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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 01 Dec 2011 08:29:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/01/t132274622242ekjrq5j5h73hz.htm/, Retrieved Thu, 28 Mar 2024 20:01:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=149541, Retrieved Thu, 28 Mar 2024 20:01:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [WS 9 Autocorrelatie ] [2010-12-03 12:44:11] [8081b8996d5947580de3eb171e82db4f]
-   P       [(Partial) Autocorrelation Function] [Verbetering WS9] [2010-12-14 19:15:43] [3635fb7041b1998c5a1332cf9de22bce]
- R PD          [(Partial) Autocorrelation Function] [] [2011-12-01 13:29:59] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2011-12-01 13:43:53] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
9 676
8 642
9 402
9 610
9 294
9 448
10 319
9 548
9 801
9 596
8 923
9 746
9 829
9 125
9 782
9 441
9 162
9 915
10 444
10 209
9 985
9 842
9 429
10 132
9 849
9 172
10 313
9 819
9 955
10 048
10 082
10 541
10 208
10 233
9 439
9 963
10 158
9 225
10 474
9 757
10 490
10 281
10 444
10 640
10 695
10 786
9 832
9 747
10 411
9 511
10 402
9 701
10 540
10 112
10 915
11 183
10 384
10 834
9 886
10 216
10 943
9 867
10 203
10 837
10 573
10 647
11 502
10 656
10 866
10 835
9 945
10 331




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149541&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149541&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' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4221443.5820.000308
20.4491783.81140.000144
30.4637043.93479.5e-05
40.1920021.62920.05382
50.2653742.25180.013694
60.2183671.85290.033997
70.1831851.55440.062239
80.1768771.50090.068884
90.3633873.08340.00145
100.2851562.41960.009031
110.2585462.19380.015738
120.5547774.70746e-06
130.2032941.7250.044409
140.2685532.27870.012825
150.1816821.54160.063774
160.0072540.06150.475546
170.0152960.12980.448548
18-0.043481-0.36890.356626
190.0284680.24160.404904
20-0.003314-0.02810.488823
210.1456931.23620.110193
220.1167710.99080.162541
230.0753330.63920.262355
240.26732.26810.013161
250.078580.66680.253524
260.0496120.4210.337513
270.0041360.03510.486052
28-0.083945-0.71230.239293
29-0.129633-1.10.137505
30-0.151708-1.28730.101059
31-0.11544-0.97950.165296
32-0.143913-1.22110.113008
33-0.021329-0.1810.428444
34-0.033341-0.28290.389031
35-0.096824-0.82160.207014
360.0505910.42930.334502

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.422144 & 3.582 & 0.000308 \tabularnewline
2 & 0.449178 & 3.8114 & 0.000144 \tabularnewline
3 & 0.463704 & 3.9347 & 9.5e-05 \tabularnewline
4 & 0.192002 & 1.6292 & 0.05382 \tabularnewline
5 & 0.265374 & 2.2518 & 0.013694 \tabularnewline
6 & 0.218367 & 1.8529 & 0.033997 \tabularnewline
7 & 0.183185 & 1.5544 & 0.062239 \tabularnewline
8 & 0.176877 & 1.5009 & 0.068884 \tabularnewline
