143236 & 0.8594 & 0.197899 \tabularnewline
10 & -0.118823 & -0.7129 & 0.24024 \tabularnewline
11 & -0.33934 & -2.036 & 0.024578 \tabularnewline
12 & -0.409689 & -2.4581 & 0.009455 \tabularnewline
13 & -0.304626 & -1.8278 & 0.037942 \tabularnewline
14 & -0.115147 & -0.6909 & 0.247035 \tabularnewline
15 & 0.036739 & 0.2204 & 0.413389 \tabularnewline
16 & 0.069463 & 0.4168 & 0.339657 \tabularnewline
17 & -0.004525 & -0.0271 & 0.489245 \tabularnewline
18 & -0.118641 & -0.7118 & 0.240575 \tabularnewline
19 & -0.217518 & -1.3051 & 0.100069 \tabularnewline
20 & -0.250348 & -1.5021 & 0.070898 \tabularnewline
21 & -0.205728 & -1.2344 & 0.112531 \tabularnewline
22 & -0.12157 & -0.7294 & 0.235233 \tabularnewline
23 & -0.046621 & -0.2797 & 0.390644 \tabularnewline
24 & -0.027925 & -0.1676 & 0.433937 \tabularnewline
25 & -0.063209 & -0.3793 & 0.353363 \tabularnewline
26 & -0.123422 & -0.7405 & 0.231889 \tabularnewline
27 & -0.175293 & -1.0518 & 0.14996 \tabularnewline
28 & -0.183578 & -1.1015 & 0.139002 \tabularnewline
29 & -0.145252 & -0.8715 & 0.194624 \tabularnewline
30 & -0.087511 & -0.5251 & 0.301379 \tabularnewline
31 & -0.027902 & -0.1674 & 0.433991 \tabularnewline
32 & 0.016854 & 0.1011 & 0.460006 \tabularnewline
33 & 0.024156 & 0.1449 & 0.442785 \tabularnewline
34 & 0.010759 & 0.0646 & 0.474443 \tabularnewline
35 & -0.002403 & -0.0144 & 0.494288 \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70376&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]0.830536[/C][C]4.9832[/C][C]8e-06[/C][/ROW]
[ROW][C]2[/C][C]0.479515[/C][C]2.8771[/C][C]0.003354[/C][/ROW]
[ROW][C]3[/C][C]0.15331[/C][C]0.9199[/C][C]0.181884[/C][/ROW]
[ROW][C]4[/C][C]-0.005278[/C][C]-0.0317[/C][C]0.487455[/C][/ROW]
[ROW][C]5[/C][C]0.029058[/C][C]0.1744[/C][C]0.431284[/C][/ROW]
[ROW][C]6[/C][C]0.179535[/C][C]1.0772[/C][C]0.144276[/C][/ROW]
[ROW][C]7[/C][C]0.311199[/C][C]1.8672[/C][C]0.035017[/C][/ROW]
[ROW][C]8[/C][C]0.309987[/C][C]1.8599[/C][C]0.035541[/C][/ROW]
[ROW][C]9[/C][C]0.143236[/C][C]0.8594[/C][C]0.197899[/C][/ROW]
[ROW][C]10[/C][C]-0.118823[/C][C]-0.7129[/C][C]0.24024[/C][/ROW]
[ROW][C]11[/C][C]-0.33934[/C][C]-2.036[/C][C]0.024578[/C][/ROW]
[ROW][C]12[/C][C]-0.409689[/C][C]-2.4581[/C][C]0.009455[/C][/ROW]
[ROW][C]13[/C][C]-0.304626[/C][C]-1.8278[/C][C]0.037942[/C][/ROW]
[ROW][C]14[/C][C]-0.115147[/C][C]-0.6909[/C][C]0.247035[/C][/ROW]
[ROW][C]15[/C][C]0.036739[/C][C]0.2204[/C][C]0.413389[/C][/ROW]
[ROW][C]16[/C][C]0.069463[/C][C]0.4168[/C][C]0.339657[/C][/ROW]
[ROW][C]17[/C][C]-0.004525[/C][C]-0.0271[/C][C]0.489245[/C][/ROW]
[ROW][C]18[/C][C]-0.118641[/C][C]-0.7118[/C][C]0.240575[/C][/ROW]
[ROW][C]19[/C][C]-0.217518[/C][C]-1.3051[/C][C]0.100069[/C][/ROW]
[ROW][C]20[/C][C]-0.250348[/C][C]-1.5021[/C][C]0.070898[/C][/ROW]
