Free Statistics

of Irreproducible Research!

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 computationFri, 27 Nov 2009 12:42:13 -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/27/t1259351010bz9sygobc3mz4vx.htm/, Retrieved Mon, 29 Apr 2024 23:23:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61184, Retrieved Mon, 29 Apr 2024 23:23:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
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]
-   PD          [(Partial) Autocorrelation Function] [WS 8.2] [2009-11-27 19:42:13] [71c065898bd1c08eef04509b4bcee039] [Current]
Feedback Forum

Post a new message
Dataseries X:
100.00
94.97
107.50
124.27
107.06
79.71
163.41
144.83
166.82
154.26
132.60
157.51
104.02
106.03
113.23
117.64
113.34
66.62
185.99
174.57
208.19
163.81
162.46
148.16
113.41
105.63
111.79
132.36
110.75
67.37
178.29
156.38
189.71
152.80
150.80
160.40
127.25
108.47
117.09
147.25
116.19
75.83
181.94
179.12
183.15
197.90
155.42
162.54
125.90
105.50
121.11
137.51
97.20
69.74
152.58
146.59
161.16
152.84
121.95
140.12




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=61184&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=61184&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61184&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
10.5138643.56020.000424
20.5646313.91190.000144
30.3064552.12320.019461
40.2147271.48770.071689
50.1207540.83660.203479
60.1249940.8660.195403
70.0325420.22550.411291
80.0182020.12610.450087
9-0.113214-0.78440.218338
10-0.170398-1.18060.121799
11-0.241615-1.6740.050322
12-0.373026-2.58440.006426
13-0.290842-2.0150.024761
14-0.228984-1.58640.059602
15-0.11154-0.77280.221723
16-0.062324-0.43180.333913
17-0.017261-0.11960.452655
18-0.024176-0.16750.433841
19-0.023279-0.16130.436273
20-0.001146-0.00790.496848
210.1210980.8390.202816
220.0272760.1890.425456
230.2536741.75750.042604
240.1706021.1820.121521
250.2681471.85780.03467
260.2000281.38580.086101
270.1522871.05510.148336
28-0.017387-0.12050.45231
290.0141220.09780.461233
30-0.091645-0.63490.264243
31-0.052339-0.36260.359242
32-0.099314-0.68810.247362
33-0.144055-0.9980.161631
34-0.156176-1.0820.142325
35-0.232259-1.60910.057073
36-0.237222-1.64350.053405

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.513864 & 3.5602 & 0.000424 \tabularnewline
2 & 0.564631 & 3.9119 & 0.000144 \tabularnewline
3 & 0.306455 & 2.1232 & 0.019461 \tabularnewline
4 & 0.214727 & 1.4877 & 0.071689 \tabularnewline
5 & 0.120754 & 0.8366 & 0.203479 \tabularnewline
6 & 0.124994 & 0.866 & 0.195403 \tabularnewline
7 & 0.032542 & 0.2255 & 0.411291 \tabularnewline
8 & 0.018202 & 0.1261 & 0.450087 \tabularnewline
9 & -0.113214 & -0.7844 & 0.218338 \tabularnewline
10 & -0.170398 & -1.1806 & 0.121799 \tabularnewline
11 & -0.241615 & -1.674 & 0.050322 \tabularnewline
