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Description of Statistical Computation

Author's title

Method-1: ACF - d=D=1, lambda=1 - Totale industriële productie index met ba...

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 20 Dec 2009 12:50:14 -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/20/t1261338636hhzw2zfx95zxwri.htm/, Retrieved Sat, 27 Apr 2024 11:28:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70004, Retrieved Sat, 27 Apr 2024 11:28:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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]
- R PD        [(Partial) Autocorrelation Function] [Totale industriël...] [2009-11-26 09:03:46] [74be16979710d4c4e7c6647856088456]
- R P           [(Partial) Autocorrelation Function] [Method-1: ACF - d...] [2009-11-27 13:48:51] [74be16979710d4c4e7c6647856088456]
- R P               [(Partial) Autocorrelation Function] [Method-1: ACF - d...] [2009-12-20 19:50:14] [8f072ead2c7c0b3cf3fdae49bab9dd9b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
99.8
116.8
115.7
99.4
94.3
91

Tables (Output of Computation)





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=70004&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=70004&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70004&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.627811-4.34963.5e-05
20.1007610.69810.244245
30.2495641.7290.045115
4-0.240973-1.66950.050764
50.1070150.74140.231024
60.0598580.41470.340102
7-0.135462-0.93850.17634
80.1132270.78450.218313
9-0.020367-0.14110.444189
10-0.06666-0.46180.323144
110.1038030.71920.237761
12-0.082875-0.57420.284266
130.0195490.13540.446415
14-0.006082-0.04210.483282
150.0520190.36040.360066
16-0.100508-0.69630.244786
170.0823090.57030.285582
180.0403660.27970.390468
19-0.147788-1.02390.155506
200.1022580.70850.241041
210.0679960.47110.319856
22-0.265405-1.83880.036069
230.3725142.58080.006484
24-0.28378-1.96610.027543
250.0241120.16710.434016
260.1728511.19750.118487
27-0.155451-1.0770.143433
280.031450.21790.414218
290.0397140.27510.392191
30-0.058522-0.40550.343474
310.0278390.19290.423937
320.0166250.11520.45439
33-0.053049-0.36750.357419
340.0519360.35980.360279
35-0.073624-0.51010.306166
360.0201470.13960.444787

