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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 computationThu, 26 Nov 2009 02:49:31 -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/26/t1259229037g6hf2ssdz8hkbca.htm/, Retrieved Mon, 29 Apr 2024 03:54:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59740, Retrieved Mon, 29 Apr 2024 03:54:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
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] [] [2009-11-26 09:49:31] [b4088cbf8335906ce53a9289ed6fac01] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-26 14:51:36] [2f674a53c3d7aaa1bcf80e66074d3c9b]
- RMPD              [Variance Reduction Matrix] [] [2009-12-21 12:47:46] [8f79fe502d085bc4aad43092067387d5]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-26 14:56:20] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-26 15:00:23] [2f674a53c3d7aaa1bcf80e66074d3c9b]
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Dataseries X:
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
8.00
8.2
8.1
8.1
8.00
7.9
7.9
8.00
8.00
7.9
8.00
7.7
7.2
7.5
7.3
7.00
7.00
7.00
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
8.00
8.00
7.7
7.3
7.4
8.1
8.3
8.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59740&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]2 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=59740&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59740&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8534297.29170
20.5956555.08931e-06
30.4167893.5610.000327
40.4183743.57460.000313
50.5426394.63638e-06
60.6389825.45950
70.5994165.12141e-06
80.4697224.01337.2e-05
90.3587753.06540.001523
100.3393322.89930.002469
110.382673.26950.000822
120.4149113.5450.000345
130.3332182.8470.002863
140.2223071.89940.030732
150.1360951.16280.124349
160.0989680.84560.200273
170.0950270.81190.209742
180.0836670.71480.238491
190.0325940.27850.390713
20-0.031706-0.27090.393616
21-0.079816-0.6820.248714
22-0.098279-0.83970.201911
23-0.097328-0.83160.204182
24-0.099166-0.84730.199805
25-0.145578-1.24380.108772
26-0.179826-1.53640.064378
27-0.192706-1.64650.051982
28-0.187067-1.59830.057148
29-0.179672-1.53510.064539
30-0.188983-1.61470.055348
31-0.228375-1.95120.027433
32-0.277832-2.37380.010119
33-0.299856-2.5620.006236
34-0.281966-2.40910.009257
35-0.247223-2.11230.019042
36-0.227147-1.94070.028076

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.853429 & 7.2917 & 0 \tabularnewline
2 & 0.595655 & 5.0893 & 1e-06 \tabularnewline
3 & 0.416789 & 3.561 & 0.000327 \tabularnewline
4 & 0.418374 & 3.5746 & 0.000313 \tabularnewline
5 & 0.542639 & 4.6363 & 8e-06 \tabularnewline
6 & 0.638982 & 5.4595 & 0 \tabularnewline
7 & 0.599416 & 5.1214 & 1e-06 \tabularnewline
8 & 0.469722 & 4.0133 & 7.2e-05 \tabularnewline
9 & 0.358775 & 3.0654 & 0.001523 \tabularnewline
