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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 04 Dec 2008 11:19:15 -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/2008/Dec/04/t122841491090nc1h7jb7rpf6g.htm/, Retrieved Wed, 22 May 2024 05:23:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28996, Retrieved Wed, 22 May 2024 05:23:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [(P)ACF Transportm...] [2008-12-04 18:19:15] [b72e060d4eaf5aae1831b15bc791ef7e] [Current]
-   P     [(Partial) Autocorrelation Function] [(P)ACF Transportm...] [2008-12-09 17:06:01] [74be16979710d4c4e7c6647856088456]
- RMP     [Spectral Analysis] [Spectral Analysis...] [2008-12-09 17:23:26] [74be16979710d4c4e7c6647856088456]
- RMP     [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-09 17:30:45] [74be16979710d4c4e7c6647856088456]
- RMPD    [Cross Correlation Function] [Cross Correlation...] [2008-12-09 17:38:05] [74be16979710d4c4e7c6647856088456]
- RMP       [Pearson Correlation] [Pearson Correlation] [2008-12-12 13:23:51] [74be16979710d4c4e7c6647856088456]
-   PD      [Cross Correlation Function] [sqddssssdsss] [2008-12-17 10:28:49] [74be16979710d4c4e7c6647856088456]
-   PD        [Cross Correlation Function] [gvgfkjhgl;kjhg] [2008-12-18 09:49:28] [74be16979710d4c4e7c6647856088456]
F RMPD    [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-09 17:45:04] [74be16979710d4c4e7c6647856088456]
F   PD      [ARIMA Forecasting] [dfqsdfsq] [2008-12-15 17:32:11] [74be16979710d4c4e7c6647856088456]
- RMPD    [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-09 17:49:57] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.8
105.3
116.1
112.8
114.5
117.2
77.1
80.1
120.3
133.4
109.4
93.2
91.2
99.2
108.2
101.5
106.9
104.4
77.9
60
99.5
95
105.6
102.5
93.3
97.3
127
111.7
96.4
133
72.2
95.8
124.1
127.6
110.7
104.6
112.7
115.3
139.4
119
97.4
154
81.5
88.8
127.7
105.1
114.9
106.4
104.5
121.6
141.4
99
126.7
134.1
81.3
88.6
132.7
132.9
134.4
103.7
119.7
115
132.9
108.5
113.9
142
97.7
92.2
128.8
134.9
128.2
114.8
117.9

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=28996&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=28996&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28996&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
10.1791051.39890.08346
20.3700762.89040.002661
30.1869291.460.074716
40.0940250.73440.232772
50.2576032.01190.024324
60.1777691.38840.08503
7-0.026996-0.21080.416855
80.1539361.20230.116951
90.003510.02740.48911
10-0.130911-1.02240.155303
11-0.063915-0.49920.30972
12-0.475099-3.71060.000225
13-0.135679-1.05970.146733
14-0.241581-1.88680.031974
15-0.141391-1.10430.136901
16-0.153752-1.20080.117227
17-0.210444-1.64360.0527
18-0.194127-1.51620.067319
19-0.07565-0.59080.278403
20-0.183631-1.43420.07831
21-0.013146-0.10270.45928
22-0.19271-1.50510.068728
230.0225230.17590.430474
240.039120.30550.3805
250.0723960.56540.286928
260.1316281.0280.153994
270.044170.3450.36565
280.0077240.06030.476046