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.627811 & -4.3496 & 3.5e-05 \tabularnewline
2 & 0.100761 & 0.6981 & 0.244245 \tabularnewline
3 & 0.249564 & 1.729 & 0.045115 \tabularnewline
4 & -0.240973 & -1.6695 & 0.050764 \tabularnewline
5 & 0.107015 & 0.7414 & 0.231024 \tabularnewline
6 & 0.059858 & 0.4147 & 0.340102 \tabularnewline
7 & -0.135462 & -0.9385 & 0.17634 \tabularnewline
8 & 0.113227 & 0.7845 & 0.218313 \tabularnewline
9 & -0.020367 & -0.1411 & 0.444189 \tabularnewline
10 & -0.06666 & -0.4618 & 0.323144 \tabularnewline
11 & 0.103803 & 0.7192 & 0.237761 \tabularnewline
12 & -0.082875 & -0.5742 & 0.284266 \tabularnewline
13 & 0.019549 & 0.1354 & 0.446415 \tabularnewline
14 & -0.006082 & -0.0421 & 0.483282 \tabularnewline
15 & 0.052019 & 0.3604 & 0.360066 \tabularnewline
16 & -0.100508 & -0.6963 & 0.244786 \tabularnewline
17 & 0.082309 & 0.5703 & 0.285582 \tabularnewline
18 & 0.040366 & 0.2797 & 0.390468 \tabularnewline
19 & -0.147788 & -1.0239 & 0.155506 \tabularnewline
20 & 0.102258 & 0.7085 & 0.241041 \tabularnewline
21 & 0.067996 & 0.4711 & 0.319856 \tabularnewline
22 & -0.265405 & -1.8388 & 0.036069 \tabularnewline
23 & 0.372514 & 2.5808 & 0.006484 \tabularnewline
24 & -0.28378 & -1.9661 & 0.027543 \tabularnewline
25 & 0.024112 & 0.1671 & 0.434016 \tabularnewline
26 & 0.172851 & 1.1975 & 0.118487 \tabularnewline
27 & -0.155451 & -1.077 & 0.143433 \tabularnewline
28 & 0.03145 & 0.2179 & 0.414218 \tabularnewline
29 & 0.039714 & 0.2751 & 0.392191 \tabularnewline
30 & -0.058522 & -0.4055 & 0.343474 \tabularnewline
31 & 0.027839 & 0.1929 & 0.423937 \tabularnewline
32 & 0.016625 & 0.1152 & 0.45439 \tabularnewline
33 & -0.053049 & -0.3675 & 0.357419 \tabularnewline
34 & 0.051936 & 0.3598 & 0.360279 \tabularnewline
35 & -0.073624 & -0.5101 & 0.306166 \tabularnewline
36 & 0.020147 & 0.1396 & 0.444787 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70004&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]-0.627811[/C][C]-4.3496[/C][C]3.5e-05[/C][/ROW]
[ROW][C]2[/C][C]0.100761[/C][C]0.6981[/C][C]0.244245[/C][/ROW]
[ROW][C]3[/C][C]0.249564[/C][C]1.729[/C][C]0.045115[/C][/ROW]
[ROW][C]4[/C][C]-0.240973[/C][C]-1.6695[/C][C]0.050764[/C][/ROW]
[ROW][C]5[/C][C]0.107015[/C][C]0.7414[/C][C]0.231024[/C][/ROW]
[ROW][C]6[/C][C]0.059858[/C][C]0.4147[/C][C]0.340102[/C][/ROW]
[ROW][C]7[/C][C]-0.135462[/C][C]-0.9385[/C][C]0.17634[/C][/ROW]
[ROW][C]8[/C][C]0.113227[/C][C]0.7845[/C][C]0.218313[/C][/ROW]
[ROW][C]9[/C][C]-0.020367[/C][C]-0.1411[/C][C]0.444189[/C][/ROW]
[ROW][C]10[/C][C]-0.06666[/C][C]-0.4618[/C][C]0.323144[/C][/ROW]
[ROW][C]11[/C][C]0.103803[/C][C]0.7192[/C][C]0.237761[/C][/ROW]