10 & 0.339332 & 2.8993 & 0.002469 \tabularnewline
11 & 0.38267 & 3.2695 & 0.000822 \tabularnewline
12 & 0.414911 & 3.545 & 0.000345 \tabularnewline
13 & 0.333218 & 2.847 & 0.002863 \tabularnewline
14 & 0.222307 & 1.8994 & 0.030732 \tabularnewline
15 & 0.136095 & 1.1628 & 0.124349 \tabularnewline
16 & 0.098968 & 0.8456 & 0.200273 \tabularnewline
17 & 0.095027 & 0.8119 & 0.209742 \tabularnewline
18 & 0.083667 & 0.7148 & 0.238491 \tabularnewline
19 & 0.032594 & 0.2785 & 0.390713 \tabularnewline
20 & -0.031706 & -0.2709 & 0.393616 \tabularnewline
21 & -0.079816 & -0.682 & 0.248714 \tabularnewline
22 & -0.098279 & -0.8397 & 0.201911 \tabularnewline
23 & -0.097328 & -0.8316 & 0.204182 \tabularnewline
24 & -0.099166 & -0.8473 & 0.199805 \tabularnewline
25 & -0.145578 & -1.2438 & 0.108772 \tabularnewline
26 & -0.179826 & -1.5364 & 0.064378 \tabularnewline
27 & -0.192706 & -1.6465 & 0.051982 \tabularnewline
28 & -0.187067 & -1.5983 & 0.057148 \tabularnewline
29 & -0.179672 & -1.5351 & 0.064539 \tabularnewline
30 & -0.188983 & -1.6147 & 0.055348 \tabularnewline
31 & -0.228375 & -1.9512 & 0.027433 \tabularnewline
32 & -0.277832 & -2.3738 & 0.010119 \tabularnewline
33 & -0.299856 & -2.562 & 0.006236 \tabularnewline
34 & -0.281966 & -2.4091 & 0.009257 \tabularnewline
35 & -0.247223 & -2.1123 & 0.019042 \tabularnewline
36 & -0.227147 & -1.9407 & 0.028076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59740&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]0.853429[/C][C]7.2917[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.595655[/C][C]5.0893[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.416789[/C][C]3.561[/C][C]0.000327[/C][/ROW]
[ROW][C]4[/C][C]0.418374[/C][C]3.5746[/C][C]0.000313[/C][/ROW]
[ROW][C]5[/C][C]0.542639[/C][C]4.6363[/C][C]8e-06[/C][/ROW]
[ROW][C]6[/C][C]0.638982[/C][C]5.4595[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.599416[/C][C]5.1214[/C][C]1e-06[/C][/ROW]
[ROW][C]8[/C][C]0.469722[/C][C]4.0133[/C][C]7.2e-05[/C][/ROW]
[ROW][C]9[/C][C]0.358775[/C][C]3.0654[/C][C]0.001523[/C][/ROW]
[ROW][C]10[/C][C]0.339332[/C][C]2.8993[/C][C]0.002469[/C][/ROW]
[ROW][C]11[/C][C]0.38267[/C][C]3.2695[/C][C]0.000822[/C][/ROW]
[ROW][C]12[/C][C]0.414911[/C][C]3.545[/C][C]0.000345[/C][/ROW]
[ROW][C]13[/C][C]0.333218[/C][C]2.847[/C][C]0.002863[/C][/ROW]
[ROW][C]14[/C][C]0.222307[/C][C]1.8994[/C][C]0.030732[/C][/ROW]
[ROW][C]15[/C][C]0.136095[/C][C]1.1628[/C][C]0.124349[/C][/ROW]
[ROW][C]16[/C][C]0.098968[/C][C]0.8456[/C][C]0.200273[/C][/ROW]
[ROW][C]17[/C][C]0.095027[/C][C]0.8119[/C][C]0.209742[/C][/ROW]
[ROW][C]18[/C][C]0.083667[/C][C]0.7148[/C][C]0.238491[/C][/ROW]
[ROW][C]19[/C][C]0.032594[/C][C]0.2785[/C][C]0.390713[/C][/ROW]
[ROW][C]20[/C][C]-0.031706[/C][C]-0.2709[/C][C]0.393616[/C][/ROW]
[ROW][C]21[/C][C]-0.079816[/C][C]-0.682[/C][C]0.248714[/C][/ROW]