[ROW][C]21[/C][C]-0.205728[/C][C]-1.2344[/C][C]0.112531[/C][/ROW]
[ROW][C]22[/C][C]-0.12157[/C][C]-0.7294[/C][C]0.235233[/C][/ROW]
[ROW][C]23[/C][C]-0.046621[/C][C]-0.2797[/C][C]0.390644[/C][/ROW]
[ROW][C]24[/C][C]-0.027925[/C][C]-0.1676[/C][C]0.433937[/C][/ROW]
[ROW][C]25[/C][C]-0.063209[/C][C]-0.3793[/C][C]0.353363[/C][/ROW]
[ROW][C]26[/C][C]-0.123422[/C][C]-0.7405[/C][C]0.231889[/C][/ROW]
[ROW][C]27[/C][C]-0.175293[/C][C]-1.0518[/C][C]0.14996[/C][/ROW]
[ROW][C]28[/C][C]-0.183578[/C][C]-1.1015[/C][C]0.139002[/C][/ROW]
[ROW][C]29[/C][C]-0.145252[/C][C]-0.8715[/C][C]0.194624[/C][/ROW]
[ROW][C]30[/C][C]-0.087511[/C][C]-0.5251[/C][C]0.301379[/C][/ROW]
[ROW][C]31[/C][C]-0.027902[/C][C]-0.1674[/C][C]0.433991[/C][/ROW]
[ROW][C]32[/C][C]0.016854[/C][C]0.1011[/C][C]0.460006[/C][/ROW]
[ROW][C]33[/C][C]0.024156[/C][C]0.1449[/C][C]0.442785[/C][/ROW]
[ROW][C]34[/C][C]0.010759[/C][C]0.0646[/C][C]0.474443[/C][/ROW]
[ROW][C]35[/C][C]-0.002403[/C][C]-0.0144[/C][C]0.494288[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70376&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
10.8305364.98328e-06
20.4795152.87710.003354
30.153310.91990.181884
4-0.005278-0.03170.487455
50.0290580.17440.431284
60.1795351.07720.144276
70.3111991.86720.035017
80.3099871.85990.035541
90.1432360.85940.197899
10-0.118823-0.71290.24024
11-0.33934-2.0360.024578
12-0.409689-2.45810.009455
13-0.304626-1.82780.037942
14-0.115147-0.69090.247035
150.0367390.22040.413389
160.0694630.41680.339657
17-0.004525-0.02710.489245
18-0.118641-0.71180.240575
19-0.217518-1.30510.100069
20-0.250348-1.50210.070898
21-0.205728-1.23440.112531
22-0.12157-0.72940.235233
23-0.046621-0.27970.390644
24-0.027925-0.16760.433937
25-0.063209-0.37930.353363
26-0.123422-0.74050.231889
27-0.175293-1.05180.14996
28-0.183578-1.10150.139002
29-0.145252-0.87150.194624
30-0.087511-0.52510.301379
31-0.027902-0.16740.433991
320.0168540.10110.460006
330.0241560.14490.442785
340.0107590.06460.474443
35-0.002403-0.01440.494288
36NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8305364.98328e-06
2-0.677847-4.06710.000124
30.2867211.72030.04698
40.1935221.16110.126615
50.1315890.78950.217484
60.0783440.47010.320572
7-0.087103-0.52260.302221
8-0.161936-0.97160.168862
9-0.201347-1.20810.117446
10-0.131899-0.79140.216949
110.0078610.04720.48132
120.0151210.09070.464106
130.0943720.56620.287375
14-0.077287-0.46370.322819
150.0232970.13980.444805
160.0104430.06270.475194
170.1085280.65120.259537
18-0.002517-0.01510.494017
19-0.214195-1.28520.10347
20-0.047212-0.28330.389295
21-0.096865-0.58120.282367
22-0.084506-0.5070.307611
230.0536510.32190.374692
24-0.086878-0.52130.302686
250.0817430.49050.313393
26-0.056542-0.33930.368194
27-0.030341-0.1820.428285
280.0983830.59030.279338
29-0.037938-0.22760.410611
