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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 computationTue, 24 Nov 2009 02:58:46 -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/24/t1259056776421ip2yx1hejj4i.htm/, Retrieved Mon, 22 Jul 2024 20:15:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58971, Retrieved Mon, 22 Jul 2024 20:15:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact255
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] [] [2009-11-24 09:58:46] [2ffc7e281e02b99889abd2ccc65ed6c3] [Current]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-18 11:19:36] [fef2f8976fa1eef1b54e2cee317fe737]
- R                 [(Partial) Autocorrelation Function] [Paper: ACF 2] [2010-12-22 20:22:11] [29e492448d11757ae0fad5ef6e7f8e86]
- R P               [(Partial) Autocorrelation Function] [Paper: ACF 3] [2010-12-22 20:24:01] [29e492448d11757ae0fad5ef6e7f8e86]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-18 11:49:26] [fef2f8976fa1eef1b54e2cee317fe737]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-18 11:51:01] [fef2f8976fa1eef1b54e2cee317fe737]
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Dataseries X:
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96




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=58971&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=58971&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58971&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
1-0.155732-1.02120.156434
20.1978571.29740.100699
30.3253622.13350.019313
40.0568070.37250.355671
50.0289940.19010.425052
60.2839531.8620.034723
7-0.050056-0.32820.372161
8-0.042757-0.28040.390266
90.1440840.94480.175015
10-0.13219-0.86680.195424
11-0.061466-0.40310.34445
12-0.088888-0.58290.28151
13-0.070172-0.46020.323863
14-0.178216-1.16860.124493
15-0.00561-0.03680.485412
16-0.145309-0.95290.172994
17-0.044872-0.29420.384993
18-0.054293-0.3560.361782
19-0.184503-1.20990.116469
20-0.060992-0.40.345586
21-0.007469-0.0490.480582
22-0.233951-1.53410.066163
230.1587071.04070.151913
24-0.231807-1.52010.067908
25-0.014685-0.09630.461865
260.0743410.48750.314194
27-0.041571-0.27260.393234
28-0.104422-0.68470.248591
290.0834410.54720.293548
30-0.044442-0.29140.386063
31-0.051648-0.33870.368251
320.1315930.86290.196486
33-0.049535-0.32480.373445
340.028980.190.425089
35-0.014828-0.09720.461497
360.0622580.40830.342556

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.155732 & -1.0212 & 0.156434 \tabularnewline
2 & 0.197857 & 1.2974 & 0.100699 \tabularnewline
3 & 0.325362 & 2.1335 & 0.019313 \tabularnewline
4 & 0.056807 & 0.3725 & 0.355671 \tabularnewline
5 & 0.028994 & 0.1901 & 0.425052 \tabularnewline
6 & 0.283953 & 1.862 & 0.034723 \tabularnewline
7 & -0.050056 & -0.3282 & 0.372161 \tabularnewline
8 & -0.042757 & -0.2804 & 0.390266 \tabularnewline
