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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 computationSat, 19 Dec 2009 15:29:28 -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/19/t12612619148qutdtmrkp4l1iz.htm/, Retrieved Fri, 03 May 2024 19:16:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69762, Retrieved Fri, 03 May 2024 19:16:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsShw Paper; stationair maken via ACF D=1
Estimated Impact121

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] [Ws8.2ACF2] [2009-11-25 19:27:24] [e0fc65a5811681d807296d590d5b45de]
-    D            [(Partial) Autocorrelation Function] [Paper; stationair...] [2009-12-19 22:29:28] [51108381f3361ca8af49c4f74052c840] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
152,60
153,32
165,50
139,18
136,53
115,92
96,65
83,77
84,66
106,03
86,92
54,66
151,66
121,27
132,95
119,64
122,16
117,44
106,69
87,45
80,98
110,30
87,01
55,73
146,00
137,54
138,54
135,62
107,27
99,04
91,36
68,35
82,59
98,41
71,25
47,58
130,83
113,60
125,69
113,60
97,12
104,43
91,84
75,11
89,24
110,23
78,42
68,45
122,81
129,66
159,06
139,03
102,16
113,59
81,46
77,36
87,57
101,23
87,21
64,94
133,12
117,99
135,90
125,67
108,03
128,31
84,74
86,38
92,24
95,83
92,33
54,27

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=69762&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=69762&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69762&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
10.5269234.08156.7e-05
20.3420722.64970.005142
30.1452281.12490.132549
40.0295910.22920.409741
50.0725450.56190.288129
60.0814190.63070.265325
70.028050.21730.414365
80.029940.23190.408695
90.0208940.16180.435987
10-0.194613-1.50750.06847
11-0.34585-2.67890.004758
12-0.445322-3.44940.000517
13-0.325296-2.51970.007212
14-0.12884-0.9980.161146
150.0395710.30650.380136
16-0.077499-0.60030.275281
170.0266230.20620.418659
180.0126210.09780.461225
19-0.049583-0.38410.351143
200.0507270.39290.347882
21-0.030367-0.23520.407419
220.0635560.49230.312151
230.2445091.8940.031527
240.2767642.14380.018056
250.2159281.67260.04981
260.168351.3040.098601
27-0.023495-0.1820.4281
28-0.017921-0.13880.445032
29-0.071811-0.55620.290055
30-0.122066-0.94550.174092
31-0.089738-0.69510.244834
32-0.009644-0.07470.47035
330.0068040.05270.479071
34-0.101933-0.78960.216444
35-0.14557-1.12760.131993
36-0.31385-2.43110.009029

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.526923 & 4.0815 & 6.7e-05 \tabularnewline
2 & 0.342072 & 2.6497 & 0.005142 \tabularnewline
3 & 0.145228 & 1.1249 & 0.132549 \tabularnewline
4 & 0.029591 & 0.2292 & 0.409741 \tabularnewline
5 & 0.072545 & 0.5619 & 0.288129 \tabularnewline
6 & 0.081419 & 0.6307 & 0.265325 \tabularnewline
7 & 0.02805 & 0.2173 & 0.414365 \tabularnewline
