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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 07:29:58 -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/t1261405870ia40vw77pg7972e.htm/, Retrieved Thu, 31 Oct 2024 22:57:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70199, Retrieved Thu, 31 Oct 2024 22:57:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsShw; Paper; toepassing ACF d = 1 & D = 0
Estimated Impact210
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] [Ws8.1 ACF1] [2009-11-25 19:12:20] [e0fc65a5811681d807296d590d5b45de]
-    D          [(Partial) Autocorrelation Function] [Paper stationair ...] [2009-12-19 17:48:37] [e0fc65a5811681d807296d590d5b45de]
-   PD              [(Partial) Autocorrelation Function] [Paper; toepassing...] [2009-12-21 14:29:58] [51108381f3361ca8af49c4f74052c840] [Current]
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Dataseries X:
103.1
103.1
103.3
103.5
103.3
103.5
103.8
103.9
103.9
104.2
104.6
104.9
105.2
105.2
105.6
105.6
106.2
106.3
106.4
106.9
107.2
107.3
107.3
107.4
107.55
107.87
108.37
108.38
107.92
108.03
108.14
108.3
108.64
108.66
109.04
109.03
109.03
109.54
109.75
109.83
109.65
109.82
109.95
110.12
110.15
110.2
109.99
110.14
110.14
110.81
110.97
110.99
109.73
109.81
110.02
110.18
110.21
110.25
110.36
110.51
110.64
110.95
111.18
111.19
111.69
111.7
111.83
111.77
111.73
112.01
111.86
112.04




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=70199&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=70199&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70199&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
10.0080780.06810.472963
2-0.071394-0.60160.274687
3-0.224178-1.8890.031491
40.0399850.33690.368585
50.1215921.02460.154526
60.1209371.0190.155824
70.0772690.65110.258549
8-0.007411-0.06240.475192
9-0.180627-1.5220.066227
10-0.008945-0.07540.470067
110.0676530.57010.285219
120.0228090.19220.424071
130.0742070.62530.266896
14-0.096184-0.81050.210192
15-0.00287-0.02420.490387
160.044990.37910.352874
170.0388730.32750.372108
180.0371710.31320.377519
19-0.061243-0.5160.303714
20-0.041908-0.35310.362521
21-0.11152-0.93970.175283
22-0.025384-0.21390.415624
230.1019190.85880.196674
240.2204611.85760.033684
250.0265860.2240.411694
26-0.168152-1.41690.080446
27-0.011194-0.09430.46256
28-0.002577-0.02170.491367
290.008650.07290.471051
300.0285070.24020.405433
31-0.013638-0.11490.454418
32-0.037268-0.3140.37721
33-0.143872-1.21230.11471
34-0.054768-0.46150.322933
350.0699470.58940.278737
36-0.222573-1.87540.032423

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.008078 & 0.0681 & 0.472963 \tabularnewline
2 & -0.071394 & -0.6016 & 0.274687 \tabularnewline
3 & -0.224178 & -1.889 & 0.031491 \tabularnewline
4 & 0.039985 & 0.3369 & 0.368585 \tabularnewline
5 & 0.121592 & 1.0246 & 0.154526 \tabularnewline
