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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, 06 Dec 2009 08:35:28 -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/06/t1260113993zuzynyao2qvg6zh.htm/, Retrieved Mon, 06 May 2024 06:37:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64435, Retrieved Mon, 06 May 2024 06:37:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
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] [] [2009-12-06 15:35:28] [0545e25c765ce26b196961216dc11e13] [Current]
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Dataseries X:
9051
8823
8776
8255
7969
8758
8693
8271
7790
7769
8170
8209
9395
9260
9018
8501
8500
9649
9319
8830
8436
8169
8269
7945
9144
8770
8834
7837
7792
8616
8518
7940
7545
7531
7665
7599
8444
8549
7986
7335
7287
7870
7839
7327
7259
6964
7271
6956
7608
7692
7255
6804
6655
7341
7602
7086
6625
6272
6576
6491
7649
7400
6913
6532
6486
7295
7556
7088
6952
6773
6917
7371
8221
7953
8027
7287
8076
8933
9433
9479
9199
9469
10015
10999
13009
13699
13895
13248
13973
15095
15201
14823
14538
14547
14407




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=64435&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=64435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64435&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
10.9335189.09880
20.8539638.32340
30.7823887.62580
40.7268027.0840
50.6661276.49260
60.5851995.70380
70.5054324.92632e-06
80.4166464.0615e-05
90.3226213.14450.00111
100.2522142.45830.007886
110.2033991.98250.025157
120.1738881.69490.04669
130.1165811.13630.129347
140.0615250.59970.275077
150.0202880.19770.421836
16-0.003454-0.03370.486605
17-0.024032-0.23420.407652
18-0.049277-0.48030.316063
19-0.073002-0.71150.239248
20-0.09835-0.95860.170099
21-0.129785-1.2650.104484
22-0.140862-1.3730.0865
23-0.141972-1.38380.084835
24-0.137538-1.34060.091631
25-0.158411-1.5440.062956
26-0.181844-1.77240.039768
27-0.195405-1.90460.02993
28-0.192861-1.87980.031601
29-0.192932-1.88050.031554
30-0.196722-1.91740.029095
31-0.197869-1.92860.028384
32-0.207152-2.01910.023149
33-0.218258-2.12730.017992
34-0.216701-2.11210.018649
35-0.208807-2.03520.022308
36-0.190615-1.85790.033141

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.933518 & 9.0988 & 0 \tabularnewline
2 & 0.853963 & 8.3234 & 0 \tabularnewline
3 & 0.782388 & 7.6258 & 0 \tabularnewline
4 & 0.726802 & 7.084 & 0 \tabularnewline
5 & 0.666127 & 6.4926 & 0 \tabularnewline
6 & 0.585199 & 5.7038 & 0 \tabularnewline
7 & 0.505432 & 4.9263 & 2e-06 \tabularnewline
8 & 0.416646 & 4.061 & 5e-05 \tabularnewline
9 & 0.322621 & 3.1445 & 0.00111 \tabularnewline
10 & 0.252214 & 2.4583 & 0.007886 \tabularnewline
11 & 0.203399 & 1.9825 & 0.025157 \tabularnewline
12 & 0.173888 & 1.6949 & 0.04669 \tabularnewline