8 & 0.02994 & 0.2319 & 0.408695 \tabularnewline
9 & 0.020894 & 0.1618 & 0.435987 \tabularnewline
10 & -0.194613 & -1.5075 & 0.06847 \tabularnewline
11 & -0.34585 & -2.6789 & 0.004758 \tabularnewline
12 & -0.445322 & -3.4494 & 0.000517 \tabularnewline
13 & -0.325296 & -2.5197 & 0.007212 \tabularnewline
14 & -0.12884 & -0.998 & 0.161146 \tabularnewline
15 & 0.039571 & 0.3065 & 0.380136 \tabularnewline
16 & -0.077499 & -0.6003 & 0.275281 \tabularnewline
17 & 0.026623 & 0.2062 & 0.418659 \tabularnewline
18 & 0.012621 & 0.0978 & 0.461225 \tabularnewline
19 & -0.049583 & -0.3841 & 0.351143 \tabularnewline
20 & 0.050727 & 0.3929 & 0.347882 \tabularnewline
21 & -0.030367 & -0.2352 & 0.407419 \tabularnewline
22 & 0.063556 & 0.4923 & 0.312151 \tabularnewline
23 & 0.244509 & 1.894 & 0.031527 \tabularnewline
24 & 0.276764 & 2.1438 & 0.018056 \tabularnewline
25 & 0.215928 & 1.6726 & 0.04981 \tabularnewline
26 & 0.16835 & 1.304 & 0.098601 \tabularnewline
27 & -0.023495 & -0.182 & 0.4281 \tabularnewline
28 & -0.017921 & -0.1388 & 0.445032 \tabularnewline
29 & -0.071811 & -0.5562 & 0.290055 \tabularnewline
30 & -0.122066 & -0.9455 & 0.174092 \tabularnewline
31 & -0.089738 & -0.6951 & 0.244834 \tabularnewline
32 & -0.009644 & -0.0747 & 0.47035 \tabularnewline
33 & 0.006804 & 0.0527 & 0.479071 \tabularnewline
34 & -0.101933 & -0.7896 & 0.216444 \tabularnewline
35 & -0.14557 & -1.1276 & 0.131993 \tabularnewline
36 & -0.31385 & -2.4311 & 0.009029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69762&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]0.526923[/C][C]4.0815[/C][C]6.7e-05[/C][/ROW]
[ROW][C]2[/C][C]0.342072[/C][C]2.6497[/C][C]0.005142[/C][/ROW]
[ROW][C]3[/C][C]0.145228[/C][C]1.1249[/C][C]0.132549[/C][/ROW]
[ROW][C]4[/C][C]0.029591[/C][C]0.2292[/C][C]0.409741[/C][/ROW]
[ROW][C]5[/C][C]0.072545[/C][C]0.5619[/C][C]0.288129[/C][/ROW]
[ROW][C]6[/C][C]0.081419[/C][C]0.6307[/C][C]0.265325[/C][/ROW]
[ROW][C]7[/C][C]0.02805[/C][C]0.2173[/C][C]0.414365[/C][/ROW]
[ROW][C]8[/C][C]0.02994[/C][C]0.2319[/C][C]0.408695[/C][/ROW]
[ROW][C]9[/C][C]0.020894[/C][C]0.1618[/C][C]0.435987[/C][/ROW]
[ROW][C]10[/C][C]-0.194613[/C][C]-1.5075[/C][C]0.06847[/C][/ROW]
[ROW][C]11[/C][C]-0.34585[/C][C]-2.6789[/C][C]0.004758[/C][/ROW]
[ROW][C]12[/C][C]-0.445322[/C][C]-3.4494[/C][C]0.000517[/C][/ROW]
[ROW][C]13[/C][C]-0.325296[/C][C]-2.5197[/C][C]0.007212[/C][/ROW]
[ROW][C]14[/C][C]-0.12884[/C][C]-0.998[/C][C]0.161146[/C][/ROW]
[ROW][C]15[/C][C]0.039571[/C][C]0.3065[/C][C]0.380136[/C][/ROW]
[ROW][C]16[/C][C]-0.077499[/C][C]-0.6003[/C][C]0.275281[/C][/ROW]
[ROW][C]17[/C][C]0.026623[/C][C]0.2062[/C][C]0.418659[/C][/ROW]
[ROW][C]18[/C][C]0.012621[/C][C]0.0978[/C][C]0.461225[/C][/ROW]
[ROW][C]19[/C][C]-0.049583[/C][C]-0.3841[/C][C]0.351143[/C][/ROW]
[ROW][C]20[/C][C]0.050727[/C][C]0.3929[/C][C]0.347882[/C][/ROW]
