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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 computationSun, 20 Dec 2009 09:07:26 -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/t1261325287goat5ao38xhe7yy.htm/, Retrieved Sat, 27 Apr 2024 10:10:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69926, Retrieved Sat, 27 Apr 2024 10:10:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8.1] [2009-11-27 19:35:53] [4a2be4899cba879e4eea9daa25281df8]
-    D          [(Partial) Autocorrelation Function] [PAPER 5] [2009-12-20 01:17:09] [4a2be4899cba879e4eea9daa25281df8]
-    D            [(Partial) Autocorrelation Function] [PAPER 12] [2009-12-20 01:36:32] [4a2be4899cba879e4eea9daa25281df8]
-    D                [(Partial) Autocorrelation Function] [paper 2] [2009-12-20 16:07:26] [71c065898bd1c08eef04509b4bcee039] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
31,48
29,90
33,84
39,12
33,70
25,09
51,44
45,59
52,52
48,56
41,75
49,59
32,75
33,38
35,65
37,03
35,68
20,97
58,55
54,96
65,54
51,57
51,15
46,64
35,70
33,25
35,19
41,67
34,87
21,21
56,13
49,23
59,72
48,10
47,47
50,50
40,06
34,15
36,86
46,36
36,58
23,87
57,28
56,39
57,66
62,30
48,93
51,17
39,64
33,21
38,13
43,29
30,60
21,96
48,03
46,15
50,74
48,11
38,39
44,11

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=69926&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=69926&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69926&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
10.3712722.87590.002785
20.1728231.33870.092862
30.0035110.02720.489198
4-0.144071-1.1160.134443
5-0.259584-2.01070.024427
6-0.540782-4.18894.7e-05
7-0.324668-2.51490.007303
8-0.206272-1.59780.057673
9-0.069712-0.540.295602
100.0710290.55020.292116
110.2493271.93130.029088
120.7451025.77150
130.27592.13710.018337
140.1201890.9310.177798
15-0.003348-0.02590.489698
16-0.109704-0.84980.199418
17-0.207941-1.61070.056247
18-0.445078-3.44760.00052
19-0.274791-2.12850.018705
20-0.179761-1.39240.084467
21-0.079011-0.6120.271419
220.0235510.18240.427932
230.1714711.32820.09457
240.5361214.15285.3e-05
250.240661.86410.033598
260.1058970.82030.207654
270.0325870.25240.40079
28-0.06879-0.53280.298054
29-0.11315-0.87650.192139
30-0.309804-2.39970.009764
31-0.206964-1.60310.057079
32-0.151892-1.17650.122011
33-0.094863-0.73480.232661
34-0.016328-0.12650.449889
350.0655810.5080.306661
360.3046692.360.010774

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.371272 & 2.8759 & 0.002785 \tabularnewline
2 & 0.172823 & 1.3387 & 0.092862 \tabularnewline
3 & 0.003511 & 0.0272 & 0.489198 \tabularnewline
4 & -0.144071 & -1.116 & 0.134443 \tabularnewline
5 & -0.259584 & -2.0107 & 0.024427 \tabularnewline
6 & -0.540782 & -4.1889 & 4.7e-05 \tabularnewline
7 & -0.324668 & -2.5149 & 0.007303 \tabularnewline
8 & -0.206272 & -1.5978 & 0.057673 \tabularnewline
