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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 10:46:32 -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/t1259084845srgikf9iycb38y2.htm/, Retrieved Fri, 26 Apr 2024 03:00:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59183, Retrieved Fri, 26 Apr 2024 03:00:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177
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 12:26:39] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [Model 1 (d = 1, D...] [2009-11-24 17:46:32] [acc980be4047884b6edd254cd7beb9fa] [Current]
-   P             [(Partial) Autocorrelation Function] [Model 1 (d = 1, D...] [2009-12-10 17:28:06] [ee7c2e7343f5b1451e62c5c16ec521f1]
- R PD            [(Partial) Autocorrelation Function] [] [2009-12-19 15:27:46] [a3c75f2af6eea9d676b2dadad1cedbf1]
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Dataseries X:
8.2
8
7.5
6.8
6.5
6.6
7.6
8
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8
8.1
8




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=59183&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=59183&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59183&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
10.4219772.79910.00379
2-0.030915-0.20510.419234
3-0.364937-2.42070.009842
4-0.339817-2.25410.014611
5-0.105644-0.70080.243571
60.0790160.52410.301407
70.1489820.98820.164221
80.0477260.31660.376529
9-0.071988-0.47750.31768
10-0.084326-0.55940.289378
110.0478190.31720.376299
12-0.028434-0.18860.425634
130.0686220.45520.325606
140.0067480.04480.482251
15-0.032446-0.21520.415294
16-0.173012-1.14760.128661
17-0.195764-1.29850.100432
180.0145320.09640.461821
190.1227760.81440.209899
200.2672581.77280.041593
210.2094881.38960.085823
220.0226930.15050.440519
23-0.242536-1.60880.057406
24-0.275538-1.82770.03719
25-0.1486-0.98570.164834
26-0.008364-0.05550.478004
27-0.000343-0.00230.499098
280.0109620.07270.471182
290.0344870.22880.410058
30-0.000579-0.00380.498477
310.0562280.3730.355478
320.0346020.22950.409762
330.0347190.23030.409463
34-0.067404-0.44710.328495
35-0.082838-0.54950.292726
36-0.059102-0.3920.348461

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.421977 & 2.7991 & 0.00379 \tabularnewline
2 & -0.030915 & -0.2051 & 0.419234 \tabularnewline
3 & -0.364937 & -2.4207 & 0.009842 \tabularnewline
4 & -0.339817 & -2.2541 & 0.014611 \tabularnewline
5 & -0.105644 & -0.7008 & 0.243571 \tabularnewline
6 & 0.079016 & 0.5241 & 0.301407 \tabularnewline
7 & 0.148982 & 0.9882 & 0.164221 \tabularnewline
8 & 0.047726 & 0.3166 & 0.376529 \tabularnewline
9 & -0.071988 & -0.4775 & 0.31768 \tabularnewline
10 & -0.084326 & -0.5594 & 0.289378 \tabularnewline
11 & 0.047819 & 0.3172 & 0.376299 \tabularnewline
12 & -0.028434 & -0.1886 & 0.425634 \tabularnewline