[ROW][C]21[/C][C]-0.030367[/C][C]-0.2352[/C][C]0.407419[/C][/ROW]
[ROW][C]22[/C][C]0.063556[/C][C]0.4923[/C][C]0.312151[/C][/ROW]
[ROW][C]23[/C][C]0.244509[/C][C]1.894[/C][C]0.031527[/C][/ROW]
[ROW][C]24[/C][C]0.276764[/C][C]2.1438[/C][C]0.018056[/C][/ROW]
[ROW][C]25[/C][C]0.215928[/C][C]1.6726[/C][C]0.04981[/C][/ROW]
[ROW][C]26[/C][C]0.16835[/C][C]1.304[/C][C]0.098601[/C][/ROW]
[ROW][C]27[/C][C]-0.023495[/C][C]-0.182[/C][C]0.4281[/C][/ROW]
[ROW][C]28[/C][C]-0.017921[/C][C]-0.1388[/C][C]0.445032[/C][/ROW]
[ROW][C]29[/C][C]-0.071811[/C][C]-0.5562[/C][C]0.290055[/C][/ROW]
[ROW][C]30[/C][C]-0.122066[/C][C]-0.9455[/C][C]0.174092[/C][/ROW]
[ROW][C]31[/C][C]-0.089738[/C][C]-0.6951[/C][C]0.244834[/C][/ROW]
[ROW][C]32[/C][C]-0.009644[/C][C]-0.0747[/C][C]0.47035[/C][/ROW]
[ROW][C]33[/C][C]0.006804[/C][C]0.0527[/C][C]0.479071[/C][/ROW]
[ROW][C]34[/C][C]-0.101933[/C][C]-0.7896[/C][C]0.216444[/C][/ROW]
[ROW][C]35[/C][C]-0.14557[/C][C]-1.1276[/C][C]0.131993[/C][/ROW]
[ROW][C]36[/C][C]-0.31385[/C][C]-2.4311[/C][C]0.009029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69762&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69762&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
10.5269234.08156.7e-05
20.3420722.64970.005142
30.1452281.12490.132549
40.0295910.22920.409741
50.0725450.56190.288129
60.0814190.63070.265325
70.028050.21730.414365
80.029940.23190.408695
90.0208940.16180.435987
10-0.194613-1.50750.06847
11-0.34585-2.67890.004758
12-0.445322-3.44940.000517
13-0.325296-2.51970.007212
14-0.12884-0.9980.161146
150.0395710.30650.380136
16-0.077499-0.60030.275281
170.0266230.20620.418659
180.0126210.09780.461225
19-0.049583-0.38410.351143
200.0507270.39290.347882
21-0.030367-0.23520.407419
220.0635560.49230.312151
230.2445091.8940.031527
240.2767642.14380.018056
250.2159281.67260.04981
260.168351.3040.098601
27-0.023495-0.1820.4281
28-0.017921-0.13880.445032
29-0.071811-0.55620.290055
30-0.122066-0.94550.174092
31-0.089738-0.69510.244834
32-0.009644-0.07470.47035
330.0068040.05270.479071
34-0.101933-0.78960.216444
35-0.14557-1.12760.131993
36-0.31385-2.43110.009029






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5269234.08156.7e-05
20.0891870.69080.246165
3-0.092013-0.71270.239388
4-0.054085-0.41890.338376
50.125310.97060.167811
60.0383520.29710.383718
7-0.085253-0.66040.255773
80.019720.15280.439553
90.037140.28770.38729
10-0.309419-2.39670.009837
11-0.267052-2.06860.021451
12-0.148601-1.15110.127137
130.1108030.85830.197078
140.1197670.92770.178637
150.1270920.98450.164424
16-0.22008-1.70470.046709
170.1888171.46260.074402
180.092690.7180.237779
19-0.12749-0.98750.163674
200.0816020.63210.264867
21-0.088204-0.68320.248547
22-0.037014-0.28670.387661
230.094980.73570.232386
240.03350.25950.398073
250.0682590.52870.29947
260.0742860.57540.28358
27-0.17795-1.37840.086599