[ROW][C]12[/C][C]-0.082875[/C][C]-0.5742[/C][C]0.284266[/C][/ROW]
[ROW][C]13[/C][C]0.019549[/C][C]0.1354[/C][C]0.446415[/C][/ROW]
[ROW][C]14[/C][C]-0.006082[/C][C]-0.0421[/C][C]0.483282[/C][/ROW]
[ROW][C]15[/C][C]0.052019[/C][C]0.3604[/C][C]0.360066[/C][/ROW]
[ROW][C]16[/C][C]-0.100508[/C][C]-0.6963[/C][C]0.244786[/C][/ROW]
[ROW][C]17[/C][C]0.082309[/C][C]0.5703[/C][C]0.285582[/C][/ROW]
[ROW][C]18[/C][C]0.040366[/C][C]0.2797[/C][C]0.390468[/C][/ROW]
[ROW][C]19[/C][C]-0.147788[/C][C]-1.0239[/C][C]0.155506[/C][/ROW]
[ROW][C]20[/C][C]0.102258[/C][C]0.7085[/C][C]0.241041[/C][/ROW]
[ROW][C]21[/C][C]0.067996[/C][C]0.4711[/C][C]0.319856[/C][/ROW]
[ROW][C]22[/C][C]-0.265405[/C][C]-1.8388[/C][C]0.036069[/C][/ROW]
[ROW][C]23[/C][C]0.372514[/C][C]2.5808[/C][C]0.006484[/C][/ROW]
[ROW][C]24[/C][C]-0.28378[/C][C]-1.9661[/C][C]0.027543[/C][/ROW]
[ROW][C]25[/C][C]0.024112[/C][C]0.1671[/C][C]0.434016[/C][/ROW]
[ROW][C]26[/C][C]0.172851[/C][C]1.1975[/C][C]0.118487[/C][/ROW]
[ROW][C]27[/C][C]-0.155451[/C][C]-1.077[/C][C]0.143433[/C][/ROW]
[ROW][C]28[/C][C]0.03145[/C][C]0.2179[/C][C]0.414218[/C][/ROW]
[ROW][C]29[/C][C]0.039714[/C][C]0.2751[/C][C]0.392191[/C][/ROW]
[ROW][C]30[/C][C]-0.058522[/C][C]-0.4055[/C][C]0.343474[/C][/ROW]
[ROW][C]31[/C][C]0.027839[/C][C]0.1929[/C][C]0.423937[/C][/ROW]
[ROW][C]32[/C][C]0.016625[/C][C]0.1152[/C][C]0.45439[/C][/ROW]
[ROW][C]33[/C][C]-0.053049[/C][C]-0.3675[/C][C]0.357419[/C][/ROW]
[ROW][C]34[/C][C]0.051936[/C][C]0.3598[/C][C]0.360279[/C][/ROW]
[ROW][C]35[/C][C]-0.073624[/C][C]-0.5101[/C][C]0.306166[/C][/ROW]
[ROW][C]36[/C][C]0.020147[/C][C]0.1396[/C][C]0.444787[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70004&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70004&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
1-0.627811-4.34963.5e-05
20.1007610.69810.244245
30.2495641.7290.045115
4-0.240973-1.66950.050764
50.1070150.74140.231024
60.0598580.41470.340102
7-0.135462-0.93850.17634
80.1132270.78450.218313
9-0.020367-0.14110.444189
10-0.06666-0.46180.323144
110.1038030.71920.237761
12-0.082875-0.57420.284266
130.0195490.13540.446415
14-0.006082-0.04210.483282
150.0520190.36040.360066
16-0.100508-0.69630.244786
170.0823090.57030.285582
180.0403660.27970.390468
19-0.147788-1.02390.155506
200.1022580.70850.241041
210.0679960.47110.319856
22-0.265405-1.83880.036069
230.3725142.58080.006484
24-0.28378-1.96610.027543
250.0241120.16710.434016
260.1728511.19750.118487
27-0.155451-1.0770.143433
280.031450.21790.414218
290.0397140.27510.392191
30-0.058522-0.40550.343474
310.0278390.19290.423937
320.0166250.11520.45439
33-0.053049-0.36750.357419
340.0519360.35980.360279
35-0.073624-0.51010.306166
360.0201470.13960.444787






