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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 computationTue, 24 Nov 2009 11:55:10 -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/24/t1259089077imcgx8d000xu9dq.htm/, Retrieved Fri, 26 Apr 2024 19:36:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59226, Retrieved Fri, 26 Apr 2024 19:36:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
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] [WS8] [2009-11-24 18:55:10] [9a1fef436e1d399a5ecd6808bfbd8489] [Current]
-   P             [(Partial) Autocorrelation Function] [WS8] [2009-11-26 20:37:24] [b8b64ced21f32e31669b267b64eede7f]
-   P             [(Partial) Autocorrelation Function] [WS8] [2009-11-26 20:40:39] [b8b64ced21f32e31669b267b64eede7f]
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Dataseries X:
3922
3759
4138
4634
3995
4308
4143
4429
5219
4929
5755
5592
4163
4962
5208
4755
4491
5732
5731
5040
6102
4904
5369
5578
4619
4731
5011
5299
4146
4625
4736
4219
5116
4205
4121
5103
4300
4578
3809
5526
4247
3830
4394
4826
4409
4569
4106
4794
3914
3793
4405
4022
4100
4788
3163
3585
3903
4178
3863
4187




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=59226&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=59226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59226&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
10.3754512.90820.002545
20.3526372.73150.004134
30.4857183.76240.000192
40.3414482.64480.005208
50.265752.05850.021947
60.2264481.75410.042263
70.2466011.91020.030448
80.1854831.43670.077992
90.1687991.30750.098014
100.1705831.32130.095704
11-0.043804-0.33930.367783
120.1782881.3810.086199
130.0463110.35870.360531
14-0.030149-0.23350.408071
15-0.038322-0.29680.383808
16-0.070069-0.54280.294656
17-0.05425-0.42020.337914
18-0.089643-0.69440.245066
19-0.147002-1.13870.129683
20-0.148233-1.14820.12772
21-0.055308-0.42840.334941
22-0.090401-0.70020.24324
23-0.181918-1.40910.081979
24-0.077041-0.59680.276458
25-0.073349-0.56820.286023
26-0.111904-0.86680.194752
27-0.137161-1.06240.146146
28-0.160431-1.24270.109407
29-0.119554-0.92610.179062
30-0.130737-1.01270.157639
31-0.247009-1.91330.030241
32-0.209858-1.62560.054643
33-0.141352-1.09490.138967
34-0.202231-1.56650.061248
35-0.226513-1.75460.04222
36-0.156043-1.20870.115759

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375451 & 2.9082 & 0.002545 \tabularnewline
2 & 0.352637 & 2.7315 & 0.004134 \tabularnewline
3 & 0.485718 & 3.7624 & 0.000192 \tabularnewline
4 & 0.341448 & 2.6448 & 0.005208 \tabularnewline
5 & 0.26575 & 2.0585 & 0.021947 \tabularnewline
6 & 0.226448 & 1.7541 & 0.042263 \tabularnewline
7 & 0.246601 & 1.9102 & 0.030448 \tabularnewline
8 & 0.185483 & 1.4367 & 0.077992 \tabularnewline
9 & 0.168799 & 1.3075 & 0.098014 \tabularnewline
