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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 computationSun, 26 Dec 2010 19:00:55 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/26/t1293389919ee2kv8i6e51kew1.htm/, Retrieved Tue, 07 May 2024 02:44:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115778, Retrieved Tue, 07 May 2024 02:44:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [ACF van Y(t) (d=0...] [2009-11-26 00:58:58] [9717cb857c153ca3061376906953b329]
-   P           [(Partial) Autocorrelation Function] [ACF van Y(t) (d=1...] [2009-11-26 17:32:24] [9717cb857c153ca3061376906953b329]
-   P             [(Partial) Autocorrelation Function] [ACF van Y(t) (d=1...] [2009-11-26 17:41:56] [9717cb857c153ca3061376906953b329]
-   PD                [(Partial) Autocorrelation Function] [Werkloosheid vrou...] [2010-12-26 19:00:55] [75888b09f354cf7130ae5528df429303] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
313.737
312.276
309.391
302.950
300.316
304.035
333.476
337.698
335.932
323.931
313.927
314.485
313.218
309.664
302.963
298.989
298.423
301.631
329.765
335.083
327.616
309.119
295.916
291.413
291.542
284.678
276.475
272.566
264.981
263.290
296.806
303.598
286.994
276.427
266.424
267.153
268.381
262.522
255.542
253.158
243.803
250.741
280.445
285.257
270.976
261.076
255.603
260.376
263.903
264.291
263.276
262.572
256.167
264.221
293.860
300.713
287.224
275.902
271.115
277.509
279.681
276.239
271.037
266.148
259.497
266.795
298.305
303.725
289.742
276.444
268.606

Tables (Output of Computation)





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=115778&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=115778&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115778&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1836591.39870.083613
20.1294150.98560.164212
30.3144062.39440.009949
40.1400961.06690.14521
50.0634390.48310.31541
60.168291.28170.102532
70.0482340.36730.357352
80.1839331.40080.083302
9-0.011213-0.08540.466121
10-0.072979-0.55580.290246
110.1692631.28910.101246
12-0.143894-1.09590.138833
13-0.232184-1.76830.041138
140.0494740.37680.353855
150.0015070.01150.495441
16-0.082121-0.62540.267077
17-0.041216-0.31390.377364
18-0.087371-0.66540.254218
19-0.016426-0.12510.450441
20-0.124441-0.94770.173603
21-0.236969-1.80470.038157
22-0.066099-0.50340.308297
23-0.154968-1.18020.121368
24-0.211201-1.60850.056583
25-0.044722-0.34060.367322
26-0.168924-1.28650.101692
27-0.278024-2.11740.019264
28-0.1793-1.36550.088683
29-0.133586-1.01740.156603
30-0.108791-0.82850.205384
31-0.022645-0.17250.431838
32-0.071305-0.5430.294592
330.0025920.01970.492159
34-0.000744-0.00570.497748
35-0.001902-0.01450.494246
36-0.027639-0.21050.417009

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.183659 & 1.3987 & 0.083613 \tabularnewline
2 & 0.129415 & 0.9856 & 0.164212 \tabularnewline
3 & 0.314406 & 2.3944 & 0.009949 \tabularnewline