9 & 0.144084 & 0.9448 & 0.175015 \tabularnewline
10 & -0.13219 & -0.8668 & 0.195424 \tabularnewline
11 & -0.061466 & -0.4031 & 0.34445 \tabularnewline
12 & -0.088888 & -0.5829 & 0.28151 \tabularnewline
13 & -0.070172 & -0.4602 & 0.323863 \tabularnewline
14 & -0.178216 & -1.1686 & 0.124493 \tabularnewline
15 & -0.00561 & -0.0368 & 0.485412 \tabularnewline
16 & -0.145309 & -0.9529 & 0.172994 \tabularnewline
17 & -0.044872 & -0.2942 & 0.384993 \tabularnewline
18 & -0.054293 & -0.356 & 0.361782 \tabularnewline
19 & -0.184503 & -1.2099 & 0.116469 \tabularnewline
20 & -0.060992 & -0.4 & 0.345586 \tabularnewline
21 & -0.007469 & -0.049 & 0.480582 \tabularnewline
22 & -0.233951 & -1.5341 & 0.066163 \tabularnewline
23 & 0.158707 & 1.0407 & 0.151913 \tabularnewline
24 & -0.231807 & -1.5201 & 0.067908 \tabularnewline
25 & -0.014685 & -0.0963 & 0.461865 \tabularnewline
26 & 0.074341 & 0.4875 & 0.314194 \tabularnewline
27 & -0.041571 & -0.2726 & 0.393234 \tabularnewline
28 & -0.104422 & -0.6847 & 0.248591 \tabularnewline
29 & 0.083441 & 0.5472 & 0.293548 \tabularnewline
30 & -0.044442 & -0.2914 & 0.386063 \tabularnewline
31 & -0.051648 & -0.3387 & 0.368251 \tabularnewline
32 & 0.131593 & 0.8629 & 0.196486 \tabularnewline
33 & -0.049535 & -0.3248 & 0.373445 \tabularnewline
34 & 0.02898 & 0.19 & 0.425089 \tabularnewline
35 & -0.014828 & -0.0972 & 0.461497 \tabularnewline
36 & 0.062258 & 0.4083 & 0.342556 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58971&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]-0.155732[/C][C]-1.0212[/C][C]0.156434[/C][/ROW]
[ROW][C]2[/C][C]0.197857[/C][C]1.2974[/C][C]0.100699[/C][/ROW]
[ROW][C]3[/C][C]0.325362[/C][C]2.1335[/C][C]0.019313[/C][/ROW]
[ROW][C]4[/C][C]0.056807[/C][C]0.3725[/C][C]0.355671[/C][/ROW]
[ROW][C]5[/C][C]0.028994[/C][C]0.1901[/C][C]0.425052[/C][/ROW]
[ROW][C]6[/C][C]0.283953[/C][C]1.862[/C][C]0.034723[/C][/ROW]
[ROW][C]7[/C][C]-0.050056[/C][C]-0.3282[/C][C]0.372161[/C][/ROW]
[ROW][C]8[/C][C]-0.042757[/C][C]-0.2804[/C][C]0.390266[/C][/ROW]
[ROW][C]9[/C][C]0.144084[/C][C]0.9448[/C][C]0.175015[/C][/ROW]
[ROW][C]10[/C][C]-0.13219[/C][C]-0.8668[/C][C]0.195424[/C][/ROW]
[ROW][C]11[/C][C]-0.061466[/C][C]-0.4031[/C][C]0.34445[/C][/ROW]
[ROW][C]12[/C][C]-0.088888[/C][C]-0.5829[/C][C]0.28151[/C][/ROW]
[ROW][C]13[/C][C]-0.070172[/C][C]-0.4602[/C][C]0.323863[/C][/ROW]
[ROW][C]14[/C][C]-0.178216[/C][C]-1.1686[/C][C]0.124493[/C][/ROW]
[ROW][C]15[/C][C]-0.00561[/C][C]-0.0368[/C][C]0.485412[/C][/ROW]
[ROW][C]16[/C][C]-0.145309[/C][C]-0.9529[/C][C]0.172994[/C][/ROW]
[ROW][C]17[/C][C]-0.044872[/C][C]-0.2942[/C][C]0.384993[/C][/ROW]
[ROW][C]18[/C][C]-0.054293[/C][C]-0.356[/C][C]0.361782[/C][/ROW]
[ROW][C]19[/C][C]-0.184503[/C][C]-1.2099[/C][C]0.116469[/C][/ROW]
[ROW][C]20[/C][C]-0.060992[/C][C]-0.4[/C][C]0.345586[/C][/ROW]