10 & 0.170583 & 1.3213 & 0.095704 \tabularnewline
11 & -0.043804 & -0.3393 & 0.367783 \tabularnewline
12 & 0.178288 & 1.381 & 0.086199 \tabularnewline
13 & 0.046311 & 0.3587 & 0.360531 \tabularnewline
14 & -0.030149 & -0.2335 & 0.408071 \tabularnewline
15 & -0.038322 & -0.2968 & 0.383808 \tabularnewline
16 & -0.070069 & -0.5428 & 0.294656 \tabularnewline
17 & -0.05425 & -0.4202 & 0.337914 \tabularnewline
18 & -0.089643 & -0.6944 & 0.245066 \tabularnewline
19 & -0.147002 & -1.1387 & 0.129683 \tabularnewline
20 & -0.148233 & -1.1482 & 0.12772 \tabularnewline
21 & -0.055308 & -0.4284 & 0.334941 \tabularnewline
22 & -0.090401 & -0.7002 & 0.24324 \tabularnewline
23 & -0.181918 & -1.4091 & 0.081979 \tabularnewline
24 & -0.077041 & -0.5968 & 0.276458 \tabularnewline
25 & -0.073349 & -0.5682 & 0.286023 \tabularnewline
26 & -0.111904 & -0.8668 & 0.194752 \tabularnewline
27 & -0.137161 & -1.0624 & 0.146146 \tabularnewline
28 & -0.160431 & -1.2427 & 0.109407 \tabularnewline
29 & -0.119554 & -0.9261 & 0.179062 \tabularnewline
30 & -0.130737 & -1.0127 & 0.157639 \tabularnewline
31 & -0.247009 & -1.9133 & 0.030241 \tabularnewline
32 & -0.209858 & -1.6256 & 0.054643 \tabularnewline
33 & -0.141352 & -1.0949 & 0.138967 \tabularnewline
34 & -0.202231 & -1.5665 & 0.061248 \tabularnewline
35 & -0.226513 & -1.7546 & 0.04222 \tabularnewline
36 & -0.156043 & -1.2087 & 0.115759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59226&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]0.375451[/C][C]2.9082[/C][C]0.002545[/C][/ROW]
[ROW][C]2[/C][C]0.352637[/C][C]2.7315[/C][C]0.004134[/C][/ROW]
[ROW][C]3[/C][C]0.485718[/C][C]3.7624[/C][C]0.000192[/C][/ROW]
[ROW][C]4[/C][C]0.341448[/C][C]2.6448[/C][C]0.005208[/C][/ROW]
[ROW][C]5[/C][C]0.26575[/C][C]2.0585[/C][C]0.021947[/C][/ROW]
[ROW][C]6[/C][C]0.226448[/C][C]1.7541[/C][C]0.042263[/C][/ROW]
[ROW][C]7[/C][C]0.246601[/C][C]1.9102[/C][C]0.030448[/C][/ROW]
[ROW][C]8[/C][C]0.185483[/C][C]1.4367[/C][C]0.077992[/C][/ROW]
[ROW][C]9[/C][C]0.168799[/C][C]1.3075[/C][C]0.098014[/C][/ROW]
[ROW][C]10[/C][C]0.170583[/C][C]1.3213[/C][C]0.095704[/C][/ROW]
[ROW][C]11[/C][C]-0.043804[/C][C]-0.3393[/C][C]0.367783[/C][/ROW]
[ROW][C]12[/C][C]0.178288[/C][C]1.381[/C][C]0.086199[/C][/ROW]
[ROW][C]13[/C][C]0.046311[/C][C]0.3587[/C][C]0.360531[/C][/ROW]
[ROW][C]14[/C][C]-0.030149[/C][C]-0.2335[/C][C]0.408071[/C][/ROW]
[ROW][C]15[/C][C]-0.038322[/C][C]-0.2968[/C][C]0.383808[/C][/ROW]
[ROW][C]16[/C][C]-0.070069[/C][C]-0.5428[/C][C]0.294656[/C][/ROW]
[ROW][C]17[/C][C]-0.05425[/C][C]-0.4202[/C][C]0.337914[/C][/ROW]
[ROW][C]18[/C][C]-0.089643[/C][C]-0.6944[/C][C]0.245066[/C][/ROW]
[ROW][C]19[/C][C]-0.147002[/C][C]-1.1387[/C][C]0.129683[/C][/ROW]
[ROW][C]20[/C][C]-0.148233[/C][C]-1.1482[/C][C]0.12772[/C][/ROW]
[ROW][C]21[/C][C]-0.055308[/C][C]-0.4284[/C][C]0.334941[/C][/ROW]