13 & 0.068622 & 0.4552 & 0.325606 \tabularnewline
14 & 0.006748 & 0.0448 & 0.482251 \tabularnewline
15 & -0.032446 & -0.2152 & 0.415294 \tabularnewline
16 & -0.173012 & -1.1476 & 0.128661 \tabularnewline
17 & -0.195764 & -1.2985 & 0.100432 \tabularnewline
18 & 0.014532 & 0.0964 & 0.461821 \tabularnewline
19 & 0.122776 & 0.8144 & 0.209899 \tabularnewline
20 & 0.267258 & 1.7728 & 0.041593 \tabularnewline
21 & 0.209488 & 1.3896 & 0.085823 \tabularnewline
22 & 0.022693 & 0.1505 & 0.440519 \tabularnewline
23 & -0.242536 & -1.6088 & 0.057406 \tabularnewline
24 & -0.275538 & -1.8277 & 0.03719 \tabularnewline
25 & -0.1486 & -0.9857 & 0.164834 \tabularnewline
26 & -0.008364 & -0.0555 & 0.478004 \tabularnewline
27 & -0.000343 & -0.0023 & 0.499098 \tabularnewline
28 & 0.010962 & 0.0727 & 0.471182 \tabularnewline
29 & 0.034487 & 0.2288 & 0.410058 \tabularnewline
30 & -0.000579 & -0.0038 & 0.498477 \tabularnewline
31 & 0.056228 & 0.373 & 0.355478 \tabularnewline
32 & 0.034602 & 0.2295 & 0.409762 \tabularnewline
33 & 0.034719 & 0.2303 & 0.409463 \tabularnewline
34 & -0.067404 & -0.4471 & 0.328495 \tabularnewline
35 & -0.082838 & -0.5495 & 0.292726 \tabularnewline
36 & -0.059102 & -0.392 & 0.348461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59183&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]0.421977[/C][C]2.7991[/C][C]0.00379[/C][/ROW]
[ROW][C]2[/C][C]-0.030915[/C][C]-0.2051[/C][C]0.419234[/C][/ROW]
[ROW][C]3[/C][C]-0.364937[/C][C]-2.4207[/C][C]0.009842[/C][/ROW]
[ROW][C]4[/C][C]-0.339817[/C][C]-2.2541[/C][C]0.014611[/C][/ROW]
[ROW][C]5[/C][C]-0.105644[/C][C]-0.7008[/C][C]0.243571[/C][/ROW]
[ROW][C]6[/C][C]0.079016[/C][C]0.5241[/C][C]0.301407[/C][/ROW]
[ROW][C]7[/C][C]0.148982[/C][C]0.9882[/C][C]0.164221[/C][/ROW]
[ROW][C]8[/C][C]0.047726[/C][C]0.3166[/C][C]0.376529[/C][/ROW]
[ROW][C]9[/C][C]-0.071988[/C][C]-0.4775[/C][C]0.31768[/C][/ROW]
[ROW][C]10[/C][C]-0.084326[/C][C]-0.5594[/C][C]0.289378[/C][/ROW]
[ROW][C]11[/C][C]0.047819[/C][C]0.3172[/C][C]0.376299[/C][/ROW]
[ROW][C]12[/C][C]-0.028434[/C][C]-0.1886[/C][C]0.425634[/C][/ROW]
[ROW][C]13[/C][C]0.068622[/C][C]0.4552[/C][C]0.325606[/C][/ROW]
[ROW][C]14[/C][C]0.006748[/C][C]0.0448[/C][C]0.482251[/C][/ROW]
[ROW][C]15[/C][C]-0.032446[/C][C]-0.2152[/C][C]0.415294[/C][/ROW]
[ROW][C]16[/C][C]-0.173012[/C][C]-1.1476[/C][C]0.128661[/C][/ROW]
[ROW][C]17[/C][C]-0.195764[/C][C]-1.2985[/C][C]0.100432[/C][/ROW]
[ROW][C]18[/C][C]0.014532[/C][C]0.0964[/C][C]0.461821[/C][/ROW]
[ROW][C]19[/C][C]0.122776[/C][C]0.8144[/C][C]0.209899[/C][/ROW]
[ROW][C]20[/C][C]0.267258[/C][C]1.7728[/C][C]0.041593[/C][/ROW]
[ROW][C]21[/C][C]0.209488[/C][C]1.3896[/C][C]0.085823[/C][/ROW]
[ROW][C]22[/C][C]0.022693[/C][C]0.1505[/C][C]0.440519[/C][/ROW]
[ROW][C]23[/C][C]-0.242536[/C][C]-1.6088[/C][C]0.057406[/C][/ROW]