290.0947810.74030.230991
300.0329370.25720.398927
310.0121340.09480.462405
320.0700760.54730.29308
33-0.022376-0.17480.430923
340.1719221.34280.092164
350.0098180.07670.469565
36-0.043872-0.34270.366519

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.179105 & 1.3989 & 0.08346 \tabularnewline
2 & 0.370076 & 2.8904 & 0.002661 \tabularnewline
3 & 0.186929 & 1.46 & 0.074716 \tabularnewline
4 & 0.094025 & 0.7344 & 0.232772 \tabularnewline
5 & 0.257603 & 2.0119 & 0.024324 \tabularnewline
6 & 0.177769 & 1.3884 & 0.08503 \tabularnewline
7 & -0.026996 & -0.2108 & 0.416855 \tabularnewline
8 & 0.153936 & 1.2023 & 0.116951 \tabularnewline
9 & 0.00351 & 0.0274 & 0.48911 \tabularnewline
10 & -0.130911 & -1.0224 & 0.155303 \tabularnewline
11 & -0.063915 & -0.4992 & 0.30972 \tabularnewline
12 & -0.475099 & -3.7106 & 0.000225 \tabularnewline
13 & -0.135679 & -1.0597 & 0.146733 \tabularnewline
14 & -0.241581 & -1.8868 & 0.031974 \tabularnewline
15 & -0.141391 & -1.1043 & 0.136901 \tabularnewline
16 & -0.153752 & -1.2008 & 0.117227 \tabularnewline
17 & -0.210444 & -1.6436 & 0.0527 \tabularnewline
18 & -0.194127 & -1.5162 & 0.067319 \tabularnewline
19 & -0.07565 & -0.5908 & 0.278403 \tabularnewline
20 & -0.183631 & -1.4342 & 0.07831 \tabularnewline
21 & -0.013146 & -0.1027 & 0.45928 \tabularnewline
22 & -0.19271 & -1.5051 & 0.068728 \tabularnewline
23 & 0.022523 & 0.1759 & 0.430474 \tabularnewline
24 & 0.03912 & 0.3055 & 0.3805 \tabularnewline
25 & 0.072396 & 0.5654 & 0.286928 \tabularnewline
26 & 0.131628 & 1.028 & 0.153994 \tabularnewline
27 & 0.04417 & 0.345 & 0.36565 \tabularnewline
28 & 0.007724 & 0.0603 & 0.476046 \tabularnewline
29 & 0.094781 & 0.7403 & 0.230991 \tabularnewline
30 & 0.032937 & 0.2572 & 0.398927 \tabularnewline
31 & 0.012134 & 0.0948 & 0.462405 \tabularnewline
32 & 0.070076 & 0.5473 & 0.29308 \tabularnewline
33 & -0.022376 & -0.1748 & 0.430923 \tabularnewline
34 & 0.171922 & 1.3428 & 0.092164 \tabularnewline
35 & 0.009818 & 0.0767 & 0.469565 \tabularnewline
36 & -0.043872 & -0.3427 & 0.366519 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28996&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]0.179105[/C][C]1.3989[/C][C]0.08346[/C][/ROW]
[ROW][C]2[/C][C]0.370076[/C][C]2.8904[/C][C]0.002661[/C][/ROW]
[ROW][C]3[/C][C]0.186929[/C][C]1.46[/C][C]0.074716[/C][/ROW]
[ROW][C]4[/C][C]0.094025[/C][C]0.7344[/C][C]0.232772[/C][/ROW]
[ROW][C]5[/C][C]0.257603[/C][C]2.0119[/C][C]0.024324[/C][/ROW]
[ROW][C]6[/C][C]0.177769[/C][C]1.3884[/C][C]0.08503[/C][/ROW]
[ROW][C]7[/C][C]-0.026996[/C][C]-0.2108[/C][C]0.416855[/C][/ROW]
[ROW][C]8[/C][C]0.153936[/C][C]1.2023[/C][C]0.116951[/C][/ROW]
[ROW][C]9[/C][C]0.00351[/C][C]0.0274[/C][C]0.48911[/C][/ROW]
[ROW][C]10[/C][C]-0.130911[/C][C]-1.0224[/C][C]0.155303[/C][/ROW]
[ROW][C]11[/C][C]-0.063915[/C][C]-0.4992[/C][C]0.30972[/C][/ROW]
[ROW][C]12[/C][C]-0.475099[/C][C]-3.7106[/C][C]0.000225[/C][/ROW]
[ROW][C]13[/C][C]-0.135679[/C][C]-1.0597[/C][C]0.146733[/C][/ROW]