9 & 0.363387 & 3.0834 & 0.00145 \tabularnewline
10 & 0.285156 & 2.4196 & 0.009031 \tabularnewline
11 & 0.258546 & 2.1938 & 0.015738 \tabularnewline
12 & 0.554777 & 4.7074 & 6e-06 \tabularnewline
13 & 0.203294 & 1.725 & 0.044409 \tabularnewline
14 & 0.268553 & 2.2787 & 0.012825 \tabularnewline
15 & 0.181682 & 1.5416 & 0.063774 \tabularnewline
16 & 0.007254 & 0.0615 & 0.475546 \tabularnewline
17 & 0.015296 & 0.1298 & 0.448548 \tabularnewline
18 & -0.043481 & -0.3689 & 0.356626 \tabularnewline
19 & 0.028468 & 0.2416 & 0.404904 \tabularnewline
20 & -0.003314 & -0.0281 & 0.488823 \tabularnewline
21 & 0.145693 & 1.2362 & 0.110193 \tabularnewline
22 & 0.116771 & 0.9908 & 0.162541 \tabularnewline
23 & 0.075333 & 0.6392 & 0.262355 \tabularnewline
24 & 0.2673 & 2.2681 & 0.013161 \tabularnewline
25 & 0.07858 & 0.6668 & 0.253524 \tabularnewline
26 & 0.049612 & 0.421 & 0.337513 \tabularnewline
27 & 0.004136 & 0.0351 & 0.486052 \tabularnewline
28 & -0.083945 & -0.7123 & 0.239293 \tabularnewline
29 & -0.129633 & -1.1 & 0.137505 \tabularnewline
30 & -0.151708 & -1.2873 & 0.101059 \tabularnewline
31 & -0.11544 & -0.9795 & 0.165296 \tabularnewline
32 & -0.143913 & -1.2211 & 0.113008 \tabularnewline
33 & -0.021329 & -0.181 & 0.428444 \tabularnewline
34 & -0.033341 & -0.2829 & 0.389031 \tabularnewline
35 & -0.096824 & -0.8216 & 0.207014 \tabularnewline
36 & 0.050591 & 0.4293 & 0.334502 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149541&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]0.422144[/C][C]3.582[/C][C]0.000308[/C][/ROW]
[ROW][C]2[/C][C]0.449178[/C][C]3.8114[/C][C]0.000144[/C][/ROW]
[ROW][C]3[/C][C]0.463704[/C][C]3.9347[/C][C]9.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.192002[/C][C]1.6292[/C][C]0.05382[/C][/ROW]
[ROW][C]5[/C][C]0.265374[/C][C]2.2518[/C][C]0.013694[/C][/ROW]
[ROW][C]6[/C][C]0.218367[/C][C]1.8529[/C][C]0.033997[/C][/ROW]
[ROW][C]7[/C][C]0.183185[/C][C]1.5544[/C][C]0.062239[/C][/ROW]
[ROW][C]8[/C][C]0.176877[/C][C]1.5009[/C][C]0.068884[/C][/ROW]
[ROW][C]9[/C][C]0.363387[/C][C]3.0834[/C][C]0.00145[/C][/ROW]
[ROW][C]10[/C][C]0.285156[/C][C]2.4196[/C][C]0.009031[/C][/ROW]
[ROW][C]11[/C][C]0.258546[/C][C]2.1938[/C][C]0.015738[/C][/ROW]
[ROW][C]12[/C][C]0.554777[/C][C]4.7074[/C][C]6e-06[/C][/ROW]
[ROW][C]13[/C][C]0.203294[/C][C]1.725[/C][C]0.044409[/C][/ROW]
[ROW][C]14[/C][C]0.268553[/C][C]2.2787[/C][C]0.012825[/C][/ROW]
[ROW][C]15[/C][C]0.181682[/C][C]1.5416[/C][C]0.063774[/C][/ROW]
[ROW][C]16[/C][C]0.007254[/C][C]0.0615[/C][C]0.475546[/C][/ROW]
[ROW][C]17[/C][C]0.015296[/C][C]0.1298[/C][C]0.448548[/C][/ROW]
[ROW][C]18[/C][C]-0.043481[/C][C]-0.3689[/C][C]0.356626[/C][/ROW]
[ROW][C]19[/C][C]0.028468[/C][C]0.2416[/C][C]0.404904[/C][/ROW]
[ROW][C]20[/C][C]-0.003314[/C][C]-0.0281[/C][C]0.488823[/C][/ROW]