9 & -0.069712 & -0.54 & 0.295602 \tabularnewline
10 & 0.071029 & 0.5502 & 0.292116 \tabularnewline
11 & 0.249327 & 1.9313 & 0.029088 \tabularnewline
12 & 0.745102 & 5.7715 & 0 \tabularnewline
13 & 0.2759 & 2.1371 & 0.018337 \tabularnewline
14 & 0.120189 & 0.931 & 0.177798 \tabularnewline
15 & -0.003348 & -0.0259 & 0.489698 \tabularnewline
16 & -0.109704 & -0.8498 & 0.199418 \tabularnewline
17 & -0.207941 & -1.6107 & 0.056247 \tabularnewline
18 & -0.445078 & -3.4476 & 0.00052 \tabularnewline
19 & -0.274791 & -2.1285 & 0.018705 \tabularnewline
20 & -0.179761 & -1.3924 & 0.084467 \tabularnewline
21 & -0.079011 & -0.612 & 0.271419 \tabularnewline
22 & 0.023551 & 0.1824 & 0.427932 \tabularnewline
23 & 0.171471 & 1.3282 & 0.09457 \tabularnewline
24 & 0.536121 & 4.1528 & 5.3e-05 \tabularnewline
25 & 0.24066 & 1.8641 & 0.033598 \tabularnewline
26 & 0.105897 & 0.8203 & 0.207654 \tabularnewline
27 & 0.032587 & 0.2524 & 0.40079 \tabularnewline
28 & -0.06879 & -0.5328 & 0.298054 \tabularnewline
29 & -0.11315 & -0.8765 & 0.192139 \tabularnewline
30 & -0.309804 & -2.3997 & 0.009764 \tabularnewline
31 & -0.206964 & -1.6031 & 0.057079 \tabularnewline
32 & -0.151892 & -1.1765 & 0.122011 \tabularnewline
33 & -0.094863 & -0.7348 & 0.232661 \tabularnewline
34 & -0.016328 & -0.1265 & 0.449889 \tabularnewline
35 & 0.065581 & 0.508 & 0.306661 \tabularnewline
36 & 0.304669 & 2.36 & 0.010774 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69926&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]0.371272[/C][C]2.8759[/C][C]0.002785[/C][/ROW]
[ROW][C]2[/C][C]0.172823[/C][C]1.3387[/C][C]0.092862[/C][/ROW]
[ROW][C]3[/C][C]0.003511[/C][C]0.0272[/C][C]0.489198[/C][/ROW]
[ROW][C]4[/C][C]-0.144071[/C][C]-1.116[/C][C]0.134443[/C][/ROW]
[ROW][C]5[/C][C]-0.259584[/C][C]-2.0107[/C][C]0.024427[/C][/ROW]
[ROW][C]6[/C][C]-0.540782[/C][C]-4.1889[/C][C]4.7e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.324668[/C][C]-2.5149[/C][C]0.007303[/C][/ROW]
[ROW][C]8[/C][C]-0.206272[/C][C]-1.5978[/C][C]0.057673[/C][/ROW]
[ROW][C]9[/C][C]-0.069712[/C][C]-0.54[/C][C]0.295602[/C][/ROW]
[ROW][C]10[/C][C]0.071029[/C][C]0.5502[/C][C]0.292116[/C][/ROW]
[ROW][C]11[/C][C]0.249327[/C][C]1.9313[/C][C]0.029088[/C][/ROW]
[ROW][C]12[/C][C]0.745102[/C][C]5.7715[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.2759[/C][C]2.1371[/C][C]0.018337[/C][/ROW]
[ROW][C]14[/C][C]0.120189[/C][C]0.931[/C][C]0.177798[/C][/ROW]
[ROW][C]15[/C][C]-0.003348[/C][C]-0.0259[/C][C]0.489698[/C][/ROW]
[ROW][C]16[/C][C]-0.109704[/C][C]-0.8498[/C][C]0.199418[/C][/ROW]
[ROW][C]17[/C][C]-0.207941[/C][C]-1.6107[/C][C]0.056247[/C][/ROW]
[ROW][C]18[/C][C]-0.445078[/C][C]-3.4476[/C][C]0.00052[/C][/ROW]
[ROW][C]19[/C][C]-0.274791[/C][C]-2.1285[/C][C]0.018705[/C][/ROW]
[ROW][C]20[/C][C]-0.179761[/C][C]-1.3924[/C][C]0.084467[/C][/ROW]
[ROW][C]21[/C][C]-0.079011[/C][C]-0.612[/C][C]0.271419[/C][/ROW]
