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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 computationThu, 17 Dec 2009 13:48:17 -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/17/t1261083005ucs0o2niokdaq44.htm/, Retrieved Tue, 30 Apr 2024 02:40:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69106, Retrieved Tue, 30 Apr 2024 02:40:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
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] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Thee] [2009-12-17 09:19:07] [7773f496f69461f4a67891f0ef752622]
-   PD                    [(Partial) Autocorrelation Function] [appelen Golden au...] [2009-12-17 20:48:17] [5c2088b06970f9a7d6fea063ee8d5871] [Current]
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Dataseries X:
1.77
1.76
1.77
1.95
1.98
1.93
1.94
1.92
1.94
1.92
1.92
1.94
1.91
1.88
1.98
2.4
2.47
2.22
1.98
1.89
1.87
1.88
1.86
1.81
1.79
1.78
1.73
1.88
1.91
1.9
1.84
1.85
1.83
1.82
1.82
1.81
1.75
1.74
1.73
1.96
2.07
1.96
1.87
1.84
1.81
1.78
1.72
1.73
1.64
1.61
1.63
1.92
1.88
1.68
1.58
1.49
1.46
1.44
1.44
1.42
1.4
1.38
1.36
1.48
1.56
1.51
1.51
1.42
1.4
1.38
1.35
1.29




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=69106&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=69106&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69106&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' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4036973.10090.001479
2-0.220991-1.69750.047439
3-0.355887-2.73360.004128
4-0.095627-0.73450.232769
5-0.012774-0.09810.461087
6-0.010632-0.08170.467594
7-0.003443-0.02640.489496
80.0847740.65120.258736
90.2396981.84120.035314
100.1646491.26470.105477
11-0.195923-1.50490.068841
12-0.540401-4.15095.4e-05
13-0.30738-2.3610.010773
140.0727490.55880.289207
150.1504121.15530.126305
160.0489210.37580.354218
17-0.035863-0.27550.39196
180.019260.14790.441449
190.0342030.26270.396841
200.0005170.0040.498424
21-0.044689-0.34330.366309
22-0.068115-0.52320.301397
23-0.11793-0.90580.184353
24-0.028085-0.21570.414973
250.1258610.96680.168805
260.1129460.86760.194577
270.0550780.42310.336894
280.0379150.29120.385949
290.0695530.53420.297588
300.0308840.23720.406652
31-0.025854-0.19860.421635
32-0.060104-0.46170.323008
33-0.103641-0.79610.214588
340.0149970.11520.45434
350.2613622.00760.024639
360.2516231.93280.029035

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.403697 & 3.1009 & 0.001479 \tabularnewline
2 & -0.220991 & -1.6975 & 0.047439 \tabularnewline
3 & -0.355887 & -2.7336 & 0.004128 \tabularnewline
4 & -0.095627 & -0.7345 & 0.232769 \tabularnewline
5 & -0.012774 & -0.0981 & 0.461087 \tabularnewline
6 & -0.010632 & -0.0817 & 0.467594 \tabularnewline
7 & -0.003443 & -0.0264 & 0.489496 \tabularnewline
8 & 0.084774 & 0.6512 & 0.258736 \tabularnewline