6 & 0.120937 & 1.019 & 0.155824 \tabularnewline
7 & 0.077269 & 0.6511 & 0.258549 \tabularnewline
8 & -0.007411 & -0.0624 & 0.475192 \tabularnewline
9 & -0.180627 & -1.522 & 0.066227 \tabularnewline
10 & -0.008945 & -0.0754 & 0.470067 \tabularnewline
11 & 0.067653 & 0.5701 & 0.285219 \tabularnewline
12 & 0.022809 & 0.1922 & 0.424071 \tabularnewline
13 & 0.074207 & 0.6253 & 0.266896 \tabularnewline
14 & -0.096184 & -0.8105 & 0.210192 \tabularnewline
15 & -0.00287 & -0.0242 & 0.490387 \tabularnewline
16 & 0.04499 & 0.3791 & 0.352874 \tabularnewline
17 & 0.038873 & 0.3275 & 0.372108 \tabularnewline
18 & 0.037171 & 0.3132 & 0.377519 \tabularnewline
19 & -0.061243 & -0.516 & 0.303714 \tabularnewline
20 & -0.041908 & -0.3531 & 0.362521 \tabularnewline
21 & -0.11152 & -0.9397 & 0.175283 \tabularnewline
22 & -0.025384 & -0.2139 & 0.415624 \tabularnewline
23 & 0.101919 & 0.8588 & 0.196674 \tabularnewline
24 & 0.220461 & 1.8576 & 0.033684 \tabularnewline
25 & 0.026586 & 0.224 & 0.411694 \tabularnewline
26 & -0.168152 & -1.4169 & 0.080446 \tabularnewline
27 & -0.011194 & -0.0943 & 0.46256 \tabularnewline
28 & -0.002577 & -0.0217 & 0.491367 \tabularnewline
29 & 0.00865 & 0.0729 & 0.471051 \tabularnewline
30 & 0.028507 & 0.2402 & 0.405433 \tabularnewline
31 & -0.013638 & -0.1149 & 0.454418 \tabularnewline
32 & -0.037268 & -0.314 & 0.37721 \tabularnewline
33 & -0.143872 & -1.2123 & 0.11471 \tabularnewline
34 & -0.054768 & -0.4615 & 0.322933 \tabularnewline
35 & 0.069947 & 0.5894 & 0.278737 \tabularnewline
36 & -0.222573 & -1.8754 & 0.032423 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70199&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]0.008078[/C][C]0.0681[/C][C]0.472963[/C][/ROW]
[ROW][C]2[/C][C]-0.071394[/C][C]-0.6016[/C][C]0.274687[/C][/ROW]
[ROW][C]3[/C][C]-0.224178[/C][C]-1.889[/C][C]0.031491[/C][/ROW]
[ROW][C]4[/C][C]0.039985[/C][C]0.3369[/C][C]0.368585[/C][/ROW]
[ROW][C]5[/C][C]0.121592[/C][C]1.0246[/C][C]0.154526[/C][/ROW]
[ROW][C]6[/C][C]0.120937[/C][C]1.019[/C][C]0.155824[/C][/ROW]
[ROW][C]7[/C][C]0.077269[/C][C]0.6511[/C][C]0.258549[/C][/ROW]
[ROW][C]8[/C][C]-0.007411[/C][C]-0.0624[/C][C]0.475192[/C][/ROW]
[ROW][C]9[/C][C]-0.180627[/C][C]-1.522[/C][C]0.066227[/C][/ROW]
[ROW][C]10[/C][C]-0.008945[/C][C]-0.0754[/C][C]0.470067[/C][/ROW]
[ROW][C]11[/C][C]0.067653[/C][C]0.5701[/C][C]0.285219[/C][/ROW]
[ROW][C]12[/C][C]0.022809[/C][C]0.1922[/C][C]0.424071[/C][/ROW]
[ROW][C]13[/C][C]0.074207[/C][C]0.6253[/C][C]0.266896[/C][/ROW]
[ROW][C]14[/C][C]-0.096184[/C][C]-0.8105[/C][C]0.210192[/C][/ROW]
[ROW][C]15[/C][C]-0.00287[/C][C]-0.0242[/C][C]0.490387[/C][/ROW]
[ROW][C]16[/C][C]0.04499[/C][C]0.3791[/C][C]0.352874[/C][/ROW]
[ROW][C]17[/C][C]0.038873[/C][C]0.3275[/C][C]0.372108[/C][/ROW]
[ROW][C]18[/C][C]0.037171[/C][C]0.3132[/C][C]0.377519[/C][/ROW]
[ROW][C]19[/C][C]-0.061243[/C][C]-0.516[/C][C]0.303714[/C][/ROW]