13 & 0.116581 & 1.1363 & 0.129347 \tabularnewline
14 & 0.061525 & 0.5997 & 0.275077 \tabularnewline
15 & 0.020288 & 0.1977 & 0.421836 \tabularnewline
16 & -0.003454 & -0.0337 & 0.486605 \tabularnewline
17 & -0.024032 & -0.2342 & 0.407652 \tabularnewline
18 & -0.049277 & -0.4803 & 0.316063 \tabularnewline
19 & -0.073002 & -0.7115 & 0.239248 \tabularnewline
20 & -0.09835 & -0.9586 & 0.170099 \tabularnewline
21 & -0.129785 & -1.265 & 0.104484 \tabularnewline
22 & -0.140862 & -1.373 & 0.0865 \tabularnewline
23 & -0.141972 & -1.3838 & 0.084835 \tabularnewline
24 & -0.137538 & -1.3406 & 0.091631 \tabularnewline
25 & -0.158411 & -1.544 & 0.062956 \tabularnewline
26 & -0.181844 & -1.7724 & 0.039768 \tabularnewline
27 & -0.195405 & -1.9046 & 0.02993 \tabularnewline
28 & -0.192861 & -1.8798 & 0.031601 \tabularnewline
29 & -0.192932 & -1.8805 & 0.031554 \tabularnewline
30 & -0.196722 & -1.9174 & 0.029095 \tabularnewline
31 & -0.197869 & -1.9286 & 0.028384 \tabularnewline
32 & -0.207152 & -2.0191 & 0.023149 \tabularnewline
33 & -0.218258 & -2.1273 & 0.017992 \tabularnewline
34 & -0.216701 & -2.1121 & 0.018649 \tabularnewline
35 & -0.208807 & -2.0352 & 0.022308 \tabularnewline
36 & -0.190615 & -1.8579 & 0.033141 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64435&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]0.933518[/C][C]9.0988[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.853963[/C][C]8.3234[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.782388[/C][C]7.6258[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.726802[/C][C]7.084[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.666127[/C][C]6.4926[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.585199[/C][C]5.7038[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.505432[/C][C]4.9263[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.416646[/C][C]4.061[/C][C]5e-05[/C][/ROW]
[ROW][C]9[/C][C]0.322621[/C][C]3.1445[/C][C]0.00111[/C][/ROW]
[ROW][C]10[/C][C]0.252214[/C][C]2.4583[/C][C]0.007886[/C][/ROW]
[ROW][C]11[/C][C]0.203399[/C][C]1.9825[/C][C]0.025157[/C][/ROW]
[ROW][C]12[/C][C]0.173888[/C][C]1.6949[/C][C]0.04669[/C][/ROW]
[ROW][C]13[/C][C]0.116581[/C][C]1.1363[/C][C]0.129347[/C][/ROW]
[ROW][C]14[/C][C]0.061525[/C][C]0.5997[/C][C]0.275077[/C][/ROW]
[ROW][C]15[/C][C]0.020288[/C][C]0.1977[/C][C]0.421836[/C][/ROW]
[ROW][C]16[/C][C]-0.003454[/C][C]-0.0337[/C][C]0.486605[/C][/ROW]
[ROW][C]17[/C][C]-0.024032[/C][C]-0.2342[/C][C]0.407652[/C][/ROW]
[ROW][C]18[/C][C]-0.049277[/C][C]-0.4803[/C][C]0.316063[/C][/ROW]
[ROW][C]19[/C][C]-0.073002[/C][C]-0.7115[/C][C]0.239248[/C][/ROW]
[ROW][C]20[/C][C]-0.09835[/C][C]-0.9586[/C][C]0.170099[/C][/ROW]
[ROW][C]21[/C][C]-0.129785[/C][C]-1.265[/C][C]0.104484[/C][/ROW]