9 & 0.239698 & 1.8412 & 0.035314 \tabularnewline
10 & 0.164649 & 1.2647 & 0.105477 \tabularnewline
11 & -0.195923 & -1.5049 & 0.068841 \tabularnewline
12 & -0.540401 & -4.1509 & 5.4e-05 \tabularnewline
13 & -0.30738 & -2.361 & 0.010773 \tabularnewline
14 & 0.072749 & 0.5588 & 0.289207 \tabularnewline
15 & 0.150412 & 1.1553 & 0.126305 \tabularnewline
16 & 0.048921 & 0.3758 & 0.354218 \tabularnewline
17 & -0.035863 & -0.2755 & 0.39196 \tabularnewline
18 & 0.01926 & 0.1479 & 0.441449 \tabularnewline
19 & 0.034203 & 0.2627 & 0.396841 \tabularnewline
20 & 0.000517 & 0.004 & 0.498424 \tabularnewline
21 & -0.044689 & -0.3433 & 0.366309 \tabularnewline
22 & -0.068115 & -0.5232 & 0.301397 \tabularnewline
23 & -0.11793 & -0.9058 & 0.184353 \tabularnewline
24 & -0.028085 & -0.2157 & 0.414973 \tabularnewline
25 & 0.125861 & 0.9668 & 0.168805 \tabularnewline
26 & 0.112946 & 0.8676 & 0.194577 \tabularnewline
27 & 0.055078 & 0.4231 & 0.336894 \tabularnewline
28 & 0.037915 & 0.2912 & 0.385949 \tabularnewline
29 & 0.069553 & 0.5342 & 0.297588 \tabularnewline
30 & 0.030884 & 0.2372 & 0.406652 \tabularnewline
31 & -0.025854 & -0.1986 & 0.421635 \tabularnewline
32 & -0.060104 & -0.4617 & 0.323008 \tabularnewline
33 & -0.103641 & -0.7961 & 0.214588 \tabularnewline
34 & 0.014997 & 0.1152 & 0.45434 \tabularnewline
35 & 0.261362 & 2.0076 & 0.024639 \tabularnewline
36 & 0.251623 & 1.9328 & 0.029035 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69106&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]0.403697[/C][C]3.1009[/C][C]0.001479[/C][/ROW]
[ROW][C]2[/C][C]-0.220991[/C][C]-1.6975[/C][C]0.047439[/C][/ROW]
[ROW][C]3[/C][C]-0.355887[/C][C]-2.7336[/C][C]0.004128[/C][/ROW]
[ROW][C]4[/C][C]-0.095627[/C][C]-0.7345[/C][C]0.232769[/C][/ROW]
[ROW][C]5[/C][C]-0.012774[/C][C]-0.0981[/C][C]0.461087[/C][/ROW]
[ROW][C]6[/C][C]-0.010632[/C][C]-0.0817[/C][C]0.467594[/C][/ROW]
[ROW][C]7[/C][C]-0.003443[/C][C]-0.0264[/C][C]0.489496[/C][/ROW]
[ROW][C]8[/C][C]0.084774[/C][C]0.6512[/C][C]0.258736[/C][/ROW]
[ROW][C]9[/C][C]0.239698[/C][C]1.8412[/C][C]0.035314[/C][/ROW]
[ROW][C]10[/C][C]0.164649[/C][C]1.2647[/C][C]0.105477[/C][/ROW]
[ROW][C]11[/C][C]-0.195923[/C][C]-1.5049[/C][C]0.068841[/C][/ROW]
[ROW][C]12[/C][C]-0.540401[/C][C]-4.1509[/C][C]5.4e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.30738[/C][C]-2.361[/C][C]0.010773[/C][/ROW]
[ROW][C]14[/C][C]0.072749[/C][C]0.5588[/C][C]0.289207[/C][/ROW]
[ROW][C]15[/C][C]0.150412[/C][C]1.1553[/C][C]0.126305[/C][/ROW]
[ROW][C]16[/C][C]0.048921[/C][C]0.3758[/C][C]0.354218[/C][/ROW]
[ROW][C]17[/C][C]-0.035863[/C][C]-0.2755[/C][C]0.39196[/C][/ROW]
[ROW][C]18[/C][C]0.01926[/C][C]0.1479[/C][C]0.441449[/C][/ROW]
[ROW][C]19[/C][C]0.034203[/C][C]0.2627[/C][C]0.396841[/C][/ROW]
[ROW][C]20[/C][C]0.000517[/C][C]0.004[/C][C]0.498424[/C][/ROW]
[ROW][C]21[/C][C]-0.044689[/C][C]-0.3433[/C][C]0.366309[/C][/ROW]
