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Description of Statistical Computation

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 computationWed, 25 Nov 2009 15:08:31 -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/25/t12591869441gu7gjrxhztdlir.htm/, Retrieved Tue, 07 May 2024 05:06:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59667, Retrieved Tue, 07 May 2024 05:06:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [ACF (berekening 2)] [2009-11-25 22:08:31] [befe6dd6a614b6d3a2a74a47a0a4f514] [Current]
-    D            [(Partial) Autocorrelation Function] [Autocorrelatie d=...] [2009-12-15 15:40:32] [4b87f7428fbf2a3c94095f0b8c4ae313]
-   P               [(Partial) Autocorrelation Function] [Autocorrelatie d=...] [2009-12-15 17:33:28] [4b87f7428fbf2a3c94095f0b8c4ae313]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141

Tables (Output of Computation)





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=59667&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=59667&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59667&T=0

As an alternative you can also use a QR Code:  
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
10.9365636.48870
20.8777356.08110
30.8147825.6450
40.7383185.11523e-06
50.6559164.54431.9e-05
60.574813.98240.000115
70.4807123.33050.000837
80.405682.81060.003568
90.3220292.23110.015191
100.2588081.79310.039631
110.20091.39190.085188
120.1225970.84940.199943
130.049770.34480.36587
14-0.011414-0.07910.468649
15-0.072447-0.50190.309006
16-0.126105-0.87370.19332
17-0.188453-1.30560.098949
18-0.248466-1.72140.045807
19-0.292375-2.02560.02419
20-0.339699-2.35350.01137
21-0.38631-2.67640.005075
22-0.410141-2.84150.003286
23-0.432914-2.99930.00214
24-0.448204-3.10520.001593
25-0.457408-3.1690.001331
26-0.456963-3.16590.001343
27-0.439721-3.04650.001878
28-0.424626-2.94190.002505
29-0.390523-2.70560.004705
30-0.344456-2.38650.010501
31-0.308739-2.1390.018775
32-0.280853-1.94580.028773
33-0.225881-1.56490.062083
34-0.187202-1.2970.10042
35-0.152747-1.05830.147616
36-0.132985-0.92130.180738