[ROW][C]22[/C][C]-0.140862[/C][C]-1.373[/C][C]0.0865[/C][/ROW]
[ROW][C]23[/C][C]-0.141972[/C][C]-1.3838[/C][C]0.084835[/C][/ROW]
[ROW][C]24[/C][C]-0.137538[/C][C]-1.3406[/C][C]0.091631[/C][/ROW]
[ROW][C]25[/C][C]-0.158411[/C][C]-1.544[/C][C]0.062956[/C][/ROW]
[ROW][C]26[/C][C]-0.181844[/C][C]-1.7724[/C][C]0.039768[/C][/ROW]
[ROW][C]27[/C][C]-0.195405[/C][C]-1.9046[/C][C]0.02993[/C][/ROW]
[ROW][C]28[/C][C]-0.192861[/C][C]-1.8798[/C][C]0.031601[/C][/ROW]
[ROW][C]29[/C][C]-0.192932[/C][C]-1.8805[/C][C]0.031554[/C][/ROW]
[ROW][C]30[/C][C]-0.196722[/C][C]-1.9174[/C][C]0.029095[/C][/ROW]
[ROW][C]31[/C][C]-0.197869[/C][C]-1.9286[/C][C]0.028384[/C][/ROW]
[ROW][C]32[/C][C]-0.207152[/C][C]-2.0191[/C][C]0.023149[/C][/ROW]
[ROW][C]33[/C][C]-0.218258[/C][C]-2.1273[/C][C]0.017992[/C][/ROW]
[ROW][C]34[/C][C]-0.216701[/C][C]-2.1121[/C][C]0.018649[/C][/ROW]
[ROW][C]35[/C][C]-0.208807[/C][C]-2.0352[/C][C]0.022308[/C][/ROW]
[ROW][C]36[/C][C]-0.190615[/C][C]-1.8579[/C][C]0.033141[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64435&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
10.9335189.09880
20.8539638.32340
30.7823887.62580
40.7268027.0840
50.6661276.49260
60.5851995.70380
70.5054324.92632e-06
80.4166464.0615e-05
90.3226213.14450.00111
100.2522142.45830.007886
110.2033991.98250.025157
120.1738881.69490.04669
130.1165811.13630.129347
140.0615250.59970.275077
150.0202880.19770.421836
16-0.003454-0.03370.486605
17-0.024032-0.23420.407652
18-0.049277-0.48030.316063
19-0.073002-0.71150.239248
20-0.09835-0.95860.170099
21-0.129785-1.2650.104484
22-0.140862-1.3730.0865
23-0.141972-1.38380.084835
24-0.137538-1.34060.091631
25-0.158411-1.5440.062956
26-0.181844-1.77240.039768
27-0.195405-1.90460.02993
28-0.192861-1.87980.031601
29-0.192932-1.88050.031554
30-0.196722-1.91740.029095
31-0.197869-1.92860.028384
32-0.207152-2.01910.023149
33-0.218258-2.12730.017992
34-0.216701-2.11210.018649
35-0.208807-2.03520.022308
36-0.190615-1.85790.033141







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9335189.09880
2-0.136081-1.32640.093951
30.0297270.28970.386324
40.0734190.71560.237997
5-0.093382-0.91020.182517
6-0.17632-1.71860.044476
7-0.002869-0.0280.488873
8-0.157277-1.5330.064306
9-0.12333-1.20210.116161
100.1497651.45970.073832
110.0829310.80830.210464
120.0930540.9070.183357
13-0.206573-2.01340.023449
140.0500310.48760.313464
150.0033430.03260.487038
160.0061410.05990.476197
17-0.057382-0.55930.28864
18-0.026894-0.26210.396893
19-0.045322-0.44170.329838
20-0.027887-0.27180.393178
21-0.033845-0.32990.371109
220.1111081.0830.140786
23-0.007092-0.06910.472517
24-0.020484-0.19960.421091
25-0.118043-1.15050.126404
260.0044770.04360.482644
27-0.018392-0.17930.429055
280.0388010.37820.353067
29-0.068039-0.66320.254416
30-0.003328-0.03240.487095
310.0286260.2790.39042