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.627811-4.34963.5e-05
2-0.484251-3.3550.000779
30.0850350.58910.279264
40.1639721.1360.130792
50.1187280.82260.207409
60.113270.78480.218225
7-0.019234-0.13330.447273
8-0.035303-0.24460.40391
9-0.00138-0.00960.496205
10-0.0351-0.24320.404451
110.0213550.1480.4415
12-0.011183-0.07750.469283
13-0.018799-0.13020.448459
14-0.102622-0.7110.240266
150.0630960.43710.331984
16-0.005163-0.03580.485806
17-0.000218-0.00150.499399
180.1451351.00550.159843
190.0020440.01420.494379
20-0.136334-0.94460.174809
210.0572320.39650.346742
22-0.185135-1.28270.102886
230.1630961.130.132053
240.0518670.35930.360455
25-0.083536-0.57880.282731
26-0.099869-0.69190.246163
270.0855180.59250.278152
280.0778520.53940.296061
29-0.056644-0.39240.348235
30-0.038769-0.26860.394695
31-0.04726-0.32740.372384
32-0.033827-0.23440.407852
330.0276790.19180.424367
34-0.000325-0.00230.499105
35-0.110688-0.76690.223457
36-0.162909-1.12870.132324

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.627811 & -4.3496 & 3.5e-05 \tabularnewline
2 & -0.484251 & -3.355 & 0.000779 \tabularnewline
3 & 0.085035 & 0.5891 & 0.279264 \tabularnewline
4 & 0.163972 & 1.136 & 0.130792 \tabularnewline
5 & 0.118728 & 0.8226 & 0.207409 \tabularnewline
6 & 0.11327 & 0.7848 & 0.218225 \tabularnewline
7 & -0.019234 & -0.1333 & 0.447273 \tabularnewline
8 & -0.035303 & -0.2446 & 0.40391 \tabularnewline
9 & -0.00138 & -0.0096 & 0.496205 \tabularnewline
10 & -0.0351 & -0.2432 & 0.404451 \tabularnewline
11 & 0.021355 & 0.148 & 0.4415 \tabularnewline
12 & -0.011183 & -0.0775 & 0.469283 \tabularnewline
13 & -0.018799 & -0.1302 & 0.448459 \tabularnewline
14 & -0.102622 & -0.711 & 0.240266 \tabularnewline
15 & 0.063096 & 0.4371 & 0.331984 \tabularnewline
16 & -0.005163 & -0.0358 & 0.485806 \tabularnewline
17 & -0.000218 & -0.0015 & 0.499399 \tabularnewline
18 & 0.145135 & 1.0055 & 0.159843 \tabularnewline
19 & 0.002044 & 0.0142 & 0.494379 \tabularnewline
20 & -0.136334 & -0.9446 & 0.174809 \tabularnewline
21 & 0.057232 & 0.3965 & 0.346742 \tabularnewline
22 & -0.185135 & -1.2827 & 0.102886 \tabularnewline
23 & 0.163096 & 1.13 & 0.132053 \tabularnewline
24 & 0.051867 & 0.3593 & 0.360455 \tabularnewline
25 & -0.083536 & -0.5788 & 0.282731 \tabularnewline
26 & -0.099869 & -0.6919 & 0.246163 \tabularnewline
27 & 0.085518 & 0.5925 & 0.278152 \tabularnewline
28 & 0.077852 & 0.5394 & 0.296061 \tabularnewline
29 & -0.056644 & -0.3924 & 0.348235 \tabularnewline
30 & -0.038769 & -0.2686 & 0.394695 \tabularnewline
31 & -0.04726 & -0.3274 & 0.372384 \tabularnewline
32 & -0.033827 & -0.2344 & 0.407852 \tabularnewline
33 & 0.027679 & 0.1918 & 0.424367 \tabularnewline
34 & -0.000325 & -0.0023 & 0.499105 \tabularnewline
35 & -0.110688 & -0.7669 & 0.223457 \tabularnewline
36 & -0.162909 & -1.1287 & 0.132324 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70004&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]-0.627811[/C][C]-4.3496[/C][C]3.5e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.484251[/C][C]-3.355[/C][C]0.000779[/C][/ROW]
[ROW][C]3[/C][C]0.085035[/C][C]0.5891[/C][C]0.279264[/C][/ROW]
[ROW][C]4[/C][C]0.163972[/C][C]1.136[/C][C]0.130792[/C][/ROW]
[ROW][C]5[/C][C]0.118728[/C][C]0.8226[/C][C]0.207409[/C][/ROW]