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936563 & 6.4887 & 0 \tabularnewline
2 & 0.877735 & 6.0811 & 0 \tabularnewline
3 & 0.814782 & 5.645 & 0 \tabularnewline
4 & 0.738318 & 5.1152 & 3e-06 \tabularnewline
5 & 0.655916 & 4.5443 & 1.9e-05 \tabularnewline
6 & 0.57481 & 3.9824 & 0.000115 \tabularnewline
7 & 0.480712 & 3.3305 & 0.000837 \tabularnewline
8 & 0.40568 & 2.8106 & 0.003568 \tabularnewline
9 & 0.322029 & 2.2311 & 0.015191 \tabularnewline
10 & 0.258808 & 1.7931 & 0.039631 \tabularnewline
11 & 0.2009 & 1.3919 & 0.085188 \tabularnewline
12 & 0.122597 & 0.8494 & 0.199943 \tabularnewline
13 & 0.04977 & 0.3448 & 0.36587 \tabularnewline
14 & -0.011414 & -0.0791 & 0.468649 \tabularnewline
15 & -0.072447 & -0.5019 & 0.309006 \tabularnewline
16 & -0.126105 & -0.8737 & 0.19332 \tabularnewline
17 & -0.188453 & -1.3056 & 0.098949 \tabularnewline
18 & -0.248466 & -1.7214 & 0.045807 \tabularnewline
19 & -0.292375 & -2.0256 & 0.02419 \tabularnewline
20 & -0.339699 & -2.3535 & 0.01137 \tabularnewline
21 & -0.38631 & -2.6764 & 0.005075 \tabularnewline
22 & -0.410141 & -2.8415 & 0.003286 \tabularnewline
23 & -0.432914 & -2.9993 & 0.00214 \tabularnewline
24 & -0.448204 & -3.1052 & 0.001593 \tabularnewline
25 & -0.457408 & -3.169 & 0.001331 \tabularnewline
26 & -0.456963 & -3.1659 & 0.001343 \tabularnewline
27 & -0.439721 & -3.0465 & 0.001878 \tabularnewline
28 & -0.424626 & -2.9419 & 0.002505 \tabularnewline
29 & -0.390523 & -2.7056 & 0.004705 \tabularnewline
30 & -0.344456 & -2.3865 & 0.010501 \tabularnewline
31 & -0.308739 & -2.139 & 0.018775 \tabularnewline
32 & -0.280853 & -1.9458 & 0.028773 \tabularnewline
33 & -0.225881 & -1.5649 & 0.062083 \tabularnewline
34 & -0.187202 & -1.297 & 0.10042 \tabularnewline
35 & -0.152747 & -1.0583 & 0.147616 \tabularnewline
36 & -0.132985 & -0.9213 & 0.180738 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59667&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]0.936563[/C][C]6.4887[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.877735[/C][C]6.0811[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.814782[/C][C]5.645[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.738318[/C][C]5.1152[/C][C]3e-06[/C][/ROW]
[ROW][C]5[/C][C]0.655916[/C][C]4.5443[/C][C]1.9e-05[/C][/ROW]
[ROW][C]6[/C][C]0.57481[/C][C]3.9824[/C][C]0.000115[/C][/ROW]
[ROW][C]7[/C][C]0.480712[/C][C]3.3305[/C][C]0.000837[/C][/ROW]
[ROW][C]8[/C][C]0.40568[/C][C]2.8106[/C][C]0.003568[/C][/ROW]
[ROW][C]9[/C][C]0.322029[/C][C]2.2311[/C][C]0.015191[/C][/ROW]
[ROW][C]10[/C][C]0.258808[/C][C]1.7931[/C][C]0.039631[/C][/ROW]
[ROW][C]11[/C][C]0.2009[/C][C]1.3919[/C][C]0.085188[/C][/ROW]