32-0.083562-0.81450.208708
330.0361590.35240.362648
340.016180.15770.437514
35-0.045086-0.43940.330669
360.0385920.37610.353823

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.933518 & 9.0988 & 0 \tabularnewline
2 & -0.136081 & -1.3264 & 0.093951 \tabularnewline
3 & 0.029727 & 0.2897 & 0.386324 \tabularnewline
4 & 0.073419 & 0.7156 & 0.237997 \tabularnewline
5 & -0.093382 & -0.9102 & 0.182517 \tabularnewline
6 & -0.17632 & -1.7186 & 0.044476 \tabularnewline
7 & -0.002869 & -0.028 & 0.488873 \tabularnewline
8 & -0.157277 & -1.533 & 0.064306 \tabularnewline
9 & -0.12333 & -1.2021 & 0.116161 \tabularnewline
10 & 0.149765 & 1.4597 & 0.073832 \tabularnewline
11 & 0.082931 & 0.8083 & 0.210464 \tabularnewline
12 & 0.093054 & 0.907 & 0.183357 \tabularnewline
13 & -0.206573 & -2.0134 & 0.023449 \tabularnewline
14 & 0.050031 & 0.4876 & 0.313464 \tabularnewline
15 & 0.003343 & 0.0326 & 0.487038 \tabularnewline
16 & 0.006141 & 0.0599 & 0.476197 \tabularnewline
17 & -0.057382 & -0.5593 & 0.28864 \tabularnewline
18 & -0.026894 & -0.2621 & 0.396893 \tabularnewline
19 & -0.045322 & -0.4417 & 0.329838 \tabularnewline
20 & -0.027887 & -0.2718 & 0.393178 \tabularnewline
21 & -0.033845 & -0.3299 & 0.371109 \tabularnewline
22 & 0.111108 & 1.083 & 0.140786 \tabularnewline
23 & -0.007092 & -0.0691 & 0.472517 \tabularnewline
24 & -0.020484 & -0.1996 & 0.421091 \tabularnewline
25 & -0.118043 & -1.1505 & 0.126404 \tabularnewline
26 & 0.004477 & 0.0436 & 0.482644 \tabularnewline
27 & -0.018392 & -0.1793 & 0.429055 \tabularnewline
28 & 0.038801 & 0.3782 & 0.353067 \tabularnewline
29 & -0.068039 & -0.6632 & 0.254416 \tabularnewline
30 & -0.003328 & -0.0324 & 0.487095 \tabularnewline
31 & 0.028626 & 0.279 & 0.39042 \tabularnewline
32 & -0.083562 & -0.8145 & 0.208708 \tabularnewline
33 & 0.036159 & 0.3524 & 0.362648 \tabularnewline
34 & 0.01618 & 0.1577 & 0.437514 \tabularnewline
35 & -0.045086 & -0.4394 & 0.330669 \tabularnewline
36 & 0.038592 & 0.3761 & 0.353823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64435&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]0.933518[/C][C]9.0988[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.136081[/C][C]-1.3264[/C][C]0.093951[/C][/ROW]
[ROW][C]3[/C][C]0.029727[/C][C]0.2897[/C][C]0.386324[/C][/ROW]
[ROW][C]4[/C][C]0.073419[/C][C]0.7156[/C][C]0.237997[/C][/ROW]
[ROW][C]5[/C][C]-0.093382[/C][C]-0.9102[/C][C]0.182517[/C][/ROW]
[ROW][C]6[/C][C]-0.17632[/C][C]-1.7186[/C][C]0.044476[/C][/ROW]
[ROW][C]7[/C][C]-0.002869[/C][C]-0.028[/C][C]0.488873[/C][/ROW]
[ROW][C]8[/C][C]-0.157277[/C][C]-1.533[/C][C]0.064306[/C][/ROW]
[ROW][C]9[/C][C]-0.12333[/C][C]-1.2021[/C][C]0.116161[/C][/ROW]
[ROW][C]10[/C][C]0.149765[/C][C]1.4597[/C][C]0.073832[/C][/ROW]
[ROW][C]11[/C][C]0.082931[/C][C]0.8083[/C][C]0.210464[/C][/ROW]