[ROW][C]6[/C][C]0.11327[/C][C]0.7848[/C][C]0.218225[/C][/ROW]
[ROW][C]7[/C][C]-0.019234[/C][C]-0.1333[/C][C]0.447273[/C][/ROW]
[ROW][C]8[/C][C]-0.035303[/C][C]-0.2446[/C][C]0.40391[/C][/ROW]
[ROW][C]9[/C][C]-0.00138[/C][C]-0.0096[/C][C]0.496205[/C][/ROW]
[ROW][C]10[/C][C]-0.0351[/C][C]-0.2432[/C][C]0.404451[/C][/ROW]
[ROW][C]11[/C][C]0.021355[/C][C]0.148[/C][C]0.4415[/C][/ROW]
[ROW][C]12[/C][C]-0.011183[/C][C]-0.0775[/C][C]0.469283[/C][/ROW]
[ROW][C]13[/C][C]-0.018799[/C][C]-0.1302[/C][C]0.448459[/C][/ROW]
[ROW][C]14[/C][C]-0.102622[/C][C]-0.711[/C][C]0.240266[/C][/ROW]
[ROW][C]15[/C][C]0.063096[/C][C]0.4371[/C][C]0.331984[/C][/ROW]
[ROW][C]16[/C][C]-0.005163[/C][C]-0.0358[/C][C]0.485806[/C][/ROW]
[ROW][C]17[/C][C]-0.000218[/C][C]-0.0015[/C][C]0.499399[/C][/ROW]
[ROW][C]18[/C][C]0.145135[/C][C]1.0055[/C][C]0.159843[/C][/ROW]
[ROW][C]19[/C][C]0.002044[/C][C]0.0142[/C][C]0.494379[/C][/ROW]
[ROW][C]20[/C][C]-0.136334[/C][C]-0.9446[/C][C]0.174809[/C][/ROW]
[ROW][C]21[/C][C]0.057232[/C][C]0.3965[/C][C]0.346742[/C][/ROW]
[ROW][C]22[/C][C]-0.185135[/C][C]-1.2827[/C][C]0.102886[/C][/ROW]
[ROW][C]23[/C][C]0.163096[/C][C]1.13[/C][C]0.132053[/C][/ROW]
[ROW][C]24[/C][C]0.051867[/C][C]0.3593[/C][C]0.360455[/C][/ROW]
[ROW][C]25[/C][C]-0.083536[/C][C]-0.5788[/C][C]0.282731[/C][/ROW]
[ROW][C]26[/C][C]-0.099869[/C][C]-0.6919[/C][C]0.246163[/C][/ROW]
[ROW][C]27[/C][C]0.085518[/C][C]0.5925[/C][C]0.278152[/C][/ROW]
[ROW][C]28[/C][C]0.077852[/C][C]0.5394[/C][C]0.296061[/C][/ROW]
[ROW][C]29[/C][C]-0.056644[/C][C]-0.3924[/C][C]0.348235[/C][/ROW]
[ROW][C]30[/C][C]-0.038769[/C][C]-0.2686[/C][C]0.394695[/C][/ROW]
[ROW][C]31[/C][C]-0.04726[/C][C]-0.3274[/C][C]0.372384[/C][/ROW]
[ROW][C]32[/C][C]-0.033827[/C][C]-0.2344[/C][C]0.407852[/C][/ROW]
[ROW][C]33[/C][C]0.027679[/C][C]0.1918[/C][C]0.424367[/C][/ROW]
[ROW][C]34[/C][C]-0.000325[/C][C]-0.0023[/C][C]0.499105[/C][/ROW]
[ROW][C]35[/C][C]-0.110688[/C][C]-0.7669[/C][C]0.223457[/C][/ROW]
[ROW][C]36[/C][C]-0.162909[/C][C]-1.1287[/C][C]0.132324[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70004&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70004&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
1-0.627811-4.34963.5e-05
2-0.484251-3.3550.000779
30.0850350.58910.279264
40.1639721.1360.130792
50.1187280.82260.207409
60.113270.78480.218225
7-0.019234-0.13330.447273
8-0.035303-0.24460.40391
9-0.00138-0.00960.496205
10-0.0351-0.24320.404451
110.0213550.1480.4415
12-0.011183-0.07750.469283
13-0.018799-0.13020.448459
14-0.102622-0.7110.240266
150.0630960.43710.331984
16-0.005163-0.03580.485806
17-0.000218-0.00150.499399
180.1451351.00550.159843
190.0020440.01420.494379
20-0.136334-0.94460.174809
210.0572320.39650.346742
22-0.185135-1.28270.102886
230.1630961.130.132053
240.0518670.35930.360455
25-0.083536-0.57880.282731
26-0.099869-0.69190.246163
270.0855180.59250.278152
280.0778520.53940.296061
29-0.056644-0.39240.348235
30-0.038769-0.26860.394695
31-0.04726-0.32740.372384
32-0.033827-0.23440.407852
330.0276790.19180.424367
34-0.000325-0.00230.499105
35-0.110688-0.76690.223457
36-0.162909-1.12870.132324


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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')