[ROW][C]12[/C][C]0.122597[/C][C]0.8494[/C][C]0.199943[/C][/ROW]
[ROW][C]13[/C][C]0.04977[/C][C]0.3448[/C][C]0.36587[/C][/ROW]
[ROW][C]14[/C][C]-0.011414[/C][C]-0.0791[/C][C]0.468649[/C][/ROW]
[ROW][C]15[/C][C]-0.072447[/C][C]-0.5019[/C][C]0.309006[/C][/ROW]
[ROW][C]16[/C][C]-0.126105[/C][C]-0.8737[/C][C]0.19332[/C][/ROW]
[ROW][C]17[/C][C]-0.188453[/C][C]-1.3056[/C][C]0.098949[/C][/ROW]
[ROW][C]18[/C][C]-0.248466[/C][C]-1.7214[/C][C]0.045807[/C][/ROW]
[ROW][C]19[/C][C]-0.292375[/C][C]-2.0256[/C][C]0.02419[/C][/ROW]
[ROW][C]20[/C][C]-0.339699[/C][C]-2.3535[/C][C]0.01137[/C][/ROW]
[ROW][C]21[/C][C]-0.38631[/C][C]-2.6764[/C][C]0.005075[/C][/ROW]
[ROW][C]22[/C][C]-0.410141[/C][C]-2.8415[/C][C]0.003286[/C][/ROW]
[ROW][C]23[/C][C]-0.432914[/C][C]-2.9993[/C][C]0.00214[/C][/ROW]
[ROW][C]24[/C][C]-0.448204[/C][C]-3.1052[/C][C]0.001593[/C][/ROW]
[ROW][C]25[/C][C]-0.457408[/C][C]-3.169[/C][C]0.001331[/C][/ROW]
[ROW][C]26[/C][C]-0.456963[/C][C]-3.1659[/C][C]0.001343[/C][/ROW]
[ROW][C]27[/C][C]-0.439721[/C][C]-3.0465[/C][C]0.001878[/C][/ROW]
[ROW][C]28[/C][C]-0.424626[/C][C]-2.9419[/C][C]0.002505[/C][/ROW]
[ROW][C]29[/C][C]-0.390523[/C][C]-2.7056[/C][C]0.004705[/C][/ROW]
[ROW][C]30[/C][C]-0.344456[/C][C]-2.3865[/C][C]0.010501[/C][/ROW]
[ROW][C]31[/C][C]-0.308739[/C][C]-2.139[/C][C]0.018775[/C][/ROW]
[ROW][C]32[/C][C]-0.280853[/C][C]-1.9458[/C][C]0.028773[/C][/ROW]
[ROW][C]33[/C][C]-0.225881[/C][C]-1.5649[/C][C]0.062083[/C][/ROW]
[ROW][C]34[/C][C]-0.187202[/C][C]-1.297[/C][C]0.10042[/C][/ROW]
[ROW][C]35[/C][C]-0.152747[/C][C]-1.0583[/C][C]0.147616[/C][/ROW]
[ROW][C]36[/C][C]-0.132985[/C][C]-0.9213[/C][C]0.180738[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59667&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59667&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9365636.48870
20.8777356.08110
30.8147825.6450
40.7383185.11523e-06
50.6559164.54431.9e-05
60.574813.98240.000115
70.4807123.33050.000837
80.405682.81060.003568
90.3220292.23110.015191
100.2588081.79310.039631
110.20091.39190.085188
120.1225970.84940.199943
130.049770.34480.36587
14-0.011414-0.07910.468649
15-0.072447-0.50190.309006
16-0.126105-0.87370.19332
17-0.188453-1.30560.098949
18-0.248466-1.72140.045807
19-0.292375-2.02560.02419
20-0.339699-2.35350.01137
21-0.38631-2.67640.005075
22-0.410141-2.84150.003286
23-0.432914-2.99930.00214
24-0.448204-3.10520.001593
25-0.457408-3.1690.001331
26-0.456963-3.16590.001343
27-0.439721-3.04650.001878
28-0.424626-2.94190.002505
29-0.390523-2.70560.004705
30-0.344456-2.38650.010501
31-0.308739-2.1390.018775
32-0.280853-1.94580.028773
33-0.225881-1.56490.062083
34-0.187202-1.2970.10042
35-0.152747-1.05830.147616
36-0.132985-0.92130.180738