[ROW][C]14[/C][C]-0.241581[/C][C]-1.8868[/C][C]0.031974[/C][/ROW]
[ROW][C]15[/C][C]-0.141391[/C][C]-1.1043[/C][C]0.136901[/C][/ROW]
[ROW][C]16[/C][C]-0.153752[/C][C]-1.2008[/C][C]0.117227[/C][/ROW]
[ROW][C]17[/C][C]-0.210444[/C][C]-1.6436[/C][C]0.0527[/C][/ROW]
[ROW][C]18[/C][C]-0.194127[/C][C]-1.5162[/C][C]0.067319[/C][/ROW]
[ROW][C]19[/C][C]-0.07565[/C][C]-0.5908[/C][C]0.278403[/C][/ROW]
[ROW][C]20[/C][C]-0.183631[/C][C]-1.4342[/C][C]0.07831[/C][/ROW]
[ROW][C]21[/C][C]-0.013146[/C][C]-0.1027[/C][C]0.45928[/C][/ROW]
[ROW][C]22[/C][C]-0.19271[/C][C]-1.5051[/C][C]0.068728[/C][/ROW]
[ROW][C]23[/C][C]0.022523[/C][C]0.1759[/C][C]0.430474[/C][/ROW]
[ROW][C]24[/C][C]0.03912[/C][C]0.3055[/C][C]0.3805[/C][/ROW]
[ROW][C]25[/C][C]0.072396[/C][C]0.5654[/C][C]0.286928[/C][/ROW]
[ROW][C]26[/C][C]0.131628[/C][C]1.028[/C][C]0.153994[/C][/ROW]
[ROW][C]27[/C][C]0.04417[/C][C]0.345[/C][C]0.36565[/C][/ROW]
[ROW][C]28[/C][C]0.007724[/C][C]0.0603[/C][C]0.476046[/C][/ROW]
[ROW][C]29[/C][C]0.094781[/C][C]0.7403[/C][C]0.230991[/C][/ROW]
[ROW][C]30[/C][C]0.032937[/C][C]0.2572[/C][C]0.398927[/C][/ROW]
[ROW][C]31[/C][C]0.012134[/C][C]0.0948[/C][C]0.462405[/C][/ROW]
[ROW][C]32[/C][C]0.070076[/C][C]0.5473[/C][C]0.29308[/C][/ROW]
[ROW][C]33[/C][C]-0.022376[/C][C]-0.1748[/C][C]0.430923[/C][/ROW]
[ROW][C]34[/C][C]0.171922[/C][C]1.3428[/C][C]0.092164[/C][/ROW]
[ROW][C]35[/C][C]0.009818[/C][C]0.0767[/C][C]0.469565[/C][/ROW]
[ROW][C]36[/C][C]-0.043872[/C][C]-0.3427[/C][C]0.366519[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28996&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28996&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
10.1791051.39890.08346
20.3700762.89040.002661
30.1869291.460.074716
40.0940250.73440.232772
50.2576032.01190.024324
60.1777691.38840.08503
7-0.026996-0.21080.416855
80.1539361.20230.116951
90.003510.02740.48911
10-0.130911-1.02240.155303
11-0.063915-0.49920.30972
12-0.475099-3.71060.000225
13-0.135679-1.05970.146733
14-0.241581-1.88680.031974
15-0.141391-1.10430.136901
16-0.153752-1.20080.117227
17-0.210444-1.64360.0527
18-0.194127-1.51620.067319
19-0.07565-0.59080.278403
20-0.183631-1.43420.07831
21-0.013146-0.10270.45928
22-0.19271-1.50510.068728
230.0225230.17590.430474
240.039120.30550.3805
250.0723960.56540.286928
260.1316281.0280.153994
270.044170.3450.36565
280.0077240.06030.476046
290.0947810.74030.230991
300.0329370.25720.398927
310.0121340.09480.462405
320.0700760.54730.29308
33-0.022376-0.17480.430923
340.1719221.34280.092164
350.0098180.07670.469565
36-0.043872-0.34270.366519






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1791051.39890.08346
20.34922.72730.004163
30.0955990.74670.229071
4-0.075705-0.59130.278262
50.1874771.46420.074131
60.1396681.09080.139817
7-0.250506-1.95650.027493
80.0495270.38680.350118
90.0891210.69610.244518
10-0.311764-2.4350.008917
11-0.169372-1.32280.095414
12-0.365724-2.85640.002925
13-0.003832-0.02990.488112
14-0.023453-0.18320.427634