[ROW][C]21[/C][C]0.145693[/C][C]1.2362[/C][C]0.110193[/C][/ROW]
[ROW][C]22[/C][C]0.116771[/C][C]0.9908[/C][C]0.162541[/C][/ROW]
[ROW][C]23[/C][C]0.075333[/C][C]0.6392[/C][C]0.262355[/C][/ROW]
[ROW][C]24[/C][C]0.2673[/C][C]2.2681[/C][C]0.013161[/C][/ROW]
[ROW][C]25[/C][C]0.07858[/C][C]0.6668[/C][C]0.253524[/C][/ROW]
[ROW][C]26[/C][C]0.049612[/C][C]0.421[/C][C]0.337513[/C][/ROW]
[ROW][C]27[/C][C]0.004136[/C][C]0.0351[/C][C]0.486052[/C][/ROW]
[ROW][C]28[/C][C]-0.083945[/C][C]-0.7123[/C][C]0.239293[/C][/ROW]
[ROW][C]29[/C][C]-0.129633[/C][C]-1.1[/C][C]0.137505[/C][/ROW]
[ROW][C]30[/C][C]-0.151708[/C][C]-1.2873[/C][C]0.101059[/C][/ROW]
[ROW][C]31[/C][C]-0.11544[/C][C]-0.9795[/C][C]0.165296[/C][/ROW]
[ROW][C]32[/C][C]-0.143913[/C][C]-1.2211[/C][C]0.113008[/C][/ROW]
[ROW][C]33[/C][C]-0.021329[/C][C]-0.181[/C][C]0.428444[/C][/ROW]
[ROW][C]34[/C][C]-0.033341[/C][C]-0.2829[/C][C]0.389031[/C][/ROW]
[ROW][C]35[/C][C]-0.096824[/C][C]-0.8216[/C][C]0.207014[/C][/ROW]
[ROW][C]36[/C][C]0.050591[/C][C]0.4293[/C][C]0.334502[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149541&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
10.4221443.5820.000308
20.4491783.81140.000144
30.4637043.93479.5e-05
40.1920021.62920.05382
50.2653742.25180.013694
60.2183671.85290.033997
70.1831851.55440.062239
80.1768771.50090.068884
90.3633873.08340.00145
100.2851562.41960.009031
110.2585462.19380.015738
120.5547774.70746e-06
130.2032941.7250.044409
140.2685532.27870.012825
150.1816821.54160.063774
160.0072540.06150.475546
170.0152960.12980.448548
18-0.043481-0.36890.356626
190.0284680.24160.404904
20-0.003314-0.02810.488823
210.1456931.23620.110193
220.1167710.99080.162541
230.0753330.63920.262355
240.26732.26810.013161
250.078580.66680.253524
260.0496120.4210.337513
270.0041360.03510.486052
28-0.083945-0.71230.239293
29-0.129633-1.10.137505
30-0.151708-1.28730.101059
31-0.11544-0.97950.165296
32-0.143913-1.22110.113008
33-0.021329-0.1810.428444
34-0.033341-0.28290.389031
35-0.096824-0.82160.207014
360.0505910.42930.334502







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4221443.5820.000308
20.3297332.79790.003297
30.2695282.2870.012568
4-0.18495-1.56940.060475
50.0307210.26070.397542
60.0494170.41930.338116
70.0948280.80460.211838
8-0.023159-0.19650.422381
90.3286832.7890.00338
100.0769830.65320.257847
11-0.047192-0.40040.345011
120.3642853.09110.001418
13-0.194683-1.65190.051451
14-0.097676-0.82880.204975
15-0.242109-2.05440.021786
16-0.00798-0.06770.473101
17-0.191188-1.62230.054557
18-0.077563-0.65810.256272
190.1530391.29860.099116
200.0489740.41560.339486
21-0.002089-0.01770.492952
220.0170030.14430.442845
230.0040510.03440.486335
240.0110190.09350.462885
250.051730.43890.33101
26-0.121375-1.02990.153252
270.0008840.00750.497018
28-0.012422-0.10540.458176
29-0.011785-0.10.460313
30-0.062275-0.52840.299418