[ROW][C]24[/C][C]-0.275538[/C][C]-1.8277[/C][C]0.03719[/C][/ROW]
[ROW][C]25[/C][C]-0.1486[/C][C]-0.9857[/C][C]0.164834[/C][/ROW]
[ROW][C]26[/C][C]-0.008364[/C][C]-0.0555[/C][C]0.478004[/C][/ROW]
[ROW][C]27[/C][C]-0.000343[/C][C]-0.0023[/C][C]0.499098[/C][/ROW]
[ROW][C]28[/C][C]0.010962[/C][C]0.0727[/C][C]0.471182[/C][/ROW]
[ROW][C]29[/C][C]0.034487[/C][C]0.2288[/C][C]0.410058[/C][/ROW]
[ROW][C]30[/C][C]-0.000579[/C][C]-0.0038[/C][C]0.498477[/C][/ROW]
[ROW][C]31[/C][C]0.056228[/C][C]0.373[/C][C]0.355478[/C][/ROW]
[ROW][C]32[/C][C]0.034602[/C][C]0.2295[/C][C]0.409762[/C][/ROW]
[ROW][C]33[/C][C]0.034719[/C][C]0.2303[/C][C]0.409463[/C][/ROW]
[ROW][C]34[/C][C]-0.067404[/C][C]-0.4471[/C][C]0.328495[/C][/ROW]
[ROW][C]35[/C][C]-0.082838[/C][C]-0.5495[/C][C]0.292726[/C][/ROW]
[ROW][C]36[/C][C]-0.059102[/C][C]-0.392[/C][C]0.348461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59183&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59183&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
10.4219772.79910.00379
2-0.030915-0.20510.419234
3-0.364937-2.42070.009842
4-0.339817-2.25410.014611
5-0.105644-0.70080.243571
60.0790160.52410.301407
70.1489820.98820.164221
80.0477260.31660.376529
9-0.071988-0.47750.31768
10-0.084326-0.55940.289378
110.0478190.31720.376299
12-0.028434-0.18860.425634
130.0686220.45520.325606
140.0067480.04480.482251
15-0.032446-0.21520.415294
16-0.173012-1.14760.128661
17-0.195764-1.29850.100432
180.0145320.09640.461821
190.1227760.81440.209899
200.2672581.77280.041593
210.2094881.38960.085823
220.0226930.15050.440519
23-0.242536-1.60880.057406
24-0.275538-1.82770.03719
25-0.1486-0.98570.164834
26-0.008364-0.05550.478004
27-0.000343-0.00230.499098
280.0109620.07270.471182
290.0344870.22880.410058
30-0.000579-0.00380.498477
310.0562280.3730.355478
320.0346020.22950.409762
330.0347190.23030.409463
34-0.067404-0.44710.328495
35-0.082838-0.54950.292726
36-0.059102-0.3920.348461







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4219772.79910.00379
2-0.254252-1.68650.049387
3-0.313847-2.08180.021604
4-0.066484-0.4410.330685
50.0361930.24010.405694
6-0.034968-0.2320.408826
7-0.011112-0.07370.470789
8-0.070384-0.46690.321447
9-0.057618-0.38220.352079
100.0202140.13410.446974
110.1146480.76050.22551
12-0.210684-1.39750.084632
130.1467590.97350.167816
14-0.036393-0.24140.405181
15-0.055044-0.36510.358385
16-0.198594-1.31730.097274
17-0.0626-0.41520.339993
180.1328210.8810.191544
19-0.043078-0.28570.388207
200.1472580.97680.167004
210.0482920.32030.375117
22-0.049382-0.32760.372398
23-0.104804-0.69520.245296
24-0.055842-0.37040.356426
25-0.005141-0.03410.486475
26-0.16473-1.09270.140237
27-0.115705-0.76750.223442
28-0.038579-0.25590.39961
29-0.0162-0.10750.457457
30-0.016392-0.10870.456953
31-0.019671-0.13050.448391