12 & -0.373026 & -2.5844 & 0.006426 \tabularnewline
13 & -0.290842 & -2.015 & 0.024761 \tabularnewline
14 & -0.228984 & -1.5864 & 0.059602 \tabularnewline
15 & -0.11154 & -0.7728 & 0.221723 \tabularnewline
16 & -0.062324 & -0.4318 & 0.333913 \tabularnewline
17 & -0.017261 & -0.1196 & 0.452655 \tabularnewline
18 & -0.024176 & -0.1675 & 0.433841 \tabularnewline
19 & -0.023279 & -0.1613 & 0.436273 \tabularnewline
20 & -0.001146 & -0.0079 & 0.496848 \tabularnewline
21 & 0.121098 & 0.839 & 0.202816 \tabularnewline
22 & 0.027276 & 0.189 & 0.425456 \tabularnewline
23 & 0.253674 & 1.7575 & 0.042604 \tabularnewline
24 & 0.170602 & 1.182 & 0.121521 \tabularnewline
25 & 0.268147 & 1.8578 & 0.03467 \tabularnewline
26 & 0.200028 & 1.3858 & 0.086101 \tabularnewline
27 & 0.152287 & 1.0551 & 0.148336 \tabularnewline
28 & -0.017387 & -0.1205 & 0.45231 \tabularnewline
29 & 0.014122 & 0.0978 & 0.461233 \tabularnewline
30 & -0.091645 & -0.6349 & 0.264243 \tabularnewline
31 & -0.052339 & -0.3626 & 0.359242 \tabularnewline
32 & -0.099314 & -0.6881 & 0.247362 \tabularnewline
33 & -0.144055 & -0.998 & 0.161631 \tabularnewline
34 & -0.156176 & -1.082 & 0.142325 \tabularnewline
35 & -0.232259 & -1.6091 & 0.057073 \tabularnewline
36 & -0.237222 & -1.6435 & 0.053405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61184&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]0.513864[/C][C]3.5602[/C][C]0.000424[/C][/ROW]
[ROW][C]2[/C][C]0.564631[/C][C]3.9119[/C][C]0.000144[/C][/ROW]
[ROW][C]3[/C][C]0.306455[/C][C]2.1232[/C][C]0.019461[/C][/ROW]
[ROW][C]4[/C][C]0.214727[/C][C]1.4877[/C][C]0.071689[/C][/ROW]
[ROW][C]5[/C][C]0.120754[/C][C]0.8366[/C][C]0.203479[/C][/ROW]
[ROW][C]6[/C][C]0.124994[/C][C]0.866[/C][C]0.195403[/C][/ROW]
[ROW][C]7[/C][C]0.032542[/C][C]0.2255[/C][C]0.411291[/C][/ROW]
[ROW][C]8[/C][C]0.018202[/C][C]0.1261[/C][C]0.450087[/C][/ROW]
[ROW][C]9[/C][C]-0.113214[/C][C]-0.7844[/C][C]0.218338[/C][/ROW]
[ROW][C]10[/C][C]-0.170398[/C][C]-1.1806[/C][C]0.121799[/C][/ROW]
[ROW][C]11[/C][C]-0.241615[/C][C]-1.674[/C][C]0.050322[/C][/ROW]
[ROW][C]12[/C][C]-0.373026[/C][C]-2.5844[/C][C]0.006426[/C][/ROW]
[ROW][C]13[/C][C]-0.290842[/C][C]-2.015[/C][C]0.024761[/C][/ROW]
[ROW][C]14[/C][C]-0.228984[/C][C]-1.5864[/C][C]0.059602[/C][/ROW]
[ROW][C]15[/C][C]-0.11154[/C][C]-0.7728[/C][C]0.221723[/C][/ROW]
[ROW][C]16[/C][C]-0.062324[/C][C]-0.4318[/C][C]0.333913[/C][/ROW]
[ROW][C]17[/C][C]-0.017261[/C][C]-0.1196[/C][C]0.452655[/C][/ROW]
[ROW][C]18[/C][C]-0.024176[/C][C]-0.1675[/C][C]0.433841[/C][/ROW]
[ROW][C]19[/C][C]-0.023279[/C][C]-0.1613[/C][C]0.436273[/C][/ROW]
[ROW][C]20[/C][C]-0.001146[/C][C]-0.0079[/C][C]0.496848[/C][/ROW]
[ROW][C]21[/C][C]0.121098[/C][C]0.839[/C][C]0.202816[/C][/ROW]
[ROW][C]22[/C][C]0.027276[/C][C]0.189[/C][C]0.425456[/C][/ROW]