28-0.021375-0.16560.434525
29-0.087214-0.67560.250959
30-0.061135-0.47350.318771
310.0343490.26610.395549
320.0088110.06820.472908
330.0561310.43480.332637
34-0.114286-0.88530.189777
35-0.013499-0.10460.458537
360.0032750.02540.489921

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.526923 & 4.0815 & 6.7e-05 \tabularnewline
2 & 0.089187 & 0.6908 & 0.246165 \tabularnewline
3 & -0.092013 & -0.7127 & 0.239388 \tabularnewline
4 & -0.054085 & -0.4189 & 0.338376 \tabularnewline
5 & 0.12531 & 0.9706 & 0.167811 \tabularnewline
6 & 0.038352 & 0.2971 & 0.383718 \tabularnewline
7 & -0.085253 & -0.6604 & 0.255773 \tabularnewline
8 & 0.01972 & 0.1528 & 0.439553 \tabularnewline
9 & 0.03714 & 0.2877 & 0.38729 \tabularnewline
10 & -0.309419 & -2.3967 & 0.009837 \tabularnewline
11 & -0.267052 & -2.0686 & 0.021451 \tabularnewline
12 & -0.148601 & -1.1511 & 0.127137 \tabularnewline
13 & 0.110803 & 0.8583 & 0.197078 \tabularnewline
14 & 0.119767 & 0.9277 & 0.178637 \tabularnewline
15 & 0.127092 & 0.9845 & 0.164424 \tabularnewline
16 & -0.22008 & -1.7047 & 0.046709 \tabularnewline
17 & 0.188817 & 1.4626 & 0.074402 \tabularnewline
18 & 0.09269 & 0.718 & 0.237779 \tabularnewline
19 & -0.12749 & -0.9875 & 0.163674 \tabularnewline
20 & 0.081602 & 0.6321 & 0.264867 \tabularnewline
21 & -0.088204 & -0.6832 & 0.248547 \tabularnewline
22 & -0.037014 & -0.2867 & 0.387661 \tabularnewline
23 & 0.09498 & 0.7357 & 0.232386 \tabularnewline
24 & 0.0335 & 0.2595 & 0.398073 \tabularnewline
25 & 0.068259 & 0.5287 & 0.29947 \tabularnewline
26 & 0.074286 & 0.5754 & 0.28358 \tabularnewline
27 & -0.17795 & -1.3784 & 0.086599 \tabularnewline
28 & -0.021375 & -0.1656 & 0.434525 \tabularnewline
29 & -0.087214 & -0.6756 & 0.250959 \tabularnewline
30 & -0.061135 & -0.4735 & 0.318771 \tabularnewline
31 & 0.034349 & 0.2661 & 0.395549 \tabularnewline
32 & 0.008811 & 0.0682 & 0.472908 \tabularnewline
33 & 0.056131 & 0.4348 & 0.332637 \tabularnewline
34 & -0.114286 & -0.8853 & 0.189777 \tabularnewline
35 & -0.013499 & -0.1046 & 0.458537 \tabularnewline
36 & 0.003275 & 0.0254 & 0.489921 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69762&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]0.526923[/C][C]4.0815[/C][C]6.7e-05[/C][/ROW]
[ROW][C]2[/C][C]0.089187[/C][C]0.6908[/C][C]0.246165[/C][/ROW]
[ROW][C]3[/C][C]-0.092013[/C][C]-0.7127[/C][C]0.239388[/C][/ROW]
[ROW][C]4[/C][C]-0.054085[/C][C]-0.4189[/C][C]0.338376[/C][/ROW]
[ROW][C]5[/C][C]0.12531[/C][C]0.9706[/C][C]0.167811[/C][/ROW]
[ROW][C]6[/C][C]0.038352[/C][C]0.2971[/C][C]0.383718[/C][/ROW]
[ROW][C]7[/C][C]-0.085253[/C][C]-0.6604[/C][C]0.255773[/C][/ROW]
[ROW][C]8[/C][C]0.01972[/C][C]0.1528[/C][C]0.439553[/C][/ROW]
[ROW][C]9[/C][C]0.03714[/C][C]0.2877[/C][C]0.38729[/C][/ROW]
[ROW][C]10[/C][C]-0.309419[/C][C]-2.3967[/C][C]0.009837[/C][/ROW]