32-0.024329-0.16140.436266
33-0.02683-0.1780.429781
34-0.047187-0.3130.377879
35-0.035962-0.23850.406283
36-0.053557-0.35530.362048

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.421977 & 2.7991 & 0.00379 \tabularnewline
2 & -0.254252 & -1.6865 & 0.049387 \tabularnewline
3 & -0.313847 & -2.0818 & 0.021604 \tabularnewline
4 & -0.066484 & -0.441 & 0.330685 \tabularnewline
5 & 0.036193 & 0.2401 & 0.405694 \tabularnewline
6 & -0.034968 & -0.232 & 0.408826 \tabularnewline
7 & -0.011112 & -0.0737 & 0.470789 \tabularnewline
8 & -0.070384 & -0.4669 & 0.321447 \tabularnewline
9 & -0.057618 & -0.3822 & 0.352079 \tabularnewline
10 & 0.020214 & 0.1341 & 0.446974 \tabularnewline
11 & 0.114648 & 0.7605 & 0.22551 \tabularnewline
12 & -0.210684 & -1.3975 & 0.084632 \tabularnewline
13 & 0.146759 & 0.9735 & 0.167816 \tabularnewline
14 & -0.036393 & -0.2414 & 0.405181 \tabularnewline
15 & -0.055044 & -0.3651 & 0.358385 \tabularnewline
16 & -0.198594 & -1.3173 & 0.097274 \tabularnewline
17 & -0.0626 & -0.4152 & 0.339993 \tabularnewline
18 & 0.132821 & 0.881 & 0.191544 \tabularnewline
19 & -0.043078 & -0.2857 & 0.388207 \tabularnewline
20 & 0.147258 & 0.9768 & 0.167004 \tabularnewline
21 & 0.048292 & 0.3203 & 0.375117 \tabularnewline
22 & -0.049382 & -0.3276 & 0.372398 \tabularnewline
23 & -0.104804 & -0.6952 & 0.245296 \tabularnewline
24 & -0.055842 & -0.3704 & 0.356426 \tabularnewline
25 & -0.005141 & -0.0341 & 0.486475 \tabularnewline
26 & -0.16473 & -1.0927 & 0.140237 \tabularnewline
27 & -0.115705 & -0.7675 & 0.223442 \tabularnewline
28 & -0.038579 & -0.2559 & 0.39961 \tabularnewline
29 & -0.0162 & -0.1075 & 0.457457 \tabularnewline
30 & -0.016392 & -0.1087 & 0.456953 \tabularnewline
31 & -0.019671 & -0.1305 & 0.448391 \tabularnewline
32 & -0.024329 & -0.1614 & 0.436266 \tabularnewline
33 & -0.02683 & -0.178 & 0.429781 \tabularnewline
34 & -0.047187 & -0.313 & 0.377879 \tabularnewline
35 & -0.035962 & -0.2385 & 0.406283 \tabularnewline
36 & -0.053557 & -0.3553 & 0.362048 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59183&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]0.421977[/C][C]2.7991[/C][C]0.00379[/C][/ROW]
[ROW][C]2[/C][C]-0.254252[/C][C]-1.6865[/C][C]0.049387[/C][/ROW]
[ROW][C]3[/C][C]-0.313847[/C][C]-2.0818[/C][C]0.021604[/C][/ROW]
[ROW][C]4[/C][C]-0.066484[/C][C]-0.441[/C][C]0.330685[/C][/ROW]
[ROW][C]5[/C][C]0.036193[/C][C]0.2401[/C][C]0.405694[/C][/ROW]
[ROW][C]6[/C][C]-0.034968[/C][C]-0.232[/C][C]0.408826[/C][/ROW]
[ROW][C]7[/C][C]-0.011112[/C][C]-0.0737[/C][C]0.470789[/C][/ROW]
[ROW][C]8[/C][C]-0.070384[/C][C]-0.4669[/C][C]0.321447[/C][/ROW]
[ROW][C]9[/C][C]-0.057618[/C][C]-0.3822[/C][C]0.352079[/C][/ROW]
[ROW][C]10[/C][C]0.020214[/C][C]0.1341[/C][C]0.446974[/C][/ROW]
[ROW][C]11[/C][C]0.114648[/C][C]0.7605[/C][C]0.22551[/C][/ROW]