[ROW][C]20[/C][C]-0.041908[/C][C]-0.3531[/C][C]0.362521[/C][/ROW]
[ROW][C]21[/C][C]-0.11152[/C][C]-0.9397[/C][C]0.175283[/C][/ROW]
[ROW][C]22[/C][C]-0.025384[/C][C]-0.2139[/C][C]0.415624[/C][/ROW]
[ROW][C]23[/C][C]0.101919[/C][C]0.8588[/C][C]0.196674[/C][/ROW]
[ROW][C]24[/C][C]0.220461[/C][C]1.8576[/C][C]0.033684[/C][/ROW]
[ROW][C]25[/C][C]0.026586[/C][C]0.224[/C][C]0.411694[/C][/ROW]
[ROW][C]26[/C][C]-0.168152[/C][C]-1.4169[/C][C]0.080446[/C][/ROW]
[ROW][C]27[/C][C]-0.011194[/C][C]-0.0943[/C][C]0.46256[/C][/ROW]
[ROW][C]28[/C][C]-0.002577[/C][C]-0.0217[/C][C]0.491367[/C][/ROW]
[ROW][C]29[/C][C]0.00865[/C][C]0.0729[/C][C]0.471051[/C][/ROW]
[ROW][C]30[/C][C]0.028507[/C][C]0.2402[/C][C]0.405433[/C][/ROW]
[ROW][C]31[/C][C]-0.013638[/C][C]-0.1149[/C][C]0.454418[/C][/ROW]
[ROW][C]32[/C][C]-0.037268[/C][C]-0.314[/C][C]0.37721[/C][/ROW]
[ROW][C]33[/C][C]-0.143872[/C][C]-1.2123[/C][C]0.11471[/C][/ROW]
[ROW][C]34[/C][C]-0.054768[/C][C]-0.4615[/C][C]0.322933[/C][/ROW]
[ROW][C]35[/C][C]0.069947[/C][C]0.5894[/C][C]0.278737[/C][/ROW]
[ROW][C]36[/C][C]-0.222573[/C][C]-1.8754[/C][C]0.032423[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70199&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70199&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
10.0080780.06810.472963
2-0.071394-0.60160.274687
3-0.224178-1.8890.031491
40.0399850.33690.368585
50.1215921.02460.154526
60.1209371.0190.155824
70.0772690.65110.258549
8-0.007411-0.06240.475192
9-0.180627-1.5220.066227
10-0.008945-0.07540.470067
110.0676530.57010.285219
120.0228090.19220.424071
130.0742070.62530.266896
14-0.096184-0.81050.210192
15-0.00287-0.02420.490387
160.044990.37910.352874
170.0388730.32750.372108
180.0371710.31320.377519
19-0.061243-0.5160.303714
20-0.041908-0.35310.362521
21-0.11152-0.93970.175283
22-0.025384-0.21390.415624
230.1019190.85880.196674
240.2204611.85760.033684
250.0265860.2240.411694
26-0.168152-1.41690.080446
27-0.011194-0.09430.46256
28-0.002577-0.02170.491367
290.008650.07290.471051
300.0285070.24020.405433
31-0.013638-0.11490.454418
32-0.037268-0.3140.37721
33-0.143872-1.21230.11471
34-0.054768-0.46150.322933
350.0699470.58940.278737
36-0.222573-1.87540.032423







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0080780.06810.472963
2-0.071464-0.60220.274492
3-0.224142-1.88870.031512
40.0372350.31370.377316
50.0956650.80610.211442
60.0815040.68680.247233
70.1160310.97770.165772
80.0560630.47240.319047
9-0.147924-1.24640.108352
100.0060450.05090.47976
110.0303130.25540.399569
12-0.084243-0.70980.240063
130.0838940.70690.24097
14-0.058566-0.49350.311596
150.0093740.0790.468631
160.1063420.89610.186627
170.0070090.05910.476536
180.0099670.0840.466653
19-0.025269-0.21290.415999
20-0.041334-0.34830.364327
21-0.14923-1.25740.106359
22-0.046454-0.39140.348327
230.0461190.38860.349365
240.2049651.72710.044252