[ROW][C]22[/C][C]-0.098279[/C][C]-0.8397[/C][C]0.201911[/C][/ROW]
[ROW][C]23[/C][C]-0.097328[/C][C]-0.8316[/C][C]0.204182[/C][/ROW]
[ROW][C]24[/C][C]-0.099166[/C][C]-0.8473[/C][C]0.199805[/C][/ROW]
[ROW][C]25[/C][C]-0.145578[/C][C]-1.2438[/C][C]0.108772[/C][/ROW]
[ROW][C]26[/C][C]-0.179826[/C][C]-1.5364[/C][C]0.064378[/C][/ROW]
[ROW][C]27[/C][C]-0.192706[/C][C]-1.6465[/C][C]0.051982[/C][/ROW]
[ROW][C]28[/C][C]-0.187067[/C][C]-1.5983[/C][C]0.057148[/C][/ROW]
[ROW][C]29[/C][C]-0.179672[/C][C]-1.5351[/C][C]0.064539[/C][/ROW]
[ROW][C]30[/C][C]-0.188983[/C][C]-1.6147[/C][C]0.055348[/C][/ROW]
[ROW][C]31[/C][C]-0.228375[/C][C]-1.9512[/C][C]0.027433[/C][/ROW]
[ROW][C]32[/C][C]-0.277832[/C][C]-2.3738[/C][C]0.010119[/C][/ROW]
[ROW][C]33[/C][C]-0.299856[/C][C]-2.562[/C][C]0.006236[/C][/ROW]
[ROW][C]34[/C][C]-0.281966[/C][C]-2.4091[/C][C]0.009257[/C][/ROW]
[ROW][C]35[/C][C]-0.247223[/C][C]-2.1123[/C][C]0.019042[/C][/ROW]
[ROW][C]36[/C][C]-0.227147[/C][C]-1.9407[/C][C]0.028076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59740&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59740&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
10.8534297.29170
20.5956555.08931e-06
30.4167893.5610.000327
40.4183743.57460.000313
50.5426394.63638e-06
60.6389825.45950
70.5994165.12141e-06
80.4697224.01337.2e-05
90.3587753.06540.001523
100.3393322.89930.002469
110.382673.26950.000822
120.4149113.5450.000345
130.3332182.8470.002863
140.2223071.89940.030732
150.1360951.16280.124349
160.0989680.84560.200273
170.0950270.81190.209742
180.0836670.71480.238491
190.0325940.27850.390713
20-0.031706-0.27090.393616
21-0.079816-0.6820.248714
22-0.098279-0.83970.201911
23-0.097328-0.83160.204182
24-0.099166-0.84730.199805
25-0.145578-1.24380.108772
26-0.179826-1.53640.064378
27-0.192706-1.64650.051982
28-0.187067-1.59830.057148
29-0.179672-1.53510.064539
30-0.188983-1.61470.055348
31-0.228375-1.95120.027433
32-0.277832-2.37380.010119
33-0.299856-2.5620.006236
34-0.281966-2.40910.009257
35-0.247223-2.11230.019042
36-0.227147-1.94070.028076







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8534297.29170
2-0.488435-4.17324.1e-05
30.37223.18010.001081
40.3820713.26440.000836
50.1634871.39680.083347
6-0.039243-0.33530.369183
7-0.107199-0.91590.181365
80.1113340.95120.172311
90.0344430.29430.384688
10-0.016052-0.13710.445646
11-0.085415-0.72980.233928
12-0.002185-0.01870.492577
13-0.36087-3.08330.001445
140.3180442.71740.004107
15-0.308133-2.63270.005166
16-0.151802-1.2970.099359
17-0.026229-0.22410.411652
18-0.00589-0.05030.48
19-0.069476-0.59360.277307
20-0.057101-0.48790.313553
210.0001260.00110.499573
22-0.004374-0.03740.485146
230.1091910.93290.176965
24-0.103553-0.88480.189597
250.0830890.70990.240011
260.0628720.53720.296388
270.0477510.4080.342241
280.0480790.41080.341218