4 & 0.140096 & 1.0669 & 0.14521 \tabularnewline
5 & 0.063439 & 0.4831 & 0.31541 \tabularnewline
6 & 0.16829 & 1.2817 & 0.102532 \tabularnewline
7 & 0.048234 & 0.3673 & 0.357352 \tabularnewline
8 & 0.183933 & 1.4008 & 0.083302 \tabularnewline
9 & -0.011213 & -0.0854 & 0.466121 \tabularnewline
10 & -0.072979 & -0.5558 & 0.290246 \tabularnewline
11 & 0.169263 & 1.2891 & 0.101246 \tabularnewline
12 & -0.143894 & -1.0959 & 0.138833 \tabularnewline
13 & -0.232184 & -1.7683 & 0.041138 \tabularnewline
14 & 0.049474 & 0.3768 & 0.353855 \tabularnewline
15 & 0.001507 & 0.0115 & 0.495441 \tabularnewline
16 & -0.082121 & -0.6254 & 0.267077 \tabularnewline
17 & -0.041216 & -0.3139 & 0.377364 \tabularnewline
18 & -0.087371 & -0.6654 & 0.254218 \tabularnewline
19 & -0.016426 & -0.1251 & 0.450441 \tabularnewline
20 & -0.124441 & -0.9477 & 0.173603 \tabularnewline
21 & -0.236969 & -1.8047 & 0.038157 \tabularnewline
22 & -0.066099 & -0.5034 & 0.308297 \tabularnewline
23 & -0.154968 & -1.1802 & 0.121368 \tabularnewline
24 & -0.211201 & -1.6085 & 0.056583 \tabularnewline
25 & -0.044722 & -0.3406 & 0.367322 \tabularnewline
26 & -0.168924 & -1.2865 & 0.101692 \tabularnewline
27 & -0.278024 & -2.1174 & 0.019264 \tabularnewline
28 & -0.1793 & -1.3655 & 0.088683 \tabularnewline
29 & -0.133586 & -1.0174 & 0.156603 \tabularnewline
30 & -0.108791 & -0.8285 & 0.205384 \tabularnewline
31 & -0.022645 & -0.1725 & 0.431838 \tabularnewline
32 & -0.071305 & -0.543 & 0.294592 \tabularnewline
33 & 0.002592 & 0.0197 & 0.492159 \tabularnewline
34 & -0.000744 & -0.0057 & 0.497748 \tabularnewline
35 & -0.001902 & -0.0145 & 0.494246 \tabularnewline
36 & -0.027639 & -0.2105 & 0.417009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115778&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]0.183659[/C][C]1.3987[/C][C]0.083613[/C][/ROW]
[ROW][C]2[/C][C]0.129415[/C][C]0.9856[/C][C]0.164212[/C][/ROW]
[ROW][C]3[/C][C]0.314406[/C][C]2.3944[/C][C]0.009949[/C][/ROW]
[ROW][C]4[/C][C]0.140096[/C][C]1.0669[/C][C]0.14521[/C][/ROW]
[ROW][C]5[/C][C]0.063439[/C][C]0.4831[/C][C]0.31541[/C][/ROW]
[ROW][C]6[/C][C]0.16829[/C][C]1.2817[/C][C]0.102532[/C][/ROW]
[ROW][C]7[/C][C]0.048234[/C][C]0.3673[/C][C]0.357352[/C][/ROW]
[ROW][C]8[/C][C]0.183933[/C][C]1.4008[/C][C]0.083302[/C][/ROW]
[ROW][C]9[/C][C]-0.011213[/C][C]-0.0854[/C][C]0.466121[/C][/ROW]
[ROW][C]10[/C][C]-0.072979[/C][C]-0.5558[/C][C]0.290246[/C][/ROW]
[ROW][C]11[/C][C]0.169263[/C][C]1.2891[/C][C]0.101246[/C][/ROW]
[ROW][C]12[/C][C]-0.143894[/C][C]-1.0959[/C][C]0.138833[/C][/ROW]
[ROW][C]13[/C][C]-0.232184[/C][C]-1.7683[/C][C]0.041138[/C][/ROW]
[ROW][C]14[/C][C]0.049474[/C][C]0.3768[/C][C]0.353855[/C][/ROW]
[ROW][C]15[/C][C]0.001507[/C][C]0.0115[/C][C]0.495441[/C][/ROW]
[ROW][C]16[/C][C]-0.082121[/C][C]-0.6254[/C][C]0.267077[/C][/ROW]
[ROW][C]17[/C][C]-0.041216[/C][C]-0.3139[/C][C]0.377364[/C][/ROW]
[ROW][C]18[/C][C]-0.087371[/C][C]-0.6654[/C][C]0.254218[/C][/ROW]