150.0803720.62770.266264
160.0206670.16140.436151
170.0199820.15610.438249
180.0888080.69360.245278
190.0486050.37960.352775
20-0.009085-0.0710.471831
210.1148450.8970.186631
22-0.305173-2.38350.010139
23-0.003607-0.02820.488808
24-0.109216-0.8530.198497
250.0580860.45370.325839
260.054680.42710.335419
270.0311680.24340.404243
28-0.096161-0.7510.227758
29-0.046451-0.36280.359007
300.0289820.22640.41084
31-0.078062-0.60970.272167
32-0.12799-0.99960.160718
330.1015090.79280.215481
34-0.031209-0.24380.40412
350.0257660.20120.42059
36-0.129749-1.01340.157442

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.179105 & 1.3989 & 0.08346 \tabularnewline
2 & 0.3492 & 2.7273 & 0.004163 \tabularnewline
3 & 0.095599 & 0.7467 & 0.229071 \tabularnewline
4 & -0.075705 & -0.5913 & 0.278262 \tabularnewline
5 & 0.187477 & 1.4642 & 0.074131 \tabularnewline
6 & 0.139668 & 1.0908 & 0.139817 \tabularnewline
7 & -0.250506 & -1.9565 & 0.027493 \tabularnewline
8 & 0.049527 & 0.3868 & 0.350118 \tabularnewline
9 & 0.089121 & 0.6961 & 0.244518 \tabularnewline
10 & -0.311764 & -2.435 & 0.008917 \tabularnewline
11 & -0.169372 & -1.3228 & 0.095414 \tabularnewline
12 & -0.365724 & -2.8564 & 0.002925 \tabularnewline
13 & -0.003832 & -0.0299 & 0.488112 \tabularnewline
14 & -0.023453 & -0.1832 & 0.427634 \tabularnewline
15 & 0.080372 & 0.6277 & 0.266264 \tabularnewline
16 & 0.020667 & 0.1614 & 0.436151 \tabularnewline
17 & 0.019982 & 0.1561 & 0.438249 \tabularnewline
18 & 0.088808 & 0.6936 & 0.245278 \tabularnewline
19 & 0.048605 & 0.3796 & 0.352775 \tabularnewline
20 & -0.009085 & -0.071 & 0.471831 \tabularnewline
21 & 0.114845 & 0.897 & 0.186631 \tabularnewline
22 & -0.305173 & -2.3835 & 0.010139 \tabularnewline
23 & -0.003607 & -0.0282 & 0.488808 \tabularnewline
24 & -0.109216 & -0.853 & 0.198497 \tabularnewline
25 & 0.058086 & 0.4537 & 0.325839 \tabularnewline
26 & 0.05468 & 0.4271 & 0.335419 \tabularnewline
27 & 0.031168 & 0.2434 & 0.404243 \tabularnewline
28 & -0.096161 & -0.751 & 0.227758 \tabularnewline
29 & -0.046451 & -0.3628 & 0.359007 \tabularnewline
30 & 0.028982 & 0.2264 & 0.41084 \tabularnewline
31 & -0.078062 & -0.6097 & 0.272167 \tabularnewline
32 & -0.12799 & -0.9996 & 0.160718 \tabularnewline
33 & 0.101509 & 0.7928 & 0.215481 \tabularnewline
34 & -0.031209 & -0.2438 & 0.40412 \tabularnewline
35 & 0.025766 & 0.2012 & 0.42059 \tabularnewline
36 & -0.129749 & -1.0134 & 0.157442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28996&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]0.179105[/C][C]1.3989[/C][C]0.08346[/C][/ROW]
[ROW][C]2[/C][C]0.3492[/C][C]2.7273[/C][C]0.004163[/C][/ROW]
[ROW][C]3[/C][C]0.095599[/C][C]0.7467[/C][C]0.229071[/C][/ROW]
[ROW][C]4[/C][C]-0.075705[/C][C]-0.5913[/C][C]0.278262[/C][/ROW]
[ROW][C]5[/C][C]0.187477[/C][C]1.4642[/C][C]0.074131[/C][/ROW]
[ROW][C]6[/C][C]0.139668[/C][C]1.0908[/C][C]0.139817[/C][/ROW]
[ROW][C]7[/C][C]-0.250506[/C][C]-1.9565[/C][C]0.027493[/C][/ROW]
[ROW][C]8[/C][C]0.049527[/C][C]0.3868[/C][C]0.350118[/C][/ROW]