[ROW][C]22[/C][C]-0.090401[/C][C]-0.7002[/C][C]0.24324[/C][/ROW]
[ROW][C]23[/C][C]-0.181918[/C][C]-1.4091[/C][C]0.081979[/C][/ROW]
[ROW][C]24[/C][C]-0.077041[/C][C]-0.5968[/C][C]0.276458[/C][/ROW]
[ROW][C]25[/C][C]-0.073349[/C][C]-0.5682[/C][C]0.286023[/C][/ROW]
[ROW][C]26[/C][C]-0.111904[/C][C]-0.8668[/C][C]0.194752[/C][/ROW]
[ROW][C]27[/C][C]-0.137161[/C][C]-1.0624[/C][C]0.146146[/C][/ROW]
[ROW][C]28[/C][C]-0.160431[/C][C]-1.2427[/C][C]0.109407[/C][/ROW]
[ROW][C]29[/C][C]-0.119554[/C][C]-0.9261[/C][C]0.179062[/C][/ROW]
[ROW][C]30[/C][C]-0.130737[/C][C]-1.0127[/C][C]0.157639[/C][/ROW]
[ROW][C]31[/C][C]-0.247009[/C][C]-1.9133[/C][C]0.030241[/C][/ROW]
[ROW][C]32[/C][C]-0.209858[/C][C]-1.6256[/C][C]0.054643[/C][/ROW]
[ROW][C]33[/C][C]-0.141352[/C][C]-1.0949[/C][C]0.138967[/C][/ROW]
[ROW][C]34[/C][C]-0.202231[/C][C]-1.5665[/C][C]0.061248[/C][/ROW]
[ROW][C]35[/C][C]-0.226513[/C][C]-1.7546[/C][C]0.04222[/C][/ROW]
[ROW][C]36[/C][C]-0.156043[/C][C]-1.2087[/C][C]0.115759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59226&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
10.3754512.90820.002545
20.3526372.73150.004134
30.4857183.76240.000192
40.3414482.64480.005208
50.265752.05850.021947
60.2264481.75410.042263
70.2466011.91020.030448
80.1854831.43670.077992
90.1687991.30750.098014
100.1705831.32130.095704
11-0.043804-0.33930.367783
120.1782881.3810.086199
130.0463110.35870.360531
14-0.030149-0.23350.408071
15-0.038322-0.29680.383808
16-0.070069-0.54280.294656
17-0.05425-0.42020.337914
18-0.089643-0.69440.245066
19-0.147002-1.13870.129683
20-0.148233-1.14820.12772
21-0.055308-0.42840.334941
22-0.090401-0.70020.24324
23-0.181918-1.40910.081979
24-0.077041-0.59680.276458
25-0.073349-0.56820.286023
26-0.111904-0.86680.194752
27-0.137161-1.06240.146146
28-0.160431-1.24270.109407
29-0.119554-0.92610.179062
30-0.130737-1.01270.157639
31-0.247009-1.91330.030241
32-0.209858-1.62560.054643
33-0.141352-1.09490.138967
34-0.202231-1.56650.061248
35-0.226513-1.75460.04222
36-0.156043-1.20870.115759







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3754512.90820.002545
20.2464081.90870.030546
30.3636612.81690.003277
40.0862640.66820.253285
5-0.0115-0.08910.464658
6-0.08494-0.65790.256547
70.0371250.28760.387334
80.0048570.03760.485055
90.0392610.30410.381046
100.0194230.15040.440458
11-0.265568-2.05710.022017
120.1715371.32870.094486
13-0.072399-0.56080.288511
140.014130.10950.456604
15-0.154562-1.19720.117962
16-0.079603-0.61660.269914
17-0.002265-0.01750.49303
180.0590660.45750.324473
19-0.07667-0.59390.277411
20-0.083403-0.6460.260361
210.1263720.97890.165787
22-0.029152-0.22580.411057
230.0452770.35070.363516
24-0.05211-0.40360.343955
250.0293840.22760.410364
26-0.028963-0.22430.411626
27-0.042894-0.33230.370427
28-0.105477-0.8170.208574