[ROW][C]21[/C][C]-0.007469[/C][C]-0.049[/C][C]0.480582[/C][/ROW]
[ROW][C]22[/C][C]-0.233951[/C][C]-1.5341[/C][C]0.066163[/C][/ROW]
[ROW][C]23[/C][C]0.158707[/C][C]1.0407[/C][C]0.151913[/C][/ROW]
[ROW][C]24[/C][C]-0.231807[/C][C]-1.5201[/C][C]0.067908[/C][/ROW]
[ROW][C]25[/C][C]-0.014685[/C][C]-0.0963[/C][C]0.461865[/C][/ROW]
[ROW][C]26[/C][C]0.074341[/C][C]0.4875[/C][C]0.314194[/C][/ROW]
[ROW][C]27[/C][C]-0.041571[/C][C]-0.2726[/C][C]0.393234[/C][/ROW]
[ROW][C]28[/C][C]-0.104422[/C][C]-0.6847[/C][C]0.248591[/C][/ROW]
[ROW][C]29[/C][C]0.083441[/C][C]0.5472[/C][C]0.293548[/C][/ROW]
[ROW][C]30[/C][C]-0.044442[/C][C]-0.2914[/C][C]0.386063[/C][/ROW]
[ROW][C]31[/C][C]-0.051648[/C][C]-0.3387[/C][C]0.368251[/C][/ROW]
[ROW][C]32[/C][C]0.131593[/C][C]0.8629[/C][C]0.196486[/C][/ROW]
[ROW][C]33[/C][C]-0.049535[/C][C]-0.3248[/C][C]0.373445[/C][/ROW]
[ROW][C]34[/C][C]0.02898[/C][C]0.19[/C][C]0.425089[/C][/ROW]
[ROW][C]35[/C][C]-0.014828[/C][C]-0.0972[/C][C]0.461497[/C][/ROW]
[ROW][C]36[/C][C]0.062258[/C][C]0.4083[/C][C]0.342556[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58971&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58971&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
1-0.155732-1.02120.156434
20.1978571.29740.100699
30.3253622.13350.019313
40.0568070.37250.355671
50.0289940.19010.425052
60.2839531.8620.034723
7-0.050056-0.32820.372161
8-0.042757-0.28040.390266
90.1440840.94480.175015
10-0.13219-0.86680.195424
11-0.061466-0.40310.34445
12-0.088888-0.58290.28151
13-0.070172-0.46020.323863
14-0.178216-1.16860.124493
15-0.00561-0.03680.485412
16-0.145309-0.95290.172994
17-0.044872-0.29420.384993
18-0.054293-0.3560.361782
19-0.184503-1.20990.116469
20-0.060992-0.40.345586
21-0.007469-0.0490.480582
22-0.233951-1.53410.066163
230.1587071.04070.151913
24-0.231807-1.52010.067908
25-0.014685-0.09630.461865
260.0743410.48750.314194
27-0.041571-0.27260.393234
28-0.104422-0.68470.248591
290.0834410.54720.293548
30-0.044442-0.29140.386063
31-0.051648-0.33870.368251
320.1315930.86290.196486
33-0.049535-0.32480.373445
340.028980.190.425089
35-0.014828-0.09720.461497
360.0622580.40830.342556







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.155732-1.02120.156434
20.177921.16670.124881
30.4004832.62610.005958
40.1747931.14620.129027
5-0.09902-0.64930.259794
60.1124160.73720.232515
7-0.025296-0.16590.434516
8-0.184198-1.20790.11685
9-0.04684-0.30720.380105
10-0.096834-0.6350.264402
11-0.07545-0.49480.311645
12-0.193111-1.26630.106109
13-0.030751-0.20160.420571
14-0.038411-0.25190.401167
150.0465190.3050.380902
160.0127110.08340.466979
170.093250.61150.272049
180.0711380.46650.321613
19-0.175859-1.15320.127602
20-0.146046-0.95770.171786
210.029750.19510.423124
22-0.17871-1.17190.123849
230.1468240.96280.170518
24-0.195746-1.28360.103079
250.0177480.11640.453945
260.1013240.66440.254983
270.0993530.65150.259094