31-0.077513-0.65770.256409
320.0065860.05590.477794
33-0.099874-0.84750.199773
34-0.028462-0.24150.404925
35-0.081598-0.69240.245462
360.0578790.49110.312417

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.422144 & 3.582 & 0.000308 \tabularnewline
2 & 0.329733 & 2.7979 & 0.003297 \tabularnewline
3 & 0.269528 & 2.287 & 0.012568 \tabularnewline
4 & -0.18495 & -1.5694 & 0.060475 \tabularnewline
5 & 0.030721 & 0.2607 & 0.397542 \tabularnewline
6 & 0.049417 & 0.4193 & 0.338116 \tabularnewline
7 & 0.094828 & 0.8046 & 0.211838 \tabularnewline
8 & -0.023159 & -0.1965 & 0.422381 \tabularnewline
9 & 0.328683 & 2.789 & 0.00338 \tabularnewline
10 & 0.076983 & 0.6532 & 0.257847 \tabularnewline
11 & -0.047192 & -0.4004 & 0.345011 \tabularnewline
12 & 0.364285 & 3.0911 & 0.001418 \tabularnewline
13 & -0.194683 & -1.6519 & 0.051451 \tabularnewline
14 & -0.097676 & -0.8288 & 0.204975 \tabularnewline
15 & -0.242109 & -2.0544 & 0.021786 \tabularnewline
16 & -0.00798 & -0.0677 & 0.473101 \tabularnewline
17 & -0.191188 & -1.6223 & 0.054557 \tabularnewline
18 & -0.077563 & -0.6581 & 0.256272 \tabularnewline
19 & 0.153039 & 1.2986 & 0.099116 \tabularnewline
20 & 0.048974 & 0.4156 & 0.339486 \tabularnewline
21 & -0.002089 & -0.0177 & 0.492952 \tabularnewline
22 & 0.017003 & 0.1443 & 0.442845 \tabularnewline
23 & 0.004051 & 0.0344 & 0.486335 \tabularnewline
24 & 0.011019 & 0.0935 & 0.462885 \tabularnewline
25 & 0.05173 & 0.4389 & 0.33101 \tabularnewline
26 & -0.121375 & -1.0299 & 0.153252 \tabularnewline
27 & 0.000884 & 0.0075 & 0.497018 \tabularnewline
28 & -0.012422 & -0.1054 & 0.458176 \tabularnewline
29 & -0.011785 & -0.1 & 0.460313 \tabularnewline
30 & -0.062275 & -0.5284 & 0.299418 \tabularnewline
31 & -0.077513 & -0.6577 & 0.256409 \tabularnewline
32 & 0.006586 & 0.0559 & 0.477794 \tabularnewline
33 & -0.099874 & -0.8475 & 0.199773 \tabularnewline
34 & -0.028462 & -0.2415 & 0.404925 \tabularnewline
35 & -0.081598 & -0.6924 & 0.245462 \tabularnewline
36 & 0.057879 & 0.4911 & 0.312417 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149541&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]0.422144[/C][C]3.582[/C][C]0.000308[/C][/ROW]
[ROW][C]2[/C][C]0.329733[/C][C]2.7979[/C][C]0.003297[/C][/ROW]
[ROW][C]3[/C][C]0.269528[/C][C]2.287[/C][C]0.012568[/C][/ROW]
[ROW][C]4[/C][C]-0.18495[/C][C]-1.5694[/C][C]0.060475[/C][/ROW]
[ROW][C]5[/C][C]0.030721[/C][C]0.2607[/C][C]0.397542[/C][/ROW]
[ROW][C]6[/C][C]0.049417[/C][C]0.4193[/C][C]0.338116[/C][/ROW]
[ROW][C]7[/C][C]0.094828[/C][C]0.8046[/C][C]0.211838[/C][/ROW]
[ROW][C]8[/C][C]-0.023159[/C][C]-0.1965[/C][C]0.422381[/C][/ROW]
[ROW][C]9[/C][C]0.328683[/C][C]2.789[/C][C]0.00338[/C][/ROW]
[ROW][C]10[/C][C]0.076983[/C][C]0.6532[/C][C]0.257847[/C][/ROW]
[ROW][C]11[/C][C]-0.047192[/C][C]-0.4004[/C][C]0.345011[/C][/ROW]