[ROW][C]22[/C][C]-0.068115[/C][C]-0.5232[/C][C]0.301397[/C][/ROW]
[ROW][C]23[/C][C]-0.11793[/C][C]-0.9058[/C][C]0.184353[/C][/ROW]
[ROW][C]24[/C][C]-0.028085[/C][C]-0.2157[/C][C]0.414973[/C][/ROW]
[ROW][C]25[/C][C]0.125861[/C][C]0.9668[/C][C]0.168805[/C][/ROW]
[ROW][C]26[/C][C]0.112946[/C][C]0.8676[/C][C]0.194577[/C][/ROW]
[ROW][C]27[/C][C]0.055078[/C][C]0.4231[/C][C]0.336894[/C][/ROW]
[ROW][C]28[/C][C]0.037915[/C][C]0.2912[/C][C]0.385949[/C][/ROW]
[ROW][C]29[/C][C]0.069553[/C][C]0.5342[/C][C]0.297588[/C][/ROW]
[ROW][C]30[/C][C]0.030884[/C][C]0.2372[/C][C]0.406652[/C][/ROW]
[ROW][C]31[/C][C]-0.025854[/C][C]-0.1986[/C][C]0.421635[/C][/ROW]
[ROW][C]32[/C][C]-0.060104[/C][C]-0.4617[/C][C]0.323008[/C][/ROW]
[ROW][C]33[/C][C]-0.103641[/C][C]-0.7961[/C][C]0.214588[/C][/ROW]
[ROW][C]34[/C][C]0.014997[/C][C]0.1152[/C][C]0.45434[/C][/ROW]
[ROW][C]35[/C][C]0.261362[/C][C]2.0076[/C][C]0.024639[/C][/ROW]
[ROW][C]36[/C][C]0.251623[/C][C]1.9328[/C][C]0.029035[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69106&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69106&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
10.4036973.10090.001479
2-0.220991-1.69750.047439
3-0.355887-2.73360.004128
4-0.095627-0.73450.232769
5-0.012774-0.09810.461087
6-0.010632-0.08170.467594
7-0.003443-0.02640.489496
80.0847740.65120.258736
90.2396981.84120.035314
100.1646491.26470.105477
11-0.195923-1.50490.068841
12-0.540401-4.15095.4e-05
13-0.30738-2.3610.010773
140.0727490.55880.289207
150.1504121.15530.126305
160.0489210.37580.354218
17-0.035863-0.27550.39196
180.019260.14790.441449
190.0342030.26270.396841
200.0005170.0040.498424
21-0.044689-0.34330.366309
22-0.068115-0.52320.301397
23-0.11793-0.90580.184353
24-0.028085-0.21570.414973
250.1258610.96680.168805
260.1129460.86760.194577
270.0550780.42310.336894
280.0379150.29120.385949
290.0695530.53420.297588
300.0308840.23720.406652
31-0.025854-0.19860.421635
32-0.060104-0.46170.323008
33-0.103641-0.79610.214588
340.0149970.11520.45434
350.2613622.00760.024639
360.2516231.93280.029035







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4036973.10090.001479
2-0.458721-3.52350.000415
3-0.061379-0.47150.319524
40.0536460.41210.340892
5-0.217861-1.67340.04977
60.0319480.24540.403501
7-0.026773-0.20560.418888
80.049580.38080.352349
90.2546021.95560.027624
10-0.057442-0.44120.330333
11-0.223671-1.7180.045516
12-0.33018-2.53620.006937
130.0253140.19440.423251
14-0.118898-0.91330.182409
15-0.186952-1.4360.078141
160.0464840.3570.361165
17-0.211816-1.6270.054535
180.0367020.28190.389498
19-0.027974-0.21490.415305
20-0.010845-0.08330.466946
210.2248551.72710.044687
22-0.117858-0.90530.184499
23-0.327069-2.51230.007375
24-0.150629-1.1570.125967
25-0.007128-0.05480.478261
26-0.139173-1.0690.14471
27-0.024318-0.18680.426233
280.0338860.26030.397777