[ROW][C]22[/C][C]0.023551[/C][C]0.1824[/C][C]0.427932[/C][/ROW]
[ROW][C]23[/C][C]0.171471[/C][C]1.3282[/C][C]0.09457[/C][/ROW]
[ROW][C]24[/C][C]0.536121[/C][C]4.1528[/C][C]5.3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.24066[/C][C]1.8641[/C][C]0.033598[/C][/ROW]
[ROW][C]26[/C][C]0.105897[/C][C]0.8203[/C][C]0.207654[/C][/ROW]
[ROW][C]27[/C][C]0.032587[/C][C]0.2524[/C][C]0.40079[/C][/ROW]
[ROW][C]28[/C][C]-0.06879[/C][C]-0.5328[/C][C]0.298054[/C][/ROW]
[ROW][C]29[/C][C]-0.11315[/C][C]-0.8765[/C][C]0.192139[/C][/ROW]
[ROW][C]30[/C][C]-0.309804[/C][C]-2.3997[/C][C]0.009764[/C][/ROW]
[ROW][C]31[/C][C]-0.206964[/C][C]-1.6031[/C][C]0.057079[/C][/ROW]
[ROW][C]32[/C][C]-0.151892[/C][C]-1.1765[/C][C]0.122011[/C][/ROW]
[ROW][C]33[/C][C]-0.094863[/C][C]-0.7348[/C][C]0.232661[/C][/ROW]
[ROW][C]34[/C][C]-0.016328[/C][C]-0.1265[/C][C]0.449889[/C][/ROW]
[ROW][C]35[/C][C]0.065581[/C][C]0.508[/C][C]0.306661[/C][/ROW]
[ROW][C]36[/C][C]0.304669[/C][C]2.36[/C][C]0.010774[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69926&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69926&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
10.3712722.87590.002785
20.1728231.33870.092862
30.0035110.02720.489198
4-0.144071-1.1160.134443
5-0.259584-2.01070.024427
6-0.540782-4.18894.7e-05
7-0.324668-2.51490.007303
8-0.206272-1.59780.057673
9-0.069712-0.540.295602
100.0710290.55020.292116
110.2493271.93130.029088
120.7451025.77150
130.27592.13710.018337
140.1201890.9310.177798
15-0.003348-0.02590.489698
16-0.109704-0.84980.199418
17-0.207941-1.61070.056247
18-0.445078-3.44760.00052
19-0.274791-2.12850.018705
20-0.179761-1.39240.084467
21-0.079011-0.6120.271419
220.0235510.18240.427932
230.1714711.32820.09457
240.5361214.15285.3e-05
250.240661.86410.033598
260.1058970.82030.207654
270.0325870.25240.40079
28-0.06879-0.53280.298054
29-0.11315-0.87650.192139
30-0.309804-2.39970.009764
31-0.206964-1.60310.057079
32-0.151892-1.17650.122011
33-0.094863-0.73480.232661
34-0.016328-0.12650.449889
350.0655810.5080.306661
360.3046692.360.010774






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3712722.87590.002785
20.0405730.31430.377201
3-0.084943-0.6580.256537
4-0.147494-1.14250.128896
5-0.178944-1.38610.085424
6-0.451555-3.49770.000445
7-0.023616-0.18290.427736
8-0.063111-0.48890.313362
9-0.044111-0.34170.366892
10-0.009618-0.07450.470429
110.1216120.9420.174985
120.624564.83785e-06
13-0.352501-2.73050.004145
14-0.15501-1.20070.117292
15-0.018557-0.14370.443092
160.0041530.03220.487222
17-0.035785-0.27720.391294
180.1327261.02810.154017
190.029030.22490.411425
20-0.064768-0.50170.308861
21-0.066604-0.51590.303907
22-0.028524-0.22090.412943
23-0.040781-0.31590.376593
24-0.076283-0.59090.278409
250.1617741.25310.107516
260.0031630.02450.490268
270.0127330.09860.460881