28-0.028963-0.18990.425132
29-0.101922-0.66840.253741
30-0.014565-0.09550.462178
31-0.058952-0.38660.350488
32-0.039489-0.25890.398457
33-0.00986-0.06470.474375
34-0.009324-0.06110.475766
35-0.06928-0.45430.325949
36-0.059319-0.3890.349606

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.155732 & -1.0212 & 0.156434 \tabularnewline
2 & 0.17792 & 1.1667 & 0.124881 \tabularnewline
3 & 0.400483 & 2.6261 & 0.005958 \tabularnewline
4 & 0.174793 & 1.1462 & 0.129027 \tabularnewline
5 & -0.09902 & -0.6493 & 0.259794 \tabularnewline
6 & 0.112416 & 0.7372 & 0.232515 \tabularnewline
7 & -0.025296 & -0.1659 & 0.434516 \tabularnewline
8 & -0.184198 & -1.2079 & 0.11685 \tabularnewline
9 & -0.04684 & -0.3072 & 0.380105 \tabularnewline
10 & -0.096834 & -0.635 & 0.264402 \tabularnewline
11 & -0.07545 & -0.4948 & 0.311645 \tabularnewline
12 & -0.193111 & -1.2663 & 0.106109 \tabularnewline
13 & -0.030751 & -0.2016 & 0.420571 \tabularnewline
14 & -0.038411 & -0.2519 & 0.401167 \tabularnewline
15 & 0.046519 & 0.305 & 0.380902 \tabularnewline
16 & 0.012711 & 0.0834 & 0.466979 \tabularnewline
17 & 0.09325 & 0.6115 & 0.272049 \tabularnewline
18 & 0.071138 & 0.4665 & 0.321613 \tabularnewline
19 & -0.175859 & -1.1532 & 0.127602 \tabularnewline
20 & -0.146046 & -0.9577 & 0.171786 \tabularnewline
21 & 0.02975 & 0.1951 & 0.423124 \tabularnewline
22 & -0.17871 & -1.1719 & 0.123849 \tabularnewline
23 & 0.146824 & 0.9628 & 0.170518 \tabularnewline
24 & -0.195746 & -1.2836 & 0.103079 \tabularnewline
25 & 0.017748 & 0.1164 & 0.453945 \tabularnewline
26 & 0.101324 & 0.6644 & 0.254983 \tabularnewline
27 & 0.099353 & 0.6515 & 0.259094 \tabularnewline
28 & -0.028963 & -0.1899 & 0.425132 \tabularnewline
29 & -0.101922 & -0.6684 & 0.253741 \tabularnewline
30 & -0.014565 & -0.0955 & 0.462178 \tabularnewline
31 & -0.058952 & -0.3866 & 0.350488 \tabularnewline
32 & -0.039489 & -0.2589 & 0.398457 \tabularnewline
33 & -0.00986 & -0.0647 & 0.474375 \tabularnewline
34 & -0.009324 & -0.0611 & 0.475766 \tabularnewline
35 & -0.06928 & -0.4543 & 0.325949 \tabularnewline
36 & -0.059319 & -0.389 & 0.349606 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58971&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]-0.155732[/C][C]-1.0212[/C][C]0.156434[/C][/ROW]
[ROW][C]2[/C][C]0.17792[/C][C]1.1667[/C][C]0.124881[/C][/ROW]
[ROW][C]3[/C][C]0.400483[/C][C]2.6261[/C][C]0.005958[/C][/ROW]
[ROW][C]4[/C][C]0.174793[/C][C]1.1462[/C][C]0.129027[/C][/ROW]
[ROW][C]5[/C][C]-0.09902[/C][C]-0.6493[/C][C]0.259794[/C][/ROW]
[ROW][C]6[/C][C]0.112416[/C][C]0.7372[/C][C]0.232515[/C][/ROW]
[ROW][C]7[/C][C]-0.025296[/C][C]-0.1659[/C][C]0.434516[/C][/ROW]
[ROW][C]8[/C][C]-0.184198[/C][C]-1.2079[/C][C]0.11685[/C][/ROW]
[ROW][C]9[/C][C]-0.04684[/C][C]-0.3072[/C][C]0.380105[/C][/ROW]
[ROW][C]10[/C][C]-0.096834[/C][C]-0.635[/C][C]0.264402[/C][/ROW]