[ROW][C]12[/C][C]0.364285[/C][C]3.0911[/C][C]0.001418[/C][/ROW]
[ROW][C]13[/C][C]-0.194683[/C][C]-1.6519[/C][C]0.051451[/C][/ROW]
[ROW][C]14[/C][C]-0.097676[/C][C]-0.8288[/C][C]0.204975[/C][/ROW]
[ROW][C]15[/C][C]-0.242109[/C][C]-2.0544[/C][C]0.021786[/C][/ROW]
[ROW][C]16[/C][C]-0.00798[/C][C]-0.0677[/C][C]0.473101[/C][/ROW]
[ROW][C]17[/C][C]-0.191188[/C][C]-1.6223[/C][C]0.054557[/C][/ROW]
[ROW][C]18[/C][C]-0.077563[/C][C]-0.6581[/C][C]0.256272[/C][/ROW]
[ROW][C]19[/C][C]0.153039[/C][C]1.2986[/C][C]0.099116[/C][/ROW]
[ROW][C]20[/C][C]0.048974[/C][C]0.4156[/C][C]0.339486[/C][/ROW]
[ROW][C]21[/C][C]-0.002089[/C][C]-0.0177[/C][C]0.492952[/C][/ROW]
[ROW][C]22[/C][C]0.017003[/C][C]0.1443[/C][C]0.442845[/C][/ROW]
[ROW][C]23[/C][C]0.004051[/C][C]0.0344[/C][C]0.486335[/C][/ROW]
[ROW][C]24[/C][C]0.011019[/C][C]0.0935[/C][C]0.462885[/C][/ROW]
[ROW][C]25[/C][C]0.05173[/C][C]0.4389[/C][C]0.33101[/C][/ROW]
[ROW][C]26[/C][C]-0.121375[/C][C]-1.0299[/C][C]0.153252[/C][/ROW]
[ROW][C]27[/C][C]0.000884[/C][C]0.0075[/C][C]0.497018[/C][/ROW]
[ROW][C]28[/C][C]-0.012422[/C][C]-0.1054[/C][C]0.458176[/C][/ROW]
[ROW][C]29[/C][C]-0.011785[/C][C]-0.1[/C][C]0.460313[/C][/ROW]
[ROW][C]30[/C][C]-0.062275[/C][C]-0.5284[/C][C]0.299418[/C][/ROW]
[ROW][C]31[/C][C]-0.077513[/C][C]-0.6577[/C][C]0.256409[/C][/ROW]
[ROW][C]32[/C][C]0.006586[/C][C]0.0559[/C][C]0.477794[/C][/ROW]
[ROW][C]33[/C][C]-0.099874[/C][C]-0.8475[/C][C]0.199773[/C][/ROW]
[ROW][C]34[/C][C]-0.028462[/C][C]-0.2415[/C][C]0.404925[/C][/ROW]
[ROW][C]35[/C][C]-0.081598[/C][C]-0.6924[/C][C]0.245462[/C][/ROW]
[ROW][C]36[/C][C]0.057879[/C][C]0.4911[/C][C]0.312417[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149541&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149541&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
10.4221443.5820.000308
20.3297332.79790.003297
30.2695282.2870.012568
4-0.18495-1.56940.060475
50.0307210.26070.397542
60.0494170.41930.338116
70.0948280.80460.211838
8-0.023159-0.19650.422381
90.3286832.7890.00338
100.0769830.65320.257847
11-0.047192-0.40040.345011
120.3642853.09110.001418
13-0.194683-1.65190.051451
14-0.097676-0.82880.204975
15-0.242109-2.05440.021786
16-0.00798-0.06770.473101
17-0.191188-1.62230.054557
18-0.077563-0.65810.256272
190.1530391.29860.099116
200.0489740.41560.339486
21-0.002089-0.01770.492952
220.0170030.14430.442845
230.0040510.03440.486335
240.0110190.09350.462885
250.051730.43890.33101
26-0.121375-1.02990.153252
270.0008840.00750.497018
28-0.012422-0.10540.458176
29-0.011785-0.10.460313
30-0.062275-0.52840.299418
31-0.077513-0.65770.256409
320.0065860.05590.477794
33-0.099874-0.84750.199773
34-0.028462-0.24150.404925
35-0.081598-0.69240.245462
360.0578790.49110.312417



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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')