[ROW][C]23[/C][C]0.253674[/C][C]1.7575[/C][C]0.042604[/C][/ROW]
[ROW][C]24[/C][C]0.170602[/C][C]1.182[/C][C]0.121521[/C][/ROW]
[ROW][C]25[/C][C]0.268147[/C][C]1.8578[/C][C]0.03467[/C][/ROW]
[ROW][C]26[/C][C]0.200028[/C][C]1.3858[/C][C]0.086101[/C][/ROW]
[ROW][C]27[/C][C]0.152287[/C][C]1.0551[/C][C]0.148336[/C][/ROW]
[ROW][C]28[/C][C]-0.017387[/C][C]-0.1205[/C][C]0.45231[/C][/ROW]
[ROW][C]29[/C][C]0.014122[/C][C]0.0978[/C][C]0.461233[/C][/ROW]
[ROW][C]30[/C][C]-0.091645[/C][C]-0.6349[/C][C]0.264243[/C][/ROW]
[ROW][C]31[/C][C]-0.052339[/C][C]-0.3626[/C][C]0.359242[/C][/ROW]
[ROW][C]32[/C][C]-0.099314[/C][C]-0.6881[/C][C]0.247362[/C][/ROW]
[ROW][C]33[/C][C]-0.144055[/C][C]-0.998[/C][C]0.161631[/C][/ROW]
[ROW][C]34[/C][C]-0.156176[/C][C]-1.082[/C][C]0.142325[/C][/ROW]
[ROW][C]35[/C][C]-0.232259[/C][C]-1.6091[/C][C]0.057073[/C][/ROW]
[ROW][C]36[/C][C]-0.237222[/C][C]-1.6435[/C][C]0.053405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61184&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61184&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
10.5138643.56020.000424
20.5646313.91190.000144
30.3064552.12320.019461
40.2147271.48770.071689
50.1207540.83660.203479
60.1249940.8660.195403
70.0325420.22550.411291
80.0182020.12610.450087
9-0.113214-0.78440.218338
10-0.170398-1.18060.121799
11-0.241615-1.6740.050322
12-0.373026-2.58440.006426
13-0.290842-2.0150.024761
14-0.228984-1.58640.059602
15-0.11154-0.77280.221723
16-0.062324-0.43180.333913
17-0.017261-0.11960.452655
18-0.024176-0.16750.433841
19-0.023279-0.16130.436273
20-0.001146-0.00790.496848
210.1210980.8390.202816
220.0272760.1890.425456
230.2536741.75750.042604
240.1706021.1820.121521
250.2681471.85780.03467
260.2000281.38580.086101
270.1522871.05510.148336
28-0.017387-0.12050.45231
290.0141220.09780.461233
30-0.091645-0.63490.264243
31-0.052339-0.36260.359242
32-0.099314-0.68810.247362
33-0.144055-0.9980.161631
34-0.156176-1.0820.142325
35-0.232259-1.60910.057073
36-0.237222-1.64350.053405







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5138643.56020.000424
20.4084222.82960.003392
3-0.122411-0.84810.200299
4-0.136541-0.9460.174447
50.0086190.05970.476315
60.1241450.86010.197004
7-0.07045-0.48810.313852
8-0.0899-0.62280.268167
9-0.155709-1.07880.143038
10-0.106914-0.74070.231235
11-0.047831-0.33140.370898
12-0.238339-1.65130.052607
130.0407350.28220.389493
140.2181791.51160.068597
150.147821.02410.155455
16-0.066587-0.46130.323324
17-0.069567-0.4820.316007
180.0384320.26630.395589
190.0039110.02710.489248
20-0.011492-0.07960.468435
210.1288220.89250.188288
22-0.19297-1.33690.093772
230.2074061.4370.078609
240.0330610.22910.409901
250.0059090.04090.483756
260.0315820.21880.413865
27-0.022292-0.15440.438955
28-0.232758-1.61260.056694
29-0.008303-0.05750.477182