[ROW][C]9[/C][C]0.089121[/C][C]0.6961[/C][C]0.244518[/C][/ROW]
[ROW][C]10[/C][C]-0.311764[/C][C]-2.435[/C][C]0.008917[/C][/ROW]
[ROW][C]11[/C][C]-0.169372[/C][C]-1.3228[/C][C]0.095414[/C][/ROW]
[ROW][C]12[/C][C]-0.365724[/C][C]-2.8564[/C][C]0.002925[/C][/ROW]
[ROW][C]13[/C][C]-0.003832[/C][C]-0.0299[/C][C]0.488112[/C][/ROW]
[ROW][C]14[/C][C]-0.023453[/C][C]-0.1832[/C][C]0.427634[/C][/ROW]
[ROW][C]15[/C][C]0.080372[/C][C]0.6277[/C][C]0.266264[/C][/ROW]
[ROW][C]16[/C][C]0.020667[/C][C]0.1614[/C][C]0.436151[/C][/ROW]
[ROW][C]17[/C][C]0.019982[/C][C]0.1561[/C][C]0.438249[/C][/ROW]
[ROW][C]18[/C][C]0.088808[/C][C]0.6936[/C][C]0.245278[/C][/ROW]
[ROW][C]19[/C][C]0.048605[/C][C]0.3796[/C][C]0.352775[/C][/ROW]
[ROW][C]20[/C][C]-0.009085[/C][C]-0.071[/C][C]0.471831[/C][/ROW]
[ROW][C]21[/C][C]0.114845[/C][C]0.897[/C][C]0.186631[/C][/ROW]
[ROW][C]22[/C][C]-0.305173[/C][C]-2.3835[/C][C]0.010139[/C][/ROW]
[ROW][C]23[/C][C]-0.003607[/C][C]-0.0282[/C][C]0.488808[/C][/ROW]
[ROW][C]24[/C][C]-0.109216[/C][C]-0.853[/C][C]0.198497[/C][/ROW]
[ROW][C]25[/C][C]0.058086[/C][C]0.4537[/C][C]0.325839[/C][/ROW]
[ROW][C]26[/C][C]0.05468[/C][C]0.4271[/C][C]0.335419[/C][/ROW]
[ROW][C]27[/C][C]0.031168[/C][C]0.2434[/C][C]0.404243[/C][/ROW]
[ROW][C]28[/C][C]-0.096161[/C][C]-0.751[/C][C]0.227758[/C][/ROW]
[ROW][C]29[/C][C]-0.046451[/C][C]-0.3628[/C][C]0.359007[/C][/ROW]
[ROW][C]30[/C][C]0.028982[/C][C]0.2264[/C][C]0.41084[/C][/ROW]
[ROW][C]31[/C][C]-0.078062[/C][C]-0.6097[/C][C]0.272167[/C][/ROW]
[ROW][C]32[/C][C]-0.12799[/C][C]-0.9996[/C][C]0.160718[/C][/ROW]
[ROW][C]33[/C][C]0.101509[/C][C]0.7928[/C][C]0.215481[/C][/ROW]
[ROW][C]34[/C][C]-0.031209[/C][C]-0.2438[/C][C]0.40412[/C][/ROW]
[ROW][C]35[/C][C]0.025766[/C][C]0.2012[/C][C]0.42059[/C][/ROW]
[ROW][C]36[/C][C]-0.129749[/C][C]-1.0134[/C][C]0.157442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28996&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28996&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
10.1791051.39890.08346
20.34922.72730.004163
30.0955990.74670.229071
4-0.075705-0.59130.278262
50.1874771.46420.074131
60.1396681.09080.139817
7-0.250506-1.95650.027493
80.0495270.38680.350118
90.0891210.69610.244518
10-0.311764-2.4350.008917
11-0.169372-1.32280.095414
12-0.365724-2.85640.002925
13-0.003832-0.02990.488112
14-0.023453-0.18320.427634
150.0803720.62770.266264
160.0206670.16140.436151
170.0199820.15610.438249
180.0888080.69360.245278
190.0486050.37960.352775
20-0.009085-0.0710.471831
210.1148450.8970.186631
22-0.305173-2.38350.010139
23-0.003607-0.02820.488808
24-0.109216-0.8530.198497
250.0580860.45370.325839
260.054680.42710.335419
270.0311680.24340.404243
28-0.096161-0.7510.227758
29-0.046451-0.36280.359007
300.0289820.22640.41084
31-0.078062-0.60970.272167
32-0.12799-0.99960.160718
330.1015090.79280.215481
34-0.031209-0.24380.40412
350.0257660.20120.42059
36-0.129749-1.01340.157442


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')