29-0.00737-0.05710.477332
30-0.025856-0.20030.420971
31-0.203032-1.57270.060526
320.0108510.08410.466646
33-0.026909-0.20840.417798
34-0.014466-0.11210.455577
35-0.0617-0.47790.317219
360.0389190.30150.382052

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375451 & 2.9082 & 0.002545 \tabularnewline
2 & 0.246408 & 1.9087 & 0.030546 \tabularnewline
3 & 0.363661 & 2.8169 & 0.003277 \tabularnewline
4 & 0.086264 & 0.6682 & 0.253285 \tabularnewline
5 & -0.0115 & -0.0891 & 0.464658 \tabularnewline
6 & -0.08494 & -0.6579 & 0.256547 \tabularnewline
7 & 0.037125 & 0.2876 & 0.387334 \tabularnewline
8 & 0.004857 & 0.0376 & 0.485055 \tabularnewline
9 & 0.039261 & 0.3041 & 0.381046 \tabularnewline
10 & 0.019423 & 0.1504 & 0.440458 \tabularnewline
11 & -0.265568 & -2.0571 & 0.022017 \tabularnewline
12 & 0.171537 & 1.3287 & 0.094486 \tabularnewline
13 & -0.072399 & -0.5608 & 0.288511 \tabularnewline
14 & 0.01413 & 0.1095 & 0.456604 \tabularnewline
15 & -0.154562 & -1.1972 & 0.117962 \tabularnewline
16 & -0.079603 & -0.6166 & 0.269914 \tabularnewline
17 & -0.002265 & -0.0175 & 0.49303 \tabularnewline
18 & 0.059066 & 0.4575 & 0.324473 \tabularnewline
19 & -0.07667 & -0.5939 & 0.277411 \tabularnewline
20 & -0.083403 & -0.646 & 0.260361 \tabularnewline
21 & 0.126372 & 0.9789 & 0.165787 \tabularnewline
22 & -0.029152 & -0.2258 & 0.411057 \tabularnewline
23 & 0.045277 & 0.3507 & 0.363516 \tabularnewline
24 & -0.05211 & -0.4036 & 0.343955 \tabularnewline
25 & 0.029384 & 0.2276 & 0.410364 \tabularnewline
26 & -0.028963 & -0.2243 & 0.411626 \tabularnewline
27 & -0.042894 & -0.3323 & 0.370427 \tabularnewline
28 & -0.105477 & -0.817 & 0.208574 \tabularnewline
29 & -0.00737 & -0.0571 & 0.477332 \tabularnewline
30 & -0.025856 & -0.2003 & 0.420971 \tabularnewline
31 & -0.203032 & -1.5727 & 0.060526 \tabularnewline
32 & 0.010851 & 0.0841 & 0.466646 \tabularnewline
33 & -0.026909 & -0.2084 & 0.417798 \tabularnewline
34 & -0.014466 & -0.1121 & 0.455577 \tabularnewline
35 & -0.0617 & -0.4779 & 0.317219 \tabularnewline
36 & 0.038919 & 0.3015 & 0.382052 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59226&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]0.375451[/C][C]2.9082[/C][C]0.002545[/C][/ROW]
[ROW][C]2[/C][C]0.246408[/C][C]1.9087[/C][C]0.030546[/C][/ROW]
[ROW][C]3[/C][C]0.363661[/C][C]2.8169[/C][C]0.003277[/C][/ROW]
[ROW][C]4[/C][C]0.086264[/C][C]0.6682[/C][C]0.253285[/C][/ROW]
[ROW][C]5[/C][C]-0.0115[/C][C]-0.0891[/C][C]0.464658[/C][/ROW]
[ROW][C]6[/C][C]-0.08494[/C][C]-0.6579[/C][C]0.256547[/C][/ROW]
[ROW][C]7[/C][C]0.037125[/C][C]0.2876[/C][C]0.387334[/C][/ROW]
[ROW][C]8[/C][C]0.004857[/C][C]0.0376[/C][C]0.485055[/C][/ROW]
[ROW][C]9[/C][C]0.039261[/C][C]0.3041[/C][C]0.381046[/C][/ROW]
[ROW][C]10[/C][C]0.019423[/C][C]0.1504[/C][C]0.440458[/C][/ROW]