[ROW][C]19[/C][C]-0.016426[/C][C]-0.1251[/C][C]0.450441[/C][/ROW]
[ROW][C]20[/C][C]-0.124441[/C][C]-0.9477[/C][C]0.173603[/C][/ROW]
[ROW][C]21[/C][C]-0.236969[/C][C]-1.8047[/C][C]0.038157[/C][/ROW]
[ROW][C]22[/C][C]-0.066099[/C][C]-0.5034[/C][C]0.308297[/C][/ROW]
[ROW][C]23[/C][C]-0.154968[/C][C]-1.1802[/C][C]0.121368[/C][/ROW]
[ROW][C]24[/C][C]-0.211201[/C][C]-1.6085[/C][C]0.056583[/C][/ROW]
[ROW][C]25[/C][C]-0.044722[/C][C]-0.3406[/C][C]0.367322[/C][/ROW]
[ROW][C]26[/C][C]-0.168924[/C][C]-1.2865[/C][C]0.101692[/C][/ROW]
[ROW][C]27[/C][C]-0.278024[/C][C]-2.1174[/C][C]0.019264[/C][/ROW]
[ROW][C]28[/C][C]-0.1793[/C][C]-1.3655[/C][C]0.088683[/C][/ROW]
[ROW][C]29[/C][C]-0.133586[/C][C]-1.0174[/C][C]0.156603[/C][/ROW]
[ROW][C]30[/C][C]-0.108791[/C][C]-0.8285[/C][C]0.205384[/C][/ROW]
[ROW][C]31[/C][C]-0.022645[/C][C]-0.1725[/C][C]0.431838[/C][/ROW]
[ROW][C]32[/C][C]-0.071305[/C][C]-0.543[/C][C]0.294592[/C][/ROW]
[ROW][C]33[/C][C]0.002592[/C][C]0.0197[/C][C]0.492159[/C][/ROW]
[ROW][C]34[/C][C]-0.000744[/C][C]-0.0057[/C][C]0.497748[/C][/ROW]
[ROW][C]35[/C][C]-0.001902[/C][C]-0.0145[/C][C]0.494246[/C][/ROW]
[ROW][C]36[/C][C]-0.027639[/C][C]-0.2105[/C][C]0.417009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115778&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115778&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
10.1836591.39870.083613
20.1294150.98560.164212
30.3144062.39440.009949
40.1400961.06690.14521
50.0634390.48310.31541
60.168291.28170.102532
70.0482340.36730.357352
80.1839331.40080.083302
9-0.011213-0.08540.466121
10-0.072979-0.55580.290246
110.1692631.28910.101246
12-0.143894-1.09590.138833
13-0.232184-1.76830.041138
140.0494740.37680.353855
150.0015070.01150.495441
16-0.082121-0.62540.267077
17-0.041216-0.31390.377364
18-0.087371-0.66540.254218
19-0.016426-0.12510.450441
20-0.124441-0.94770.173603
21-0.236969-1.80470.038157
22-0.066099-0.50340.308297
23-0.154968-1.18020.121368
24-0.211201-1.60850.056583
25-0.044722-0.34060.367322
26-0.168924-1.28650.101692
27-0.278024-2.11740.019264
28-0.1793-1.36550.088683
29-0.133586-1.01740.156603
30-0.108791-0.82850.205384
31-0.022645-0.17250.431838
32-0.071305-0.5430.294592
330.0025920.01970.492159
34-0.000744-0.00570.497748
35-0.001902-0.01450.494246
36-0.027639-0.21050.417009






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1836591.39870.083613
20.0990250.75420.226905
30.2872142.18740.016381
40.042830.32620.372731
5-0.01576-0.120.452438
60.0698650.53210.298354
7-0.040825-0.31090.37849
80.1725721.31430.096964
9-0.143028-1.08930.140271
10-0.10439-0.7950.214924
110.1360671.03630.152192
12-0.218277-1.66230.050919
13-0.160639-1.22340.113065
140.0393310.29950.382802
150.1167440.88910.188811
160.0365830.27860.39077
17-0.076071-0.57930.282303
18-0.044974-0.34250.366602
190.015450.11770.453371
20-0.049806-0.37930.352922
21-0.165972-1.2640.105643
22-0.103055-0.78480.217869