28-0.078695-0.60960.272225
290.1133830.87830.191653
30-0.017632-0.13660.445913
31-0.033813-0.26190.397142
32-0.024371-0.18880.425453
330.004040.03130.487569
34-0.036242-0.28070.389941
35-0.102283-0.79230.215659
36-0.10065-0.77960.219337

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.371272 & 2.8759 & 0.002785 \tabularnewline
2 & 0.040573 & 0.3143 & 0.377201 \tabularnewline
3 & -0.084943 & -0.658 & 0.256537 \tabularnewline
4 & -0.147494 & -1.1425 & 0.128896 \tabularnewline
5 & -0.178944 & -1.3861 & 0.085424 \tabularnewline
6 & -0.451555 & -3.4977 & 0.000445 \tabularnewline
7 & -0.023616 & -0.1829 & 0.427736 \tabularnewline
8 & -0.063111 & -0.4889 & 0.313362 \tabularnewline
9 & -0.044111 & -0.3417 & 0.366892 \tabularnewline
10 & -0.009618 & -0.0745 & 0.470429 \tabularnewline
11 & 0.121612 & 0.942 & 0.174985 \tabularnewline
12 & 0.62456 & 4.8378 & 5e-06 \tabularnewline
13 & -0.352501 & -2.7305 & 0.004145 \tabularnewline
14 & -0.15501 & -1.2007 & 0.117292 \tabularnewline
15 & -0.018557 & -0.1437 & 0.443092 \tabularnewline
16 & 0.004153 & 0.0322 & 0.487222 \tabularnewline
17 & -0.035785 & -0.2772 & 0.391294 \tabularnewline
18 & 0.132726 & 1.0281 & 0.154017 \tabularnewline
19 & 0.02903 & 0.2249 & 0.411425 \tabularnewline
20 & -0.064768 & -0.5017 & 0.308861 \tabularnewline
21 & -0.066604 & -0.5159 & 0.303907 \tabularnewline
22 & -0.028524 & -0.2209 & 0.412943 \tabularnewline
23 & -0.040781 & -0.3159 & 0.376593 \tabularnewline
24 & -0.076283 & -0.5909 & 0.278409 \tabularnewline
25 & 0.161774 & 1.2531 & 0.107516 \tabularnewline
26 & 0.003163 & 0.0245 & 0.490268 \tabularnewline
27 & 0.012733 & 0.0986 & 0.460881 \tabularnewline
28 & -0.078695 & -0.6096 & 0.272225 \tabularnewline
29 & 0.113383 & 0.8783 & 0.191653 \tabularnewline
30 & -0.017632 & -0.1366 & 0.445913 \tabularnewline
31 & -0.033813 & -0.2619 & 0.397142 \tabularnewline
32 & -0.024371 & -0.1888 & 0.425453 \tabularnewline
33 & 0.00404 & 0.0313 & 0.487569 \tabularnewline
34 & -0.036242 & -0.2807 & 0.389941 \tabularnewline
35 & -0.102283 & -0.7923 & 0.215659 \tabularnewline
36 & -0.10065 & -0.7796 & 0.219337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69926&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]0.371272[/C][C]2.8759[/C][C]0.002785[/C][/ROW]
[ROW][C]2[/C][C]0.040573[/C][C]0.3143[/C][C]0.377201[/C][/ROW]
[ROW][C]3[/C][C]-0.084943[/C][C]-0.658[/C][C]0.256537[/C][/ROW]
[ROW][C]4[/C][C]-0.147494[/C][C]-1.1425[/C][C]0.128896[/C][/ROW]
[ROW][C]5[/C][C]-0.178944[/C][C]-1.3861[/C][C]0.085424[/C][/ROW]
[ROW][C]6[/C][C]-0.451555[/C][C]-3.4977[/C][C]0.000445[/C][/ROW]
[ROW][C]7[/C][C]-0.023616[/C][C]-0.1829[/C][C]0.427736[/C][/ROW]
[ROW][C]8[/C][C]-0.063111[/C][C]-0.4889[/C][C]0.313362[/C][/ROW]
[ROW][C]9[/C][C]-0.044111[/C][C]-0.3417[/C][C]0.366892[/C][/ROW]
[ROW][C]10[/C][C]-0.009618[/C][C]-0.0745[/C][C]0.470429[/C][/ROW]