[ROW][C]11[/C][C]-0.265568[/C][C]-2.0571[/C][C]0.022017[/C][/ROW]
[ROW][C]12[/C][C]0.171537[/C][C]1.3287[/C][C]0.094486[/C][/ROW]
[ROW][C]13[/C][C]-0.072399[/C][C]-0.5608[/C][C]0.288511[/C][/ROW]
[ROW][C]14[/C][C]0.01413[/C][C]0.1095[/C][C]0.456604[/C][/ROW]
[ROW][C]15[/C][C]-0.154562[/C][C]-1.1972[/C][C]0.117962[/C][/ROW]
[ROW][C]16[/C][C]-0.079603[/C][C]-0.6166[/C][C]0.269914[/C][/ROW]
[ROW][C]17[/C][C]-0.002265[/C][C]-0.0175[/C][C]0.49303[/C][/ROW]
[ROW][C]18[/C][C]0.059066[/C][C]0.4575[/C][C]0.324473[/C][/ROW]
[ROW][C]19[/C][C]-0.07667[/C][C]-0.5939[/C][C]0.277411[/C][/ROW]
[ROW][C]20[/C][C]-0.083403[/C][C]-0.646[/C][C]0.260361[/C][/ROW]
[ROW][C]21[/C][C]0.126372[/C][C]0.9789[/C][C]0.165787[/C][/ROW]
[ROW][C]22[/C][C]-0.029152[/C][C]-0.2258[/C][C]0.411057[/C][/ROW]
[ROW][C]23[/C][C]0.045277[/C][C]0.3507[/C][C]0.363516[/C][/ROW]
[ROW][C]24[/C][C]-0.05211[/C][C]-0.4036[/C][C]0.343955[/C][/ROW]
[ROW][C]25[/C][C]0.029384[/C][C]0.2276[/C][C]0.410364[/C][/ROW]
[ROW][C]26[/C][C]-0.028963[/C][C]-0.2243[/C][C]0.411626[/C][/ROW]
[ROW][C]27[/C][C]-0.042894[/C][C]-0.3323[/C][C]0.370427[/C][/ROW]
[ROW][C]28[/C][C]-0.105477[/C][C]-0.817[/C][C]0.208574[/C][/ROW]
[ROW][C]29[/C][C]-0.00737[/C][C]-0.0571[/C][C]0.477332[/C][/ROW]
[ROW][C]30[/C][C]-0.025856[/C][C]-0.2003[/C][C]0.420971[/C][/ROW]
[ROW][C]31[/C][C]-0.203032[/C][C]-1.5727[/C][C]0.060526[/C][/ROW]
[ROW][C]32[/C][C]0.010851[/C][C]0.0841[/C][C]0.466646[/C][/ROW]
[ROW][C]33[/C][C]-0.026909[/C][C]-0.2084[/C][C]0.417798[/C][/ROW]
[ROW][C]34[/C][C]-0.014466[/C][C]-0.1121[/C][C]0.455577[/C][/ROW]
[ROW][C]35[/C][C]-0.0617[/C][C]-0.4779[/C][C]0.317219[/C][/ROW]
[ROW][C]36[/C][C]0.038919[/C][C]0.3015[/C][C]0.382052[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59226&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59226&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
10.3754512.90820.002545
20.2464081.90870.030546
30.3636612.81690.003277
40.0862640.66820.253285
5-0.0115-0.08910.464658
6-0.08494-0.65790.256547
70.0371250.28760.387334
80.0048570.03760.485055
90.0392610.30410.381046
100.0194230.15040.440458
11-0.265568-2.05710.022017
120.1715371.32870.094486
13-0.072399-0.56080.288511
140.014130.10950.456604
15-0.154562-1.19720.117962
16-0.079603-0.61660.269914
17-0.002265-0.01750.49303
180.0590660.45750.324473
19-0.07667-0.59390.277411
20-0.083403-0.6460.260361
210.1263720.97890.165787
22-0.029152-0.22580.411057
230.0452770.35070.363516
24-0.05211-0.40360.343955
250.0293840.22760.410364
26-0.028963-0.22430.411626
27-0.042894-0.33230.370427
28-0.105477-0.8170.208574
29-0.00737-0.05710.477332
30-0.025856-0.20030.420971
31-0.203032-1.57270.060526
320.0108510.08410.466646
33-0.026909-0.20840.417798
34-0.014466-0.11210.455577
35-0.0617-0.47790.317219
360.0389190.30150.382052



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')