[ROW][C]11[/C][C]-0.267052[/C][C]-2.0686[/C][C]0.021451[/C][/ROW]
[ROW][C]12[/C][C]-0.148601[/C][C]-1.1511[/C][C]0.127137[/C][/ROW]
[ROW][C]13[/C][C]0.110803[/C][C]0.8583[/C][C]0.197078[/C][/ROW]
[ROW][C]14[/C][C]0.119767[/C][C]0.9277[/C][C]0.178637[/C][/ROW]
[ROW][C]15[/C][C]0.127092[/C][C]0.9845[/C][C]0.164424[/C][/ROW]
[ROW][C]16[/C][C]-0.22008[/C][C]-1.7047[/C][C]0.046709[/C][/ROW]
[ROW][C]17[/C][C]0.188817[/C][C]1.4626[/C][C]0.074402[/C][/ROW]
[ROW][C]18[/C][C]0.09269[/C][C]0.718[/C][C]0.237779[/C][/ROW]
[ROW][C]19[/C][C]-0.12749[/C][C]-0.9875[/C][C]0.163674[/C][/ROW]
[ROW][C]20[/C][C]0.081602[/C][C]0.6321[/C][C]0.264867[/C][/ROW]
[ROW][C]21[/C][C]-0.088204[/C][C]-0.6832[/C][C]0.248547[/C][/ROW]
[ROW][C]22[/C][C]-0.037014[/C][C]-0.2867[/C][C]0.387661[/C][/ROW]
[ROW][C]23[/C][C]0.09498[/C][C]0.7357[/C][C]0.232386[/C][/ROW]
[ROW][C]24[/C][C]0.0335[/C][C]0.2595[/C][C]0.398073[/C][/ROW]
[ROW][C]25[/C][C]0.068259[/C][C]0.5287[/C][C]0.29947[/C][/ROW]
[ROW][C]26[/C][C]0.074286[/C][C]0.5754[/C][C]0.28358[/C][/ROW]
[ROW][C]27[/C][C]-0.17795[/C][C]-1.3784[/C][C]0.086599[/C][/ROW]
[ROW][C]28[/C][C]-0.021375[/C][C]-0.1656[/C][C]0.434525[/C][/ROW]
[ROW][C]29[/C][C]-0.087214[/C][C]-0.6756[/C][C]0.250959[/C][/ROW]
[ROW][C]30[/C][C]-0.061135[/C][C]-0.4735[/C][C]0.318771[/C][/ROW]
[ROW][C]31[/C][C]0.034349[/C][C]0.2661[/C][C]0.395549[/C][/ROW]
[ROW][C]32[/C][C]0.008811[/C][C]0.0682[/C][C]0.472908[/C][/ROW]
[ROW][C]33[/C][C]0.056131[/C][C]0.4348[/C][C]0.332637[/C][/ROW]
[ROW][C]34[/C][C]-0.114286[/C][C]-0.8853[/C][C]0.189777[/C][/ROW]
[ROW][C]35[/C][C]-0.013499[/C][C]-0.1046[/C][C]0.458537[/C][/ROW]
[ROW][C]36[/C][C]0.003275[/C][C]0.0254[/C][C]0.489921[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69762&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69762&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
10.5269234.08156.7e-05
20.0891870.69080.246165
3-0.092013-0.71270.239388
4-0.054085-0.41890.338376
50.125310.97060.167811
60.0383520.29710.383718
7-0.085253-0.66040.255773
80.019720.15280.439553
90.037140.28770.38729
10-0.309419-2.39670.009837
11-0.267052-2.06860.021451
12-0.148601-1.15110.127137
130.1108030.85830.197078
140.1197670.92770.178637
150.1270920.98450.164424
16-0.22008-1.70470.046709
170.1888171.46260.074402
180.092690.7180.237779
19-0.12749-0.98750.163674
200.0816020.63210.264867
21-0.088204-0.68320.248547
22-0.037014-0.28670.387661
230.094980.73570.232386
240.03350.25950.398073
250.0682590.52870.29947
260.0742860.57540.28358
27-0.17795-1.37840.086599
28-0.021375-0.16560.434525
29-0.087214-0.67560.250959
30-0.061135-0.47350.318771
310.0343490.26610.395549
320.0088110.06820.472908
330.0561310.43480.332637
34-0.114286-0.88530.189777
35-0.013499-0.10460.458537
360.0032750.02540.489921


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')