[ROW][C]11[/C][C]-0.07545[/C][C]-0.4948[/C][C]0.311645[/C][/ROW]
[ROW][C]12[/C][C]-0.193111[/C][C]-1.2663[/C][C]0.106109[/C][/ROW]
[ROW][C]13[/C][C]-0.030751[/C][C]-0.2016[/C][C]0.420571[/C][/ROW]
[ROW][C]14[/C][C]-0.038411[/C][C]-0.2519[/C][C]0.401167[/C][/ROW]
[ROW][C]15[/C][C]0.046519[/C][C]0.305[/C][C]0.380902[/C][/ROW]
[ROW][C]16[/C][C]0.012711[/C][C]0.0834[/C][C]0.466979[/C][/ROW]
[ROW][C]17[/C][C]0.09325[/C][C]0.6115[/C][C]0.272049[/C][/ROW]
[ROW][C]18[/C][C]0.071138[/C][C]0.4665[/C][C]0.321613[/C][/ROW]
[ROW][C]19[/C][C]-0.175859[/C][C]-1.1532[/C][C]0.127602[/C][/ROW]
[ROW][C]20[/C][C]-0.146046[/C][C]-0.9577[/C][C]0.171786[/C][/ROW]
[ROW][C]21[/C][C]0.02975[/C][C]0.1951[/C][C]0.423124[/C][/ROW]
[ROW][C]22[/C][C]-0.17871[/C][C]-1.1719[/C][C]0.123849[/C][/ROW]
[ROW][C]23[/C][C]0.146824[/C][C]0.9628[/C][C]0.170518[/C][/ROW]
[ROW][C]24[/C][C]-0.195746[/C][C]-1.2836[/C][C]0.103079[/C][/ROW]
[ROW][C]25[/C][C]0.017748[/C][C]0.1164[/C][C]0.453945[/C][/ROW]
[ROW][C]26[/C][C]0.101324[/C][C]0.6644[/C][C]0.254983[/C][/ROW]
[ROW][C]27[/C][C]0.099353[/C][C]0.6515[/C][C]0.259094[/C][/ROW]
[ROW][C]28[/C][C]-0.028963[/C][C]-0.1899[/C][C]0.425132[/C][/ROW]
[ROW][C]29[/C][C]-0.101922[/C][C]-0.6684[/C][C]0.253741[/C][/ROW]
[ROW][C]30[/C][C]-0.014565[/C][C]-0.0955[/C][C]0.462178[/C][/ROW]
[ROW][C]31[/C][C]-0.058952[/C][C]-0.3866[/C][C]0.350488[/C][/ROW]
[ROW][C]32[/C][C]-0.039489[/C][C]-0.2589[/C][C]0.398457[/C][/ROW]
[ROW][C]33[/C][C]-0.00986[/C][C]-0.0647[/C][C]0.474375[/C][/ROW]
[ROW][C]34[/C][C]-0.009324[/C][C]-0.0611[/C][C]0.475766[/C][/ROW]
[ROW][C]35[/C][C]-0.06928[/C][C]-0.4543[/C][C]0.325949[/C][/ROW]
[ROW][C]36[/C][C]-0.059319[/C][C]-0.389[/C][C]0.349606[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58971&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58971&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
1-0.155732-1.02120.156434
20.177921.16670.124881
30.4004832.62610.005958
40.1747931.14620.129027
5-0.09902-0.64930.259794
60.1124160.73720.232515
7-0.025296-0.16590.434516
8-0.184198-1.20790.11685
9-0.04684-0.30720.380105
10-0.096834-0.6350.264402
11-0.07545-0.49480.311645
12-0.193111-1.26630.106109
13-0.030751-0.20160.420571
14-0.038411-0.25190.401167
150.0465190.3050.380902
160.0127110.08340.466979
170.093250.61150.272049
180.0711380.46650.321613
19-0.175859-1.15320.127602
20-0.146046-0.95770.171786
210.029750.19510.423124
22-0.17871-1.17190.123849
230.1468240.96280.170518
24-0.195746-1.28360.103079
250.0177480.11640.453945
260.1013240.66440.254983
270.0993530.65150.259094
28-0.028963-0.18990.425132
29-0.101922-0.66840.253741
30-0.014565-0.09550.462178
31-0.058952-0.38660.350488
32-0.039489-0.25890.398457
33-0.00986-0.06470.474375
34-0.009324-0.06110.475766
35-0.06928-0.45430.325949
36-0.059319-0.3890.349606



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')