29-0.036406-0.31110.378324
300.0057550.04920.48046
31-0.067319-0.57520.283472
32-0.114516-0.97840.165548
330.0591720.50560.307342
34-0.041133-0.35140.363134
35-0.149251-1.27520.103141
36-0.005605-0.04790.480966

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.853429 & 7.2917 & 0 \tabularnewline
2 & -0.488435 & -4.1732 & 4.1e-05 \tabularnewline
3 & 0.3722 & 3.1801 & 0.001081 \tabularnewline
4 & 0.382071 & 3.2644 & 0.000836 \tabularnewline
5 & 0.163487 & 1.3968 & 0.083347 \tabularnewline
6 & -0.039243 & -0.3353 & 0.369183 \tabularnewline
7 & -0.107199 & -0.9159 & 0.181365 \tabularnewline
8 & 0.111334 & 0.9512 & 0.172311 \tabularnewline
9 & 0.034443 & 0.2943 & 0.384688 \tabularnewline
10 & -0.016052 & -0.1371 & 0.445646 \tabularnewline
11 & -0.085415 & -0.7298 & 0.233928 \tabularnewline
12 & -0.002185 & -0.0187 & 0.492577 \tabularnewline
13 & -0.36087 & -3.0833 & 0.001445 \tabularnewline
14 & 0.318044 & 2.7174 & 0.004107 \tabularnewline
15 & -0.308133 & -2.6327 & 0.005166 \tabularnewline
16 & -0.151802 & -1.297 & 0.099359 \tabularnewline
17 & -0.026229 & -0.2241 & 0.411652 \tabularnewline
18 & -0.00589 & -0.0503 & 0.48 \tabularnewline
19 & -0.069476 & -0.5936 & 0.277307 \tabularnewline
20 & -0.057101 & -0.4879 & 0.313553 \tabularnewline
21 & 0.000126 & 0.0011 & 0.499573 \tabularnewline
22 & -0.004374 & -0.0374 & 0.485146 \tabularnewline
23 & 0.109191 & 0.9329 & 0.176965 \tabularnewline
24 & -0.103553 & -0.8848 & 0.189597 \tabularnewline
25 & 0.083089 & 0.7099 & 0.240011 \tabularnewline
26 & 0.062872 & 0.5372 & 0.296388 \tabularnewline
27 & 0.047751 & 0.408 & 0.342241 \tabularnewline
28 & 0.048079 & 0.4108 & 0.341218 \tabularnewline
29 & -0.036406 & -0.3111 & 0.378324 \tabularnewline
30 & 0.005755 & 0.0492 & 0.48046 \tabularnewline
31 & -0.067319 & -0.5752 & 0.283472 \tabularnewline
32 & -0.114516 & -0.9784 & 0.165548 \tabularnewline
33 & 0.059172 & 0.5056 & 0.307342 \tabularnewline
34 & -0.041133 & -0.3514 & 0.363134 \tabularnewline
35 & -0.149251 & -1.2752 & 0.103141 \tabularnewline
36 & -0.005605 & -0.0479 & 0.480966 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59740&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]0.853429[/C][C]7.2917[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.488435[/C][C]-4.1732[/C][C]4.1e-05[/C][/ROW]
[ROW][C]3[/C][C]0.3722[/C][C]3.1801[/C][C]0.001081[/C][/ROW]
[ROW][C]4[/C][C]0.382071[/C][C]3.2644[/C][C]0.000836[/C][/ROW]
[ROW][C]5[/C][C]0.163487[/C][C]1.3968[/C][C]0.083347[/C][/ROW]
[ROW][C]6[/C][C]-0.039243[/C][C]-0.3353[/C][C]0.369183[/C][/ROW]
[ROW][C]7[/C][C]-0.107199[/C][C]-0.9159[/C][C]0.181365[/C][/ROW]
[ROW][C]8[/C][C]0.111334[/C][C]0.9512[/C][C]0.172311[/C][/ROW]
[ROW][C]9[/C][C]0.034443[/C][C]0.2943[/C][C]0.384688[/C][/ROW]
[ROW][C]10[/C][C]-0.016052[/C][C]-0.1371[/C][C]0.445646[/C][/ROW]