29-0.064851-0.49810.310123
300.0799820.61440.270671
310.0279880.2150.415261
32-0.008222-0.06320.474929
330.0131340.10090.459991
340.0402430.30910.379162
350.0156360.12010.452404
36-0.108784-0.83560.203381

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.403697 & 3.1009 & 0.001479 \tabularnewline
2 & -0.458721 & -3.5235 & 0.000415 \tabularnewline
3 & -0.061379 & -0.4715 & 0.319524 \tabularnewline
4 & 0.053646 & 0.4121 & 0.340892 \tabularnewline
5 & -0.217861 & -1.6734 & 0.04977 \tabularnewline
6 & 0.031948 & 0.2454 & 0.403501 \tabularnewline
7 & -0.026773 & -0.2056 & 0.418888 \tabularnewline
8 & 0.04958 & 0.3808 & 0.352349 \tabularnewline
9 & 0.254602 & 1.9556 & 0.027624 \tabularnewline
10 & -0.057442 & -0.4412 & 0.330333 \tabularnewline
11 & -0.223671 & -1.718 & 0.045516 \tabularnewline
12 & -0.33018 & -2.5362 & 0.006937 \tabularnewline
13 & 0.025314 & 0.1944 & 0.423251 \tabularnewline
14 & -0.118898 & -0.9133 & 0.182409 \tabularnewline
15 & -0.186952 & -1.436 & 0.078141 \tabularnewline
16 & 0.046484 & 0.357 & 0.361165 \tabularnewline
17 & -0.211816 & -1.627 & 0.054535 \tabularnewline
18 & 0.036702 & 0.2819 & 0.389498 \tabularnewline
19 & -0.027974 & -0.2149 & 0.415305 \tabularnewline
20 & -0.010845 & -0.0833 & 0.466946 \tabularnewline
21 & 0.224855 & 1.7271 & 0.044687 \tabularnewline
22 & -0.117858 & -0.9053 & 0.184499 \tabularnewline
23 & -0.327069 & -2.5123 & 0.007375 \tabularnewline
24 & -0.150629 & -1.157 & 0.125967 \tabularnewline
25 & -0.007128 & -0.0548 & 0.478261 \tabularnewline
26 & -0.139173 & -1.069 & 0.14471 \tabularnewline
27 & -0.024318 & -0.1868 & 0.426233 \tabularnewline
28 & 0.033886 & 0.2603 & 0.397777 \tabularnewline
29 & -0.064851 & -0.4981 & 0.310123 \tabularnewline
30 & 0.079982 & 0.6144 & 0.270671 \tabularnewline
31 & 0.027988 & 0.215 & 0.415261 \tabularnewline
32 & -0.008222 & -0.0632 & 0.474929 \tabularnewline
33 & 0.013134 & 0.1009 & 0.459991 \tabularnewline
34 & 0.040243 & 0.3091 & 0.379162 \tabularnewline
35 & 0.015636 & 0.1201 & 0.452404 \tabularnewline
36 & -0.108784 & -0.8356 & 0.203381 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69106&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]0.403697[/C][C]3.1009[/C][C]0.001479[/C][/ROW]
[ROW][C]2[/C][C]-0.458721[/C][C]-3.5235[/C][C]0.000415[/C][/ROW]
[ROW][C]3[/C][C]-0.061379[/C][C]-0.4715[/C][C]0.319524[/C][/ROW]
[ROW][C]4[/C][C]0.053646[/C][C]0.4121[/C][C]0.340892[/C][/ROW]
[ROW][C]5[/C][C]-0.217861[/C][C]-1.6734[/C][C]0.04977[/C][/ROW]
[ROW][C]6[/C][C]0.031948[/C][C]0.2454[/C][C]0.403501[/C][/ROW]
[ROW][C]7[/C][C]-0.026773[/C][C]-0.2056[/C][C]0.418888[/C][/ROW]
[ROW][C]8[/C][C]0.04958[/C][C]0.3808[/C][C]0.352349[/C][/ROW]
[ROW][C]9[/C][C]0.254602[/C][C]1.9556[/C][C]0.027624[/C][/ROW]
[ROW][C]10[/C][C]-0.057442[/C][C]-0.4412[/C][C]0.330333[/C][/ROW]
[ROW][C]11[/C][C]-0.223671[/C][C]-1.718[/C][C]0.045516[/C][/ROW]