300.043250.29960.382871
31-0.098711-0.68390.248667
32-0.041571-0.2880.387288
330.018370.12730.44963
34-0.040358-0.27960.390489
35-0.008918-0.06180.475495
360.0094580.06550.474013

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.513864 & 3.5602 & 0.000424 \tabularnewline
2 & 0.408422 & 2.8296 & 0.003392 \tabularnewline
3 & -0.122411 & -0.8481 & 0.200299 \tabularnewline
4 & -0.136541 & -0.946 & 0.174447 \tabularnewline
5 & 0.008619 & 0.0597 & 0.476315 \tabularnewline
6 & 0.124145 & 0.8601 & 0.197004 \tabularnewline
7 & -0.07045 & -0.4881 & 0.313852 \tabularnewline
8 & -0.0899 & -0.6228 & 0.268167 \tabularnewline
9 & -0.155709 & -1.0788 & 0.143038 \tabularnewline
10 & -0.106914 & -0.7407 & 0.231235 \tabularnewline
11 & -0.047831 & -0.3314 & 0.370898 \tabularnewline
12 & -0.238339 & -1.6513 & 0.052607 \tabularnewline
13 & 0.040735 & 0.2822 & 0.389493 \tabularnewline
14 & 0.218179 & 1.5116 & 0.068597 \tabularnewline
15 & 0.14782 & 1.0241 & 0.155455 \tabularnewline
16 & -0.066587 & -0.4613 & 0.323324 \tabularnewline
17 & -0.069567 & -0.482 & 0.316007 \tabularnewline
18 & 0.038432 & 0.2663 & 0.395589 \tabularnewline
19 & 0.003911 & 0.0271 & 0.489248 \tabularnewline
20 & -0.011492 & -0.0796 & 0.468435 \tabularnewline
21 & 0.128822 & 0.8925 & 0.188288 \tabularnewline
22 & -0.19297 & -1.3369 & 0.093772 \tabularnewline
23 & 0.207406 & 1.437 & 0.078609 \tabularnewline
24 & 0.033061 & 0.2291 & 0.409901 \tabularnewline
25 & 0.005909 & 0.0409 & 0.483756 \tabularnewline
26 & 0.031582 & 0.2188 & 0.413865 \tabularnewline
27 & -0.022292 & -0.1544 & 0.438955 \tabularnewline
28 & -0.232758 & -1.6126 & 0.056694 \tabularnewline
29 & -0.008303 & -0.0575 & 0.477182 \tabularnewline
30 & 0.04325 & 0.2996 & 0.382871 \tabularnewline
31 & -0.098711 & -0.6839 & 0.248667 \tabularnewline
32 & -0.041571 & -0.288 & 0.387288 \tabularnewline
33 & 0.01837 & 0.1273 & 0.44963 \tabularnewline
34 & -0.040358 & -0.2796 & 0.390489 \tabularnewline
35 & -0.008918 & -0.0618 & 0.475495 \tabularnewline
36 & 0.009458 & 0.0655 & 0.474013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61184&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]0.513864[/C][C]3.5602[/C][C]0.000424[/C][/ROW]
[ROW][C]2[/C][C]0.408422[/C][C]2.8296[/C][C]0.003392[/C][/ROW]
[ROW][C]3[/C][C]-0.122411[/C][C]-0.8481[/C][C]0.200299[/C][/ROW]
[ROW][C]4[/C][C]-0.136541[/C][C]-0.946[/C][C]0.174447[/C][/ROW]
[ROW][C]5[/C][C]0.008619[/C][C]0.0597[/C][C]0.476315[/C][/ROW]
[ROW][C]6[/C][C]0.124145[/C][C]0.8601[/C][C]0.197004[/C][/ROW]
[ROW][C]7[/C][C]-0.07045[/C][C]-0.4881[/C][C]0.313852[/C][/ROW]
[ROW][C]8[/C][C]-0.0899[/C][C]-0.6228[/C][C]0.268167[/C][/ROW]
[ROW][C]9[/C][C]-0.155709[/C][C]-1.0788[/C][C]0.143038[/C][/ROW]
[ROW][C]10[/C][C]-0.106914[/C][C]-0.7407[/C][C]0.231235[/C][/ROW]