23-0.061159-0.46580.321562
24-0.006855-0.05220.479273
25-0.01878-0.1430.443383
26-0.160985-1.2260.112572
27-0.143407-1.09220.13964
28-0.034695-0.26420.396269
290.0681870.51930.302765
30-0.007392-0.05630.477649
310.0952150.72510.235642
320.0654720.49860.309966
33-0.013106-0.09980.460419
34-0.044452-0.33850.36809
350.0274230.20880.41765
36-0.09373-0.71380.239099

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.183659 & 1.3987 & 0.083613 \tabularnewline
2 & 0.099025 & 0.7542 & 0.226905 \tabularnewline
3 & 0.287214 & 2.1874 & 0.016381 \tabularnewline
4 & 0.04283 & 0.3262 & 0.372731 \tabularnewline
5 & -0.01576 & -0.12 & 0.452438 \tabularnewline
6 & 0.069865 & 0.5321 & 0.298354 \tabularnewline
7 & -0.040825 & -0.3109 & 0.37849 \tabularnewline
8 & 0.172572 & 1.3143 & 0.096964 \tabularnewline
9 & -0.143028 & -1.0893 & 0.140271 \tabularnewline
10 & -0.10439 & -0.795 & 0.214924 \tabularnewline
11 & 0.136067 & 1.0363 & 0.152192 \tabularnewline
12 & -0.218277 & -1.6623 & 0.050919 \tabularnewline
13 & -0.160639 & -1.2234 & 0.113065 \tabularnewline
14 & 0.039331 & 0.2995 & 0.382802 \tabularnewline
15 & 0.116744 & 0.8891 & 0.188811 \tabularnewline
16 & 0.036583 & 0.2786 & 0.39077 \tabularnewline
17 & -0.076071 & -0.5793 & 0.282303 \tabularnewline
18 & -0.044974 & -0.3425 & 0.366602 \tabularnewline
19 & 0.01545 & 0.1177 & 0.453371 \tabularnewline
20 & -0.049806 & -0.3793 & 0.352922 \tabularnewline
21 & -0.165972 & -1.264 & 0.105643 \tabularnewline
22 & -0.103055 & -0.7848 & 0.217869 \tabularnewline
23 & -0.061159 & -0.4658 & 0.321562 \tabularnewline
24 & -0.006855 & -0.0522 & 0.479273 \tabularnewline
25 & -0.01878 & -0.143 & 0.443383 \tabularnewline
26 & -0.160985 & -1.226 & 0.112572 \tabularnewline
27 & -0.143407 & -1.0922 & 0.13964 \tabularnewline
28 & -0.034695 & -0.2642 & 0.396269 \tabularnewline
29 & 0.068187 & 0.5193 & 0.302765 \tabularnewline
30 & -0.007392 & -0.0563 & 0.477649 \tabularnewline
31 & 0.095215 & 0.7251 & 0.235642 \tabularnewline
32 & 0.065472 & 0.4986 & 0.309966 \tabularnewline
33 & -0.013106 & -0.0998 & 0.460419 \tabularnewline
34 & -0.044452 & -0.3385 & 0.36809 \tabularnewline
35 & 0.027423 & 0.2088 & 0.41765 \tabularnewline
36 & -0.09373 & -0.7138 & 0.239099 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115778&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]0.183659[/C][C]1.3987[/C][C]0.083613[/C][/ROW]
[ROW][C]2[/C][C]0.099025[/C][C]0.7542[/C][C]0.226905[/C][/ROW]
[ROW][C]3[/C][C]0.287214[/C][C]2.1874[/C][C]0.016381[/C][/ROW]
[ROW][C]4[/C][C]0.04283[/C][C]0.3262[/C][C]0.372731[/C][/ROW]
[ROW][C]5[/C][C]-0.01576[/C][C]-0.12[/C][C]0.452438[/C][/ROW]
[ROW][C]6[/C][C]0.069865[/C][C]0.5321[/C][C]0.298354[/C][/ROW]
[ROW][C]7[/C][C]-0.040825[/C][C]-0.3109[/C][C]0.37849[/C][/ROW]
[ROW][C]8[/C][C]0.172572[/C][C]1.3143[/C][C]0.096964[/C][/ROW]
[ROW][C]9[/C][C]-0.143028[/C][C]-1.0893[/C][C]0.140271[/C][/ROW]
[ROW][C]10[/C][C]-0.10439[/C][C]-0.795[/C][C]0.214924[/C][/ROW]