[ROW][C]12[/C][C]-0.210684[/C][C]-1.3975[/C][C]0.084632[/C][/ROW]
[ROW][C]13[/C][C]0.146759[/C][C]0.9735[/C][C]0.167816[/C][/ROW]
[ROW][C]14[/C][C]-0.036393[/C][C]-0.2414[/C][C]0.405181[/C][/ROW]
[ROW][C]15[/C][C]-0.055044[/C][C]-0.3651[/C][C]0.358385[/C][/ROW]
[ROW][C]16[/C][C]-0.198594[/C][C]-1.3173[/C][C]0.097274[/C][/ROW]
[ROW][C]17[/C][C]-0.0626[/C][C]-0.4152[/C][C]0.339993[/C][/ROW]
[ROW][C]18[/C][C]0.132821[/C][C]0.881[/C][C]0.191544[/C][/ROW]
[ROW][C]19[/C][C]-0.043078[/C][C]-0.2857[/C][C]0.388207[/C][/ROW]
[ROW][C]20[/C][C]0.147258[/C][C]0.9768[/C][C]0.167004[/C][/ROW]
[ROW][C]21[/C][C]0.048292[/C][C]0.3203[/C][C]0.375117[/C][/ROW]
[ROW][C]22[/C][C]-0.049382[/C][C]-0.3276[/C][C]0.372398[/C][/ROW]
[ROW][C]23[/C][C]-0.104804[/C][C]-0.6952[/C][C]0.245296[/C][/ROW]
[ROW][C]24[/C][C]-0.055842[/C][C]-0.3704[/C][C]0.356426[/C][/ROW]
[ROW][C]25[/C][C]-0.005141[/C][C]-0.0341[/C][C]0.486475[/C][/ROW]
[ROW][C]26[/C][C]-0.16473[/C][C]-1.0927[/C][C]0.140237[/C][/ROW]
[ROW][C]27[/C][C]-0.115705[/C][C]-0.7675[/C][C]0.223442[/C][/ROW]
[ROW][C]28[/C][C]-0.038579[/C][C]-0.2559[/C][C]0.39961[/C][/ROW]
[ROW][C]29[/C][C]-0.0162[/C][C]-0.1075[/C][C]0.457457[/C][/ROW]
[ROW][C]30[/C][C]-0.016392[/C][C]-0.1087[/C][C]0.456953[/C][/ROW]
[ROW][C]31[/C][C]-0.019671[/C][C]-0.1305[/C][C]0.448391[/C][/ROW]
[ROW][C]32[/C][C]-0.024329[/C][C]-0.1614[/C][C]0.436266[/C][/ROW]
[ROW][C]33[/C][C]-0.02683[/C][C]-0.178[/C][C]0.429781[/C][/ROW]
[ROW][C]34[/C][C]-0.047187[/C][C]-0.313[/C][C]0.377879[/C][/ROW]
[ROW][C]35[/C][C]-0.035962[/C][C]-0.2385[/C][C]0.406283[/C][/ROW]
[ROW][C]36[/C][C]-0.053557[/C][C]-0.3553[/C][C]0.362048[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59183&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59183&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
10.4219772.79910.00379
2-0.254252-1.68650.049387
3-0.313847-2.08180.021604
4-0.066484-0.4410.330685
50.0361930.24010.405694
6-0.034968-0.2320.408826
7-0.011112-0.07370.470789
8-0.070384-0.46690.321447
9-0.057618-0.38220.352079
100.0202140.13410.446974
110.1146480.76050.22551
12-0.210684-1.39750.084632
130.1467590.97350.167816
14-0.036393-0.24140.405181
15-0.055044-0.36510.358385
16-0.198594-1.31730.097274
17-0.0626-0.41520.339993
180.1328210.8810.191544
19-0.043078-0.28570.388207
200.1472580.97680.167004
210.0482920.32030.375117
22-0.049382-0.32760.372398
23-0.104804-0.69520.245296
24-0.055842-0.37040.356426
25-0.005141-0.03410.486475
26-0.16473-1.09270.140237
27-0.115705-0.76750.223442
28-0.038579-0.25590.39961
29-0.0162-0.10750.457457
30-0.016392-0.10870.456953
31-0.019671-0.13050.448391
32-0.024329-0.16140.436266
33-0.02683-0.1780.429781
34-0.047187-0.3130.377879
35-0.035962-0.23850.406283
36-0.053557-0.35530.362048



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