250.1183770.99750.160964
26-0.09128-0.76910.222182
270.1256111.05840.146726
28-0.048426-0.4080.342235
29-0.162903-1.37260.087092
30-0.031607-0.26630.395379
31-0.102679-0.86520.194925
32-0.052017-0.43830.331248
33-0.054235-0.4570.324534
34-0.027441-0.23120.408903
350.0508530.42850.334794
36-0.256936-2.1650.016876

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.008078 & 0.0681 & 0.472963 \tabularnewline
2 & -0.071464 & -0.6022 & 0.274492 \tabularnewline
3 & -0.224142 & -1.8887 & 0.031512 \tabularnewline
4 & 0.037235 & 0.3137 & 0.377316 \tabularnewline
5 & 0.095665 & 0.8061 & 0.211442 \tabularnewline
6 & 0.081504 & 0.6868 & 0.247233 \tabularnewline
7 & 0.116031 & 0.9777 & 0.165772 \tabularnewline
8 & 0.056063 & 0.4724 & 0.319047 \tabularnewline
9 & -0.147924 & -1.2464 & 0.108352 \tabularnewline
10 & 0.006045 & 0.0509 & 0.47976 \tabularnewline
11 & 0.030313 & 0.2554 & 0.399569 \tabularnewline
12 & -0.084243 & -0.7098 & 0.240063 \tabularnewline
13 & 0.083894 & 0.7069 & 0.24097 \tabularnewline
14 & -0.058566 & -0.4935 & 0.311596 \tabularnewline
15 & 0.009374 & 0.079 & 0.468631 \tabularnewline
16 & 0.106342 & 0.8961 & 0.186627 \tabularnewline
17 & 0.007009 & 0.0591 & 0.476536 \tabularnewline
18 & 0.009967 & 0.084 & 0.466653 \tabularnewline
19 & -0.025269 & -0.2129 & 0.415999 \tabularnewline
20 & -0.041334 & -0.3483 & 0.364327 \tabularnewline
21 & -0.14923 & -1.2574 & 0.106359 \tabularnewline
22 & -0.046454 & -0.3914 & 0.348327 \tabularnewline
23 & 0.046119 & 0.3886 & 0.349365 \tabularnewline
24 & 0.204965 & 1.7271 & 0.044252 \tabularnewline
25 & 0.118377 & 0.9975 & 0.160964 \tabularnewline
26 & -0.09128 & -0.7691 & 0.222182 \tabularnewline
27 & 0.125611 & 1.0584 & 0.146726 \tabularnewline
28 & -0.048426 & -0.408 & 0.342235 \tabularnewline
29 & -0.162903 & -1.3726 & 0.087092 \tabularnewline
30 & -0.031607 & -0.2663 & 0.395379 \tabularnewline
31 & -0.102679 & -0.8652 & 0.194925 \tabularnewline
32 & -0.052017 & -0.4383 & 0.331248 \tabularnewline
33 & -0.054235 & -0.457 & 0.324534 \tabularnewline
34 & -0.027441 & -0.2312 & 0.408903 \tabularnewline
35 & 0.050853 & 0.4285 & 0.334794 \tabularnewline
36 & -0.256936 & -2.165 & 0.016876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70199&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]0.008078[/C][C]0.0681[/C][C]0.472963[/C][/ROW]
[ROW][C]2[/C][C]-0.071464[/C][C]-0.6022[/C][C]0.274492[/C][/ROW]
[ROW][C]3[/C][C]-0.224142[/C][C]-1.8887[/C][C]0.031512[/C][/ROW]
[ROW][C]4[/C][C]0.037235[/C][C]0.3137[/C][C]0.377316[/C][/ROW]
[ROW][C]5[/C][C]0.095665[/C][C]0.8061[/C][C]0.211442[/C][/ROW]
[ROW][C]6[/C][C]0.081504[/C][C]0.6868[/C][C]0.247233[/C][/ROW]
[ROW][C]7[/C][C]0.116031[/C][C]0.9777[/C][C]0.165772[/C][/ROW]
[ROW][C]8[/C][C]0.056063[/C][C]0.4724[/C][C]0.319047[/C][/ROW]
[ROW][C]9[/C][C]-0.147924[/C][C]-1.2464[/C][C]0.108352[/C][/ROW]