[ROW][C]12[/C][C]-0.33018[/C][C]-2.5362[/C][C]0.006937[/C][/ROW]
[ROW][C]13[/C][C]0.025314[/C][C]0.1944[/C][C]0.423251[/C][/ROW]
[ROW][C]14[/C][C]-0.118898[/C][C]-0.9133[/C][C]0.182409[/C][/ROW]
[ROW][C]15[/C][C]-0.186952[/C][C]-1.436[/C][C]0.078141[/C][/ROW]
[ROW][C]16[/C][C]0.046484[/C][C]0.357[/C][C]0.361165[/C][/ROW]
[ROW][C]17[/C][C]-0.211816[/C][C]-1.627[/C][C]0.054535[/C][/ROW]
[ROW][C]18[/C][C]0.036702[/C][C]0.2819[/C][C]0.389498[/C][/ROW]
[ROW][C]19[/C][C]-0.027974[/C][C]-0.2149[/C][C]0.415305[/C][/ROW]
[ROW][C]20[/C][C]-0.010845[/C][C]-0.0833[/C][C]0.466946[/C][/ROW]
[ROW][C]21[/C][C]0.224855[/C][C]1.7271[/C][C]0.044687[/C][/ROW]
[ROW][C]22[/C][C]-0.117858[/C][C]-0.9053[/C][C]0.184499[/C][/ROW]
[ROW][C]23[/C][C]-0.327069[/C][C]-2.5123[/C][C]0.007375[/C][/ROW]
[ROW][C]24[/C][C]-0.150629[/C][C]-1.157[/C][C]0.125967[/C][/ROW]
[ROW][C]25[/C][C]-0.007128[/C][C]-0.0548[/C][C]0.478261[/C][/ROW]
[ROW][C]26[/C][C]-0.139173[/C][C]-1.069[/C][C]0.14471[/C][/ROW]
[ROW][C]27[/C][C]-0.024318[/C][C]-0.1868[/C][C]0.426233[/C][/ROW]
[ROW][C]28[/C][C]0.033886[/C][C]0.2603[/C][C]0.397777[/C][/ROW]
[ROW][C]29[/C][C]-0.064851[/C][C]-0.4981[/C][C]0.310123[/C][/ROW]
[ROW][C]30[/C][C]0.079982[/C][C]0.6144[/C][C]0.270671[/C][/ROW]
[ROW][C]31[/C][C]0.027988[/C][C]0.215[/C][C]0.415261[/C][/ROW]
[ROW][C]32[/C][C]-0.008222[/C][C]-0.0632[/C][C]0.474929[/C][/ROW]
[ROW][C]33[/C][C]0.013134[/C][C]0.1009[/C][C]0.459991[/C][/ROW]
[ROW][C]34[/C][C]0.040243[/C][C]0.3091[/C][C]0.379162[/C][/ROW]
[ROW][C]35[/C][C]0.015636[/C][C]0.1201[/C][C]0.452404[/C][/ROW]
[ROW][C]36[/C][C]-0.108784[/C][C]-0.8356[/C][C]0.203381[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69106&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69106&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
10.4036973.10090.001479
2-0.458721-3.52350.000415
3-0.061379-0.47150.319524
40.0536460.41210.340892
5-0.217861-1.67340.04977
60.0319480.24540.403501
7-0.026773-0.20560.418888
80.049580.38080.352349
90.2546021.95560.027624
10-0.057442-0.44120.330333
11-0.223671-1.7180.045516
12-0.33018-2.53620.006937
130.0253140.19440.423251
14-0.118898-0.91330.182409
15-0.186952-1.4360.078141
160.0464840.3570.361165
17-0.211816-1.6270.054535
180.0367020.28190.389498
19-0.027974-0.21490.415305
20-0.010845-0.08330.466946
210.2248551.72710.044687
22-0.117858-0.90530.184499
23-0.327069-2.51230.007375
24-0.150629-1.1570.125967
25-0.007128-0.05480.478261
26-0.139173-1.0690.14471
27-0.024318-0.18680.426233
280.0338860.26030.397777
29-0.064851-0.49810.310123
300.0799820.61440.270671
310.0279880.2150.415261
32-0.008222-0.06320.474929
330.0131340.10090.459991
340.0402430.30910.379162
350.0156360.12010.452404
36-0.108784-0.83560.203381



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; 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')