[ROW][C]11[/C][C]-0.085415[/C][C]-0.7298[/C][C]0.233928[/C][/ROW]
[ROW][C]12[/C][C]-0.002185[/C][C]-0.0187[/C][C]0.492577[/C][/ROW]
[ROW][C]13[/C][C]-0.36087[/C][C]-3.0833[/C][C]0.001445[/C][/ROW]
[ROW][C]14[/C][C]0.318044[/C][C]2.7174[/C][C]0.004107[/C][/ROW]
[ROW][C]15[/C][C]-0.308133[/C][C]-2.6327[/C][C]0.005166[/C][/ROW]
[ROW][C]16[/C][C]-0.151802[/C][C]-1.297[/C][C]0.099359[/C][/ROW]
[ROW][C]17[/C][C]-0.026229[/C][C]-0.2241[/C][C]0.411652[/C][/ROW]
[ROW][C]18[/C][C]-0.00589[/C][C]-0.0503[/C][C]0.48[/C][/ROW]
[ROW][C]19[/C][C]-0.069476[/C][C]-0.5936[/C][C]0.277307[/C][/ROW]
[ROW][C]20[/C][C]-0.057101[/C][C]-0.4879[/C][C]0.313553[/C][/ROW]
[ROW][C]21[/C][C]0.000126[/C][C]0.0011[/C][C]0.499573[/C][/ROW]
[ROW][C]22[/C][C]-0.004374[/C][C]-0.0374[/C][C]0.485146[/C][/ROW]
[ROW][C]23[/C][C]0.109191[/C][C]0.9329[/C][C]0.176965[/C][/ROW]
[ROW][C]24[/C][C]-0.103553[/C][C]-0.8848[/C][C]0.189597[/C][/ROW]
[ROW][C]25[/C][C]0.083089[/C][C]0.7099[/C][C]0.240011[/C][/ROW]
[ROW][C]26[/C][C]0.062872[/C][C]0.5372[/C][C]0.296388[/C][/ROW]
[ROW][C]27[/C][C]0.047751[/C][C]0.408[/C][C]0.342241[/C][/ROW]
[ROW][C]28[/C][C]0.048079[/C][C]0.4108[/C][C]0.341218[/C][/ROW]
[ROW][C]29[/C][C]-0.036406[/C][C]-0.3111[/C][C]0.378324[/C][/ROW]
[ROW][C]30[/C][C]0.005755[/C][C]0.0492[/C][C]0.48046[/C][/ROW]
[ROW][C]31[/C][C]-0.067319[/C][C]-0.5752[/C][C]0.283472[/C][/ROW]
[ROW][C]32[/C][C]-0.114516[/C][C]-0.9784[/C][C]0.165548[/C][/ROW]
[ROW][C]33[/C][C]0.059172[/C][C]0.5056[/C][C]0.307342[/C][/ROW]
[ROW][C]34[/C][C]-0.041133[/C][C]-0.3514[/C][C]0.363134[/C][/ROW]
[ROW][C]35[/C][C]-0.149251[/C][C]-1.2752[/C][C]0.103141[/C][/ROW]
[ROW][C]36[/C][C]-0.005605[/C][C]-0.0479[/C][C]0.480966[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59740&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59740&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
10.8534297.29170
2-0.488435-4.17324.1e-05
30.37223.18010.001081
40.3820713.26440.000836
50.1634871.39680.083347
6-0.039243-0.33530.369183
7-0.107199-0.91590.181365
80.1113340.95120.172311
90.0344430.29430.384688
10-0.016052-0.13710.445646
11-0.085415-0.72980.233928
12-0.002185-0.01870.492577
13-0.36087-3.08330.001445
140.3180442.71740.004107
15-0.308133-2.63270.005166
16-0.151802-1.2970.099359
17-0.026229-0.22410.411652
18-0.00589-0.05030.48
19-0.069476-0.59360.277307
20-0.057101-0.48790.313553
210.0001260.00110.499573
22-0.004374-0.03740.485146
230.1091910.93290.176965
24-0.103553-0.88480.189597
250.0830890.70990.240011
260.0628720.53720.296388
270.0477510.4080.342241
280.0480790.41080.341218
29-0.036406-0.31110.378324
300.0057550.04920.48046
31-0.067319-0.57520.283472
32-0.114516-0.97840.165548
330.0591720.50560.307342
34-0.041133-0.35140.363134
35-0.149251-1.27520.103141
36-0.005605-0.04790.480966



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')