[ROW][C]11[/C][C]0.136067[/C][C]1.0363[/C][C]0.152192[/C][/ROW]
[ROW][C]12[/C][C]-0.218277[/C][C]-1.6623[/C][C]0.050919[/C][/ROW]
[ROW][C]13[/C][C]-0.160639[/C][C]-1.2234[/C][C]0.113065[/C][/ROW]
[ROW][C]14[/C][C]0.039331[/C][C]0.2995[/C][C]0.382802[/C][/ROW]
[ROW][C]15[/C][C]0.116744[/C][C]0.8891[/C][C]0.188811[/C][/ROW]
[ROW][C]16[/C][C]0.036583[/C][C]0.2786[/C][C]0.39077[/C][/ROW]
[ROW][C]17[/C][C]-0.076071[/C][C]-0.5793[/C][C]0.282303[/C][/ROW]
[ROW][C]18[/C][C]-0.044974[/C][C]-0.3425[/C][C]0.366602[/C][/ROW]
[ROW][C]19[/C][C]0.01545[/C][C]0.1177[/C][C]0.453371[/C][/ROW]
[ROW][C]20[/C][C]-0.049806[/C][C]-0.3793[/C][C]0.352922[/C][/ROW]
[ROW][C]21[/C][C]-0.165972[/C][C]-1.264[/C][C]0.105643[/C][/ROW]
[ROW][C]22[/C][C]-0.103055[/C][C]-0.7848[/C][C]0.217869[/C][/ROW]
[ROW][C]23[/C][C]-0.061159[/C][C]-0.4658[/C][C]0.321562[/C][/ROW]
[ROW][C]24[/C][C]-0.006855[/C][C]-0.0522[/C][C]0.479273[/C][/ROW]
[ROW][C]25[/C][C]-0.01878[/C][C]-0.143[/C][C]0.443383[/C][/ROW]
[ROW][C]26[/C][C]-0.160985[/C][C]-1.226[/C][C]0.112572[/C][/ROW]
[ROW][C]27[/C][C]-0.143407[/C][C]-1.0922[/C][C]0.13964[/C][/ROW]
[ROW][C]28[/C][C]-0.034695[/C][C]-0.2642[/C][C]0.396269[/C][/ROW]
[ROW][C]29[/C][C]0.068187[/C][C]0.5193[/C][C]0.302765[/C][/ROW]
[ROW][C]30[/C][C]-0.007392[/C][C]-0.0563[/C][C]0.477649[/C][/ROW]
[ROW][C]31[/C][C]0.095215[/C][C]0.7251[/C][C]0.235642[/C][/ROW]
[ROW][C]32[/C][C]0.065472[/C][C]0.4986[/C][C]0.309966[/C][/ROW]
[ROW][C]33[/C][C]-0.013106[/C][C]-0.0998[/C][C]0.460419[/C][/ROW]
[ROW][C]34[/C][C]-0.044452[/C][C]-0.3385[/C][C]0.36809[/C][/ROW]
[ROW][C]35[/C][C]0.027423[/C][C]0.2088[/C][C]0.41765[/C][/ROW]
[ROW][C]36[/C][C]-0.09373[/C][C]-0.7138[/C][C]0.239099[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115778&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115778&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
10.1836591.39870.083613
20.0990250.75420.226905
30.2872142.18740.016381
40.042830.32620.372731
5-0.01576-0.120.452438
60.0698650.53210.298354
7-0.040825-0.31090.37849
80.1725721.31430.096964
9-0.143028-1.08930.140271
10-0.10439-0.7950.214924
110.1360671.03630.152192
12-0.218277-1.66230.050919
13-0.160639-1.22340.113065
140.0393310.29950.382802
150.1167440.88910.188811
160.0365830.27860.39077
17-0.076071-0.57930.282303
18-0.044974-0.34250.366602
190.015450.11770.453371
20-0.049806-0.37930.352922
21-0.165972-1.2640.105643
22-0.103055-0.78480.217869
23-0.061159-0.46580.321562
24-0.006855-0.05220.479273
25-0.01878-0.1430.443383
26-0.160985-1.2260.112572
27-0.143407-1.09220.13964
28-0.034695-0.26420.396269
290.0681870.51930.302765
30-0.007392-0.05630.477649
310.0952150.72510.235642
320.0654720.49860.309966
33-0.013106-0.09980.460419
34-0.044452-0.33850.36809
350.0274230.20880.41765
36-0.09373-0.71380.239099


Figures (Output of Computation)

Input Parameters & R Code

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