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9365636.48870
20.004760.0330.486913
3-0.063634-0.44090.330644
4-0.14739-1.02110.156152
5-0.101973-0.70650.24165
6-0.038599-0.26740.395146
7-0.146708-1.01640.157263
80.0978240.67770.250593
9-0.109472-0.75840.225946
100.1249420.86560.195501
11-0.014438-0.10.460368
12-0.237132-1.64290.05347
13-0.048345-0.33490.369563
14-0.02401-0.16630.434293
150.0150670.10440.458649
16-0.036563-0.25330.400553
17-0.123398-0.85490.19842
18-0.04791-0.33190.370693
190.0253790.17580.430583
20-0.061579-0.42660.335777
21-0.127275-0.88180.191143
220.0917990.6360.263898
230.0283840.19670.422465
24-0.010803-0.07480.470324
25-0.069294-0.48010.316674
26-0.009072-0.06290.475072
270.0965410.66890.253396
28-0.03933-0.27250.393208
290.1565211.08440.1418
30-0.008791-0.06090.475844
31-0.056524-0.39160.348539
32-0.103331-0.71590.238761
330.1580481.0950.139493
34-0.098362-0.68150.249424
35-0.091952-0.63710.263555
36-0.083911-0.58140.281861

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936563 & 6.4887 & 0 \tabularnewline
2 & 0.00476 & 0.033 & 0.486913 \tabularnewline
3 & -0.063634 & -0.4409 & 0.330644 \tabularnewline
4 & -0.14739 & -1.0211 & 0.156152 \tabularnewline
5 & -0.101973 & -0.7065 & 0.24165 \tabularnewline
6 & -0.038599 & -0.2674 & 0.395146 \tabularnewline
7 & -0.146708 & -1.0164 & 0.157263 \tabularnewline
8 & 0.097824 & 0.6777 & 0.250593 \tabularnewline
9 & -0.109472 & -0.7584 & 0.225946 \tabularnewline
10 & 0.124942 & 0.8656 & 0.195501 \tabularnewline
11 & -0.014438 & -0.1 & 0.460368 \tabularnewline
12 & -0.237132 & -1.6429 & 0.05347 \tabularnewline
13 & -0.048345 & -0.3349 & 0.369563 \tabularnewline
14 & -0.02401 & -0.1663 & 0.434293 \tabularnewline
15 & 0.015067 & 0.1044 & 0.458649 \tabularnewline
16 & -0.036563 & -0.2533 & 0.400553 \tabularnewline
17 & -0.123398 & -0.8549 & 0.19842 \tabularnewline
18 & -0.04791 & -0.3319 & 0.370693 \tabularnewline
19 & 0.025379 & 0.1758 & 0.430583 \tabularnewline
20 & -0.061579 & -0.4266 & 0.335777 \tabularnewline
21 & -0.127275 & -0.8818 & 0.191143 \tabularnewline
22 & 0.091799 & 0.636 & 0.263898 \tabularnewline
23 & 0.028384 & 0.1967 & 0.422465 \tabularnewline
24 & -0.010803 & -0.0748 & 0.470324 \tabularnewline
25 & -0.069294 & -0.4801 & 0.316674 \tabularnewline
26 & -0.009072 & -0.0629 & 0.475072 \tabularnewline
27 & 0.096541 & 0.6689 & 0.253396 \tabularnewline
28 & -0.03933 & -0.2725 & 0.393208 \tabularnewline
29 & 0.156521 & 1.0844 & 0.1418 \tabularnewline
30 & -0.008791 & -0.0609 & 0.475844 \tabularnewline
31 & -0.056524 & -0.3916 & 0.348539 \tabularnewline
32 & -0.103331 & -0.7159 & 0.238761 \tabularnewline
33 & 0.158048 & 1.095 & 0.139493 \tabularnewline
34 & -0.098362 & -0.6815 & 0.249424 \tabularnewline
35 & -0.091952 & -0.6371 & 0.263555 \tabularnewline
36 & -0.083911 & -0.5814 & 0.281861 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59667&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]0.936563[/C][C]6.4887[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.00476[/C][C]0.033[/C][C]0.486913[/C][/ROW]
[ROW][C]3[/C][C]-0.063634[/C][C]-0.4409[/C][C]0.330644[/C][/ROW]
[ROW][C]4[/C][C]-0.14739[/C][C]-1.0211[/C][C]0.156152[/C][/ROW]
[ROW][C]5[/C][C]-0.101973[/C][C]-0.7065[/C][C]0.24165[/C][/ROW]