[ROW][C]10[/C][C]0.006045[/C][C]0.0509[/C][C]0.47976[/C][/ROW]
[ROW][C]11[/C][C]0.030313[/C][C]0.2554[/C][C]0.399569[/C][/ROW]
[ROW][C]12[/C][C]-0.084243[/C][C]-0.7098[/C][C]0.240063[/C][/ROW]
[ROW][C]13[/C][C]0.083894[/C][C]0.7069[/C][C]0.24097[/C][/ROW]
[ROW][C]14[/C][C]-0.058566[/C][C]-0.4935[/C][C]0.311596[/C][/ROW]
[ROW][C]15[/C][C]0.009374[/C][C]0.079[/C][C]0.468631[/C][/ROW]
[ROW][C]16[/C][C]0.106342[/C][C]0.8961[/C][C]0.186627[/C][/ROW]
[ROW][C]17[/C][C]0.007009[/C][C]0.0591[/C][C]0.476536[/C][/ROW]
[ROW][C]18[/C][C]0.009967[/C][C]0.084[/C][C]0.466653[/C][/ROW]
[ROW][C]19[/C][C]-0.025269[/C][C]-0.2129[/C][C]0.415999[/C][/ROW]
[ROW][C]20[/C][C]-0.041334[/C][C]-0.3483[/C][C]0.364327[/C][/ROW]
[ROW][C]21[/C][C]-0.14923[/C][C]-1.2574[/C][C]0.106359[/C][/ROW]
[ROW][C]22[/C][C]-0.046454[/C][C]-0.3914[/C][C]0.348327[/C][/ROW]
[ROW][C]23[/C][C]0.046119[/C][C]0.3886[/C][C]0.349365[/C][/ROW]
[ROW][C]24[/C][C]0.204965[/C][C]1.7271[/C][C]0.044252[/C][/ROW]
[ROW][C]25[/C][C]0.118377[/C][C]0.9975[/C][C]0.160964[/C][/ROW]
[ROW][C]26[/C][C]-0.09128[/C][C]-0.7691[/C][C]0.222182[/C][/ROW]
[ROW][C]27[/C][C]0.125611[/C][C]1.0584[/C][C]0.146726[/C][/ROW]
[ROW][C]28[/C][C]-0.048426[/C][C]-0.408[/C][C]0.342235[/C][/ROW]
[ROW][C]29[/C][C]-0.162903[/C][C]-1.3726[/C][C]0.087092[/C][/ROW]
[ROW][C]30[/C][C]-0.031607[/C][C]-0.2663[/C][C]0.395379[/C][/ROW]
[ROW][C]31[/C][C]-0.102679[/C][C]-0.8652[/C][C]0.194925[/C][/ROW]
[ROW][C]32[/C][C]-0.052017[/C][C]-0.4383[/C][C]0.331248[/C][/ROW]
[ROW][C]33[/C][C]-0.054235[/C][C]-0.457[/C][C]0.324534[/C][/ROW]
[ROW][C]34[/C][C]-0.027441[/C][C]-0.2312[/C][C]0.408903[/C][/ROW]
[ROW][C]35[/C][C]0.050853[/C][C]0.4285[/C][C]0.334794[/C][/ROW]
[ROW][C]36[/C][C]-0.256936[/C][C]-2.165[/C][C]0.016876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70199&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70199&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
10.0080780.06810.472963
2-0.071464-0.60220.274492
3-0.224142-1.88870.031512
40.0372350.31370.377316
50.0956650.80610.211442
60.0815040.68680.247233
70.1160310.97770.165772
80.0560630.47240.319047
9-0.147924-1.24640.108352
100.0060450.05090.47976
110.0303130.25540.399569
12-0.084243-0.70980.240063
130.0838940.70690.24097
14-0.058566-0.49350.311596
150.0093740.0790.468631
160.1063420.89610.186627
170.0070090.05910.476536
180.0099670.0840.466653
19-0.025269-0.21290.415999
20-0.041334-0.34830.364327
21-0.14923-1.25740.106359
22-0.046454-0.39140.348327
230.0461190.38860.349365
240.2049651.72710.044252
250.1183770.99750.160964
26-0.09128-0.76910.222182
270.1256111.05840.146726
28-0.048426-0.4080.342235
29-0.162903-1.37260.087092
30-0.031607-0.26630.395379
31-0.102679-0.86520.194925
32-0.052017-0.43830.331248
33-0.054235-0.4570.324534
34-0.027441-0.23120.408903
350.0508530.42850.334794
36-0.256936-2.1650.016876



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