30-0.041846-0.25110.401591
310.0118380.0710.471885
32-0.041016-0.24610.403504
33-0.106492-0.6390.263449
340.1103790.66230.256006
35-0.008715-0.05230.479293
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.830536 & 4.9832 & 8e-06 \tabularnewline
2 & -0.677847 & -4.0671 & 0.000124 \tabularnewline
3 & 0.286721 & 1.7203 & 0.04698 \tabularnewline
4 & 0.193522 & 1.1611 & 0.126615 \tabularnewline
5 & 0.131589 & 0.7895 & 0.217484 \tabularnewline
6 & 0.078344 & 0.4701 & 0.320572 \tabularnewline
7 & -0.087103 & -0.5226 & 0.302221 \tabularnewline
8 & -0.161936 & -0.9716 & 0.168862 \tabularnewline
9 & -0.201347 & -1.2081 & 0.117446 \tabularnewline
10 & -0.131899 & -0.7914 & 0.216949 \tabularnewline
11 & 0.007861 & 0.0472 & 0.48132 \tabularnewline
12 & 0.015121 & 0.0907 & 0.464106 \tabularnewline
13 & 0.094372 & 0.5662 & 0.287375 \tabularnewline
14 & -0.077287 & -0.4637 & 0.322819 \tabularnewline
15 & 0.023297 & 0.1398 & 0.444805 \tabularnewline
16 & 0.010443 & 0.0627 & 0.475194 \tabularnewline
17 & 0.108528 & 0.6512 & 0.259537 \tabularnewline
18 & -0.002517 & -0.0151 & 0.494017 \tabularnewline
19 & -0.214195 & -1.2852 & 0.10347 \tabularnewline
20 & -0.047212 & -0.2833 & 0.389295 \tabularnewline
21 & -0.096865 & -0.5812 & 0.282367 \tabularnewline
22 & -0.084506 & -0.507 & 0.307611 \tabularnewline
23 & 0.053651 & 0.3219 & 0.374692 \tabularnewline
24 & -0.086878 & -0.5213 & 0.302686 \tabularnewline
25 & 0.081743 & 0.4905 & 0.313393 \tabularnewline
26 & -0.056542 & -0.3393 & 0.368194 \tabularnewline
27 & -0.030341 & -0.182 & 0.428285 \tabularnewline
28 & 0.098383 & 0.5903 & 0.279338 \tabularnewline
29 & -0.037938 & -0.2276 & 0.410611 \tabularnewline
30 & -0.041846 & -0.2511 & 0.401591 \tabularnewline
31 & 0.011838 & 0.071 & 0.471885 \tabularnewline
32 & -0.041016 & -0.2461 & 0.403504 \tabularnewline
33 & -0.106492 & -0.639 & 0.263449 \tabularnewline
34 & 0.110379 & 0.6623 & 0.256006 \tabularnewline
35 & -0.008715 & -0.0523 & 0.479293 \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70376&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]0.830536[/C][C]4.9832[/C][C]8e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.677847[/C][C]-4.0671[/C][C]0.000124[/C][/ROW]
[ROW][C]3[/C][C]0.286721[/C][C]1.7203[/C][C]0.04698[/C][/ROW]
[ROW][C]4[/C][C]0.193522[/C][C]1.1611[/C][C]0.126615[/C][/ROW]
[ROW][C]5[/C][C]0.131589[/C][C]0.7895[/C][C]0.217484[/C][/ROW]
[ROW][C]6[/C][C]0.078344[/C][C]0.4701[/C][C]0.320572[/C][/ROW]
[ROW][C]7[/C][C]-0.087103[/C][C]-0.5226[/C][C]0.302221[/C][/ROW]
[ROW][C]8[/C][C]-0.161936[/C][C]-0.9716[/C][C]0.168862[/C][/ROW]
[ROW][C]9[/C][C]-0.201347[/C][C]-1.2081[/C][C]0.117446[/C][/ROW]
[ROW][C]10[/C][C]-0.131899[/C][C]-0.7914[/C][C]0.216949[/C][/ROW]
[ROW][C]11[/C][C]0.007861[/C][C]0.0472[/C][C]0.48132[/C][/ROW]