[ROW][C]12[/C][C]0.093054[/C][C]0.907[/C][C]0.183357[/C][/ROW]
[ROW][C]13[/C][C]-0.206573[/C][C]-2.0134[/C][C]0.023449[/C][/ROW]
[ROW][C]14[/C][C]0.050031[/C][C]0.4876[/C][C]0.313464[/C][/ROW]
[ROW][C]15[/C][C]0.003343[/C][C]0.0326[/C][C]0.487038[/C][/ROW]
[ROW][C]16[/C][C]0.006141[/C][C]0.0599[/C][C]0.476197[/C][/ROW]
[ROW][C]17[/C][C]-0.057382[/C][C]-0.5593[/C][C]0.28864[/C][/ROW]
[ROW][C]18[/C][C]-0.026894[/C][C]-0.2621[/C][C]0.396893[/C][/ROW]
[ROW][C]19[/C][C]-0.045322[/C][C]-0.4417[/C][C]0.329838[/C][/ROW]
[ROW][C]20[/C][C]-0.027887[/C][C]-0.2718[/C][C]0.393178[/C][/ROW]
[ROW][C]21[/C][C]-0.033845[/C][C]-0.3299[/C][C]0.371109[/C][/ROW]
[ROW][C]22[/C][C]0.111108[/C][C]1.083[/C][C]0.140786[/C][/ROW]
[ROW][C]23[/C][C]-0.007092[/C][C]-0.0691[/C][C]0.472517[/C][/ROW]
[ROW][C]24[/C][C]-0.020484[/C][C]-0.1996[/C][C]0.421091[/C][/ROW]
[ROW][C]25[/C][C]-0.118043[/C][C]-1.1505[/C][C]0.126404[/C][/ROW]
[ROW][C]26[/C][C]0.004477[/C][C]0.0436[/C][C]0.482644[/C][/ROW]
[ROW][C]27[/C][C]-0.018392[/C][C]-0.1793[/C][C]0.429055[/C][/ROW]
[ROW][C]28[/C][C]0.038801[/C][C]0.3782[/C][C]0.353067[/C][/ROW]
[ROW][C]29[/C][C]-0.068039[/C][C]-0.6632[/C][C]0.254416[/C][/ROW]
[ROW][C]30[/C][C]-0.003328[/C][C]-0.0324[/C][C]0.487095[/C][/ROW]
[ROW][C]31[/C][C]0.028626[/C][C]0.279[/C][C]0.39042[/C][/ROW]
[ROW][C]32[/C][C]-0.083562[/C][C]-0.8145[/C][C]0.208708[/C][/ROW]
[ROW][C]33[/C][C]0.036159[/C][C]0.3524[/C][C]0.362648[/C][/ROW]
[ROW][C]34[/C][C]0.01618[/C][C]0.1577[/C][C]0.437514[/C][/ROW]
[ROW][C]35[/C][C]-0.045086[/C][C]-0.4394[/C][C]0.330669[/C][/ROW]
[ROW][C]36[/C][C]0.038592[/C][C]0.3761[/C][C]0.353823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64435&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64435&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
10.9335189.09880
2-0.136081-1.32640.093951
30.0297270.28970.386324
40.0734190.71560.237997
5-0.093382-0.91020.182517
6-0.17632-1.71860.044476
7-0.002869-0.0280.488873
8-0.157277-1.5330.064306
9-0.12333-1.20210.116161
100.1497651.45970.073832
110.0829310.80830.210464
120.0930540.9070.183357
13-0.206573-2.01340.023449
140.0500310.48760.313464
150.0033430.03260.487038
160.0061410.05990.476197
17-0.057382-0.55930.28864
18-0.026894-0.26210.396893
19-0.045322-0.44170.329838
20-0.027887-0.27180.393178
21-0.033845-0.32990.371109
220.1111081.0830.140786
23-0.007092-0.06910.472517
24-0.020484-0.19960.421091
25-0.118043-1.15050.126404
260.0044770.04360.482644
27-0.018392-0.17930.429055
280.0388010.37820.353067
29-0.068039-0.66320.254416
30-0.003328-0.03240.487095
310.0286260.2790.39042
32-0.083562-0.81450.208708
330.0361590.35240.362648
340.016180.15770.437514
35-0.045086-0.43940.330669
360.0385920.37610.353823



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