[ROW][C]11[/C][C]0.121612[/C][C]0.942[/C][C]0.174985[/C][/ROW]
[ROW][C]12[/C][C]0.62456[/C][C]4.8378[/C][C]5e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.352501[/C][C]-2.7305[/C][C]0.004145[/C][/ROW]
[ROW][C]14[/C][C]-0.15501[/C][C]-1.2007[/C][C]0.117292[/C][/ROW]
[ROW][C]15[/C][C]-0.018557[/C][C]-0.1437[/C][C]0.443092[/C][/ROW]
[ROW][C]16[/C][C]0.004153[/C][C]0.0322[/C][C]0.487222[/C][/ROW]
[ROW][C]17[/C][C]-0.035785[/C][C]-0.2772[/C][C]0.391294[/C][/ROW]
[ROW][C]18[/C][C]0.132726[/C][C]1.0281[/C][C]0.154017[/C][/ROW]
[ROW][C]19[/C][C]0.02903[/C][C]0.2249[/C][C]0.411425[/C][/ROW]
[ROW][C]20[/C][C]-0.064768[/C][C]-0.5017[/C][C]0.308861[/C][/ROW]
[ROW][C]21[/C][C]-0.066604[/C][C]-0.5159[/C][C]0.303907[/C][/ROW]
[ROW][C]22[/C][C]-0.028524[/C][C]-0.2209[/C][C]0.412943[/C][/ROW]
[ROW][C]23[/C][C]-0.040781[/C][C]-0.3159[/C][C]0.376593[/C][/ROW]
[ROW][C]24[/C][C]-0.076283[/C][C]-0.5909[/C][C]0.278409[/C][/ROW]
[ROW][C]25[/C][C]0.161774[/C][C]1.2531[/C][C]0.107516[/C][/ROW]
[ROW][C]26[/C][C]0.003163[/C][C]0.0245[/C][C]0.490268[/C][/ROW]
[ROW][C]27[/C][C]0.012733[/C][C]0.0986[/C][C]0.460881[/C][/ROW]
[ROW][C]28[/C][C]-0.078695[/C][C]-0.6096[/C][C]0.272225[/C][/ROW]
[ROW][C]29[/C][C]0.113383[/C][C]0.8783[/C][C]0.191653[/C][/ROW]
[ROW][C]30[/C][C]-0.017632[/C][C]-0.1366[/C][C]0.445913[/C][/ROW]
[ROW][C]31[/C][C]-0.033813[/C][C]-0.2619[/C][C]0.397142[/C][/ROW]
[ROW][C]32[/C][C]-0.024371[/C][C]-0.1888[/C][C]0.425453[/C][/ROW]
[ROW][C]33[/C][C]0.00404[/C][C]0.0313[/C][C]0.487569[/C][/ROW]
[ROW][C]34[/C][C]-0.036242[/C][C]-0.2807[/C][C]0.389941[/C][/ROW]
[ROW][C]35[/C][C]-0.102283[/C][C]-0.7923[/C][C]0.215659[/C][/ROW]
[ROW][C]36[/C][C]-0.10065[/C][C]-0.7796[/C][C]0.219337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69926&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69926&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
10.3712722.87590.002785
20.0405730.31430.377201
3-0.084943-0.6580.256537
4-0.147494-1.14250.128896
5-0.178944-1.38610.085424
6-0.451555-3.49770.000445
7-0.023616-0.18290.427736
8-0.063111-0.48890.313362
9-0.044111-0.34170.366892
10-0.009618-0.07450.470429
110.1216120.9420.174985
120.624564.83785e-06
13-0.352501-2.73050.004145
14-0.15501-1.20070.117292
15-0.018557-0.14370.443092
160.0041530.03220.487222
17-0.035785-0.27720.391294
180.1327261.02810.154017
190.029030.22490.411425
20-0.064768-0.50170.308861
21-0.066604-0.51590.303907
22-0.028524-0.22090.412943
23-0.040781-0.31590.376593
24-0.076283-0.59090.278409
250.1617741.25310.107516
260.0031630.02450.490268
270.0127330.09860.460881
28-0.078695-0.60960.272225
290.1133830.87830.191653
30-0.017632-0.13660.445913
31-0.033813-0.26190.397142
32-0.024371-0.18880.425453
330.004040.03130.487569
34-0.036242-0.28070.389941
35-0.102283-0.79230.215659
36-0.10065-0.77960.219337


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')