[ROW][C]12[/C][C]0.015121[/C][C]0.0907[/C][C]0.464106[/C][/ROW]
[ROW][C]13[/C][C]0.094372[/C][C]0.5662[/C][C]0.287375[/C][/ROW]
[ROW][C]14[/C][C]-0.077287[/C][C]-0.4637[/C][C]0.322819[/C][/ROW]
[ROW][C]15[/C][C]0.023297[/C][C]0.1398[/C][C]0.444805[/C][/ROW]
[ROW][C]16[/C][C]0.010443[/C][C]0.0627[/C][C]0.475194[/C][/ROW]
[ROW][C]17[/C][C]0.108528[/C][C]0.6512[/C][C]0.259537[/C][/ROW]
[ROW][C]18[/C][C]-0.002517[/C][C]-0.0151[/C][C]0.494017[/C][/ROW]
[ROW][C]19[/C][C]-0.214195[/C][C]-1.2852[/C][C]0.10347[/C][/ROW]
[ROW][C]20[/C][C]-0.047212[/C][C]-0.2833[/C][C]0.389295[/C][/ROW]
[ROW][C]21[/C][C]-0.096865[/C][C]-0.5812[/C][C]0.282367[/C][/ROW]
[ROW][C]22[/C][C]-0.084506[/C][C]-0.507[/C][C]0.307611[/C][/ROW]
[ROW][C]23[/C][C]0.053651[/C][C]0.3219[/C][C]0.374692[/C][/ROW]
[ROW][C]24[/C][C]-0.086878[/C][C]-0.5213[/C][C]0.302686[/C][/ROW]
[ROW][C]25[/C][C]0.081743[/C][C]0.4905[/C][C]0.313393[/C][/ROW]
[ROW][C]26[/C][C]-0.056542[/C][C]-0.3393[/C][C]0.368194[/C][/ROW]
[ROW][C]27[/C][C]-0.030341[/C][C]-0.182[/C][C]0.428285[/C][/ROW]
[ROW][C]28[/C][C]0.098383[/C][C]0.5903[/C][C]0.279338[/C][/ROW]
[ROW][C]29[/C][C]-0.037938[/C][C]-0.2276[/C][C]0.410611[/C][/ROW]
[ROW][C]30[/C][C]-0.041846[/C][C]-0.2511[/C][C]0.401591[/C][/ROW]
[ROW][C]31[/C][C]0.011838[/C][C]0.071[/C][C]0.471885[/C][/ROW]
[ROW][C]32[/C][C]-0.041016[/C][C]-0.2461[/C][C]0.403504[/C][/ROW]
[ROW][C]33[/C][C]-0.106492[/C][C]-0.639[/C][C]0.263449[/C][/ROW]
[ROW][C]34[/C][C]0.110379[/C][C]0.6623[/C][C]0.256006[/C][/ROW]
[ROW][C]35[/C][C]-0.008715[/C][C]-0.0523[/C][C]0.479293[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70376&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70376&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
10.8305364.98328e-06
2-0.677847-4.06710.000124
30.2867211.72030.04698
40.1935221.16110.126615
50.1315890.78950.217484
60.0783440.47010.320572
7-0.087103-0.52260.302221
8-0.161936-0.97160.168862
9-0.201347-1.20810.117446
10-0.131899-0.79140.216949
110.0078610.04720.48132
120.0151210.09070.464106
130.0943720.56620.287375
14-0.077287-0.46370.322819
150.0232970.13980.444805
160.0104430.06270.475194
170.1085280.65120.259537
18-0.002517-0.01510.494017
19-0.214195-1.28520.10347
20-0.047212-0.28330.389295
21-0.096865-0.58120.282367
22-0.084506-0.5070.307611
230.0536510.32190.374692
24-0.086878-0.52130.302686
250.0817430.49050.313393
26-0.056542-0.33930.368194
27-0.030341-0.1820.428285
280.0983830.59030.279338
29-0.037938-0.22760.410611
30-0.041846-0.25110.401591
310.0118380.0710.471885
32-0.041016-0.24610.403504
33-0.106492-0.6390.263449
340.1103790.66230.256006
35-0.008715-0.05230.479293
36NANANA



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; 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')