[ROW][C]11[/C][C]-0.047831[/C][C]-0.3314[/C][C]0.370898[/C][/ROW]
[ROW][C]12[/C][C]-0.238339[/C][C]-1.6513[/C][C]0.052607[/C][/ROW]
[ROW][C]13[/C][C]0.040735[/C][C]0.2822[/C][C]0.389493[/C][/ROW]
[ROW][C]14[/C][C]0.218179[/C][C]1.5116[/C][C]0.068597[/C][/ROW]
[ROW][C]15[/C][C]0.14782[/C][C]1.0241[/C][C]0.155455[/C][/ROW]
[ROW][C]16[/C][C]-0.066587[/C][C]-0.4613[/C][C]0.323324[/C][/ROW]
[ROW][C]17[/C][C]-0.069567[/C][C]-0.482[/C][C]0.316007[/C][/ROW]
[ROW][C]18[/C][C]0.038432[/C][C]0.2663[/C][C]0.395589[/C][/ROW]
[ROW][C]19[/C][C]0.003911[/C][C]0.0271[/C][C]0.489248[/C][/ROW]
[ROW][C]20[/C][C]-0.011492[/C][C]-0.0796[/C][C]0.468435[/C][/ROW]
[ROW][C]21[/C][C]0.128822[/C][C]0.8925[/C][C]0.188288[/C][/ROW]
[ROW][C]22[/C][C]-0.19297[/C][C]-1.3369[/C][C]0.093772[/C][/ROW]
[ROW][C]23[/C][C]0.207406[/C][C]1.437[/C][C]0.078609[/C][/ROW]
[ROW][C]24[/C][C]0.033061[/C][C]0.2291[/C][C]0.409901[/C][/ROW]
[ROW][C]25[/C][C]0.005909[/C][C]0.0409[/C][C]0.483756[/C][/ROW]
[ROW][C]26[/C][C]0.031582[/C][C]0.2188[/C][C]0.413865[/C][/ROW]
[ROW][C]27[/C][C]-0.022292[/C][C]-0.1544[/C][C]0.438955[/C][/ROW]
[ROW][C]28[/C][C]-0.232758[/C][C]-1.6126[/C][C]0.056694[/C][/ROW]
[ROW][C]29[/C][C]-0.008303[/C][C]-0.0575[/C][C]0.477182[/C][/ROW]
[ROW][C]30[/C][C]0.04325[/C][C]0.2996[/C][C]0.382871[/C][/ROW]
[ROW][C]31[/C][C]-0.098711[/C][C]-0.6839[/C][C]0.248667[/C][/ROW]
[ROW][C]32[/C][C]-0.041571[/C][C]-0.288[/C][C]0.387288[/C][/ROW]
[ROW][C]33[/C][C]0.01837[/C][C]0.1273[/C][C]0.44963[/C][/ROW]
[ROW][C]34[/C][C]-0.040358[/C][C]-0.2796[/C][C]0.390489[/C][/ROW]
[ROW][C]35[/C][C]-0.008918[/C][C]-0.0618[/C][C]0.475495[/C][/ROW]
[ROW][C]36[/C][C]0.009458[/C][C]0.0655[/C][C]0.474013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61184&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61184&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
10.5138643.56020.000424
20.4084222.82960.003392
3-0.122411-0.84810.200299
4-0.136541-0.9460.174447
50.0086190.05970.476315
60.1241450.86010.197004
7-0.07045-0.48810.313852
8-0.0899-0.62280.268167
9-0.155709-1.07880.143038
10-0.106914-0.74070.231235
11-0.047831-0.33140.370898
12-0.238339-1.65130.052607
130.0407350.28220.389493
140.2181791.51160.068597
150.147821.02410.155455
16-0.066587-0.46130.323324
17-0.069567-0.4820.316007
180.0384320.26630.395589
190.0039110.02710.489248
20-0.011492-0.07960.468435
210.1288220.89250.188288
22-0.19297-1.33690.093772
230.2074061.4370.078609
240.0330610.22910.409901
250.0059090.04090.483756
260.0315820.21880.413865
27-0.022292-0.15440.438955
28-0.232758-1.61260.056694
29-0.008303-0.05750.477182
300.043250.29960.382871
31-0.098711-0.68390.248667
32-0.041571-0.2880.387288
330.018370.12730.44963
34-0.040358-0.27960.390489
35-0.008918-0.06180.475495
360.0094580.06550.474013



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')