[ROW][C]6[/C][C]-0.038599[/C][C]-0.2674[/C][C]0.395146[/C][/ROW]
[ROW][C]7[/C][C]-0.146708[/C][C]-1.0164[/C][C]0.157263[/C][/ROW]
[ROW][C]8[/C][C]0.097824[/C][C]0.6777[/C][C]0.250593[/C][/ROW]
[ROW][C]9[/C][C]-0.109472[/C][C]-0.7584[/C][C]0.225946[/C][/ROW]
[ROW][C]10[/C][C]0.124942[/C][C]0.8656[/C][C]0.195501[/C][/ROW]
[ROW][C]11[/C][C]-0.014438[/C][C]-0.1[/C][C]0.460368[/C][/ROW]
[ROW][C]12[/C][C]-0.237132[/C][C]-1.6429[/C][C]0.05347[/C][/ROW]
[ROW][C]13[/C][C]-0.048345[/C][C]-0.3349[/C][C]0.369563[/C][/ROW]
[ROW][C]14[/C][C]-0.02401[/C][C]-0.1663[/C][C]0.434293[/C][/ROW]
[ROW][C]15[/C][C]0.015067[/C][C]0.1044[/C][C]0.458649[/C][/ROW]
[ROW][C]16[/C][C]-0.036563[/C][C]-0.2533[/C][C]0.400553[/C][/ROW]
[ROW][C]17[/C][C]-0.123398[/C][C]-0.8549[/C][C]0.19842[/C][/ROW]
[ROW][C]18[/C][C]-0.04791[/C][C]-0.3319[/C][C]0.370693[/C][/ROW]
[ROW][C]19[/C][C]0.025379[/C][C]0.1758[/C][C]0.430583[/C][/ROW]
[ROW][C]20[/C][C]-0.061579[/C][C]-0.4266[/C][C]0.335777[/C][/ROW]
[ROW][C]21[/C][C]-0.127275[/C][C]-0.8818[/C][C]0.191143[/C][/ROW]
[ROW][C]22[/C][C]0.091799[/C][C]0.636[/C][C]0.263898[/C][/ROW]
[ROW][C]23[/C][C]0.028384[/C][C]0.1967[/C][C]0.422465[/C][/ROW]
[ROW][C]24[/C][C]-0.010803[/C][C]-0.0748[/C][C]0.470324[/C][/ROW]
[ROW][C]25[/C][C]-0.069294[/C][C]-0.4801[/C][C]0.316674[/C][/ROW]
[ROW][C]26[/C][C]-0.009072[/C][C]-0.0629[/C][C]0.475072[/C][/ROW]
[ROW][C]27[/C][C]0.096541[/C][C]0.6689[/C][C]0.253396[/C][/ROW]
[ROW][C]28[/C][C]-0.03933[/C][C]-0.2725[/C][C]0.393208[/C][/ROW]
[ROW][C]29[/C][C]0.156521[/C][C]1.0844[/C][C]0.1418[/C][/ROW]
[ROW][C]30[/C][C]-0.008791[/C][C]-0.0609[/C][C]0.475844[/C][/ROW]
[ROW][C]31[/C][C]-0.056524[/C][C]-0.3916[/C][C]0.348539[/C][/ROW]
[ROW][C]32[/C][C]-0.103331[/C][C]-0.7159[/C][C]0.238761[/C][/ROW]
[ROW][C]33[/C][C]0.158048[/C][C]1.095[/C][C]0.139493[/C][/ROW]
[ROW][C]34[/C][C]-0.098362[/C][C]-0.6815[/C][C]0.249424[/C][/ROW]
[ROW][C]35[/C][C]-0.091952[/C][C]-0.6371[/C][C]0.263555[/C][/ROW]
[ROW][C]36[/C][C]-0.083911[/C][C]-0.5814[/C][C]0.281861[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59667&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59667&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9365636.48870
20.004760.0330.486913
3-0.063634-0.44090.330644
4-0.14739-1.02110.156152
5-0.101973-0.70650.24165
6-0.038599-0.26740.395146
7-0.146708-1.01640.157263
80.0978240.67770.250593
9-0.109472-0.75840.225946
100.1249420.86560.195501
11-0.014438-0.10.460368
12-0.237132-1.64290.05347
13-0.048345-0.33490.369563
14-0.02401-0.16630.434293
150.0150670.10440.458649
16-0.036563-0.25330.400553
17-0.123398-0.85490.19842
18-0.04791-0.33190.370693
190.0253790.17580.430583
20-0.061579-0.42660.335777
21-0.127275-0.88180.191143
220.0917990.6360.263898
230.0283840.19670.422465
24-0.010803-0.07480.470324
25-0.069294-0.48010.316674
26-0.009072-0.06290.475072
270.0965410.66890.253396
28-0.03933-0.27250.393208
290.1565211.08440.1418
30-0.008791-0.06090.475844
31-0.056524-0.39160.348539
32-0.103331-0.71590.238761
330.1580481.0950.139493
34-0.098362-0.68150.249424
35-0.091952-0.63710.263555
36-0.083911-0.58140.281861


Figures (Output of Computation)

Input Parameters & R Code

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