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Description of Statistical Computation

Author's title

Method 1:ACF - d=D=0, 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 12:46:18 -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/t12613384202ruk95ekfo6vgf7.htm/, Retrieved Sat, 27 Apr 2024 10:26:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70002, Retrieved Sat, 27 Apr 2024 10:26:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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 13:43:54] [74be16979710d4c4e7c6647856088456]
- R                 [(Partial) Autocorrelation Function] [Method 1:ACF - d=...] [2009-12-20 19:46:18] [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=70002&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=70002&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70002&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
10.1063140.83030.204793
2-0.180062-1.40630.08235
30.0278120.21720.414382
4-0.040386-0.31540.376759
50.2489161.94410.02825
60.337762.6380.005284
70.1520761.18770.119768
8-0.057511-0.44920.327449
9-0.076246-0.59550.276855
10-0.211807-1.65430.051605
110.057930.45240.326276
120.6223174.86054e-06
130.003540.02770.489016
14-0.238898-1.86590.033436
15-0.068367-0.5340.297653
16-0.101209-0.79050.216158
170.1437571.12280.132965
180.2023171.58010.059623
190.0268850.210.417192
20-0.138784-1.08390.141328
21-0.131616-1.0280.154015
22-0.269356-2.10370.019766
230.0194530.15190.43987
240.3401642.65680.005028
25-0.07083-0.55320.291075
26-0.256608-2.00420.024749
27-0.179473-1.40170.083032
28-0.103451-0.8080.211121
290.0624540.48780.313726
300.0782560.61120.271669
31-0.024947-0.19480.423083
32-0.173715-1.35680.089929
33-0.166067-1.2970.099754
34-0.164418-1.28410.101974
35-0.040409-0.31560.37669
360.1820821.42210.080044

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.106314 & 0.8303 & 0.204793 \tabularnewline
2 & -0.180062 & -1.4063 & 0.08235 \tabularnewline
3 & 0.027812 & 0.2172 & 0.414382 \tabularnewline
4 & -0.040386 & -0.3154 & 0.376759 \tabularnewline
5 & 0.248916 & 1.9441 & 0.02825 \tabularnewline
6 & 0.33776 & 2.638 & 0.005284 \tabularnewline
7 & 0.152076 & 1.1877 & 0.119768 \tabularnewline
8 & -0.057511 & -0.4492 & 0.327449 \tabularnewline
9 & -0.076246 & -0.5955 & 0.276855 \tabularnewline
10 & -0.211807 & -1.6543 & 0.051605 \tabularnewline
11 & 0.05793 & 0.4524 & 0.326276 \tabularnewline
12 & 0.622317 & 4.8605 & 4e-06 \tabularnewline
13 & 0.00354 & 0.0277 & 0.489016 \tabularnewline
14 & -0.238898 & -1.8659 & 0.033436 \tabularnewline
15 & -0.068367 & -0.534 & 0.297653 \tabularnewline
16 & -0.101209 & -0.7905 & 0.216158 \tabularnewline
17 & 0.143757 & 1.1228 & 0.132965 \tabularnewline
18 & 0.202317 & 1.5801 & 0.059623 \tabularnewline
19 & 0.026885 & 0.21 & 0.417192 \tabularnewline
20 & -0.138784 & -1.0839 & 0.141328 \tabularnewline
21 & -0.131616 & -1.028 & 0.154015 \tabularnewline
22 & -0.269356 & -2.1037 & 0.019766 \tabularnewline
23 & 0.019453 & 0.1519 & 0.43987 \tabularnewline
24 & 0.340164 & 2.6568 & 0.005028 \tabularnewline
25 & -0.07083 & -0.5532 & 0.291075 \tabularnewline
26 & -0.256608 & -2.0042 & 0.024749 \tabularnewline
27 & -0.179473 & -1.4017 & 0.083032 \tabularnewline
28 & -0.103451 & -0.808 & 0.211121 \tabularnewline
29 & 0.062454 & 0.4878 & 0.313726 \tabularnewline
30 & 0.078256 & 0.6112 & 0.271669 \tabularnewline
31 & -0.024947 & -0.1948 & 0.423083 \tabularnewline
32 & -0.173715 & -1.3568 & 0.089929 \tabularnewline
33 & -0.166067 & -1.297 & 0.099754 \tabularnewline
34 & -0.164418 & -1.2841 & 0.101974 \tabularnewline
35 & -0.040409 & -0.3156 & 0.37669 \tabularnewline
36 & 0.182082 & 1.4221 & 0.080044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70002&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]0.106314[/C][C]0.8303[/C][C]0.204793[/C][/ROW]
[ROW][C]2[/C][C]-0.180062[/C][C]-1.4063[/C][C]0.08235[/C][/ROW]
[ROW][C]3[/C][C]0.027812[/C][C]0.2172[/C][C]0.414382[/C][/ROW]
[ROW][C]4[/C][C]-0.040386[/C][C]-0.3154[/C][C]0.376759[/C][/ROW]
[ROW][C]5[/C][C]0.248916[/C][C]1.9441[/C][C]0.02825[/C][/ROW]
[ROW][C]6[/C][C]0.33776[/C][C]2.638[/C][C]0.005284[/C][/ROW]
[ROW][C]7[/C][C]0.152076[/C][C]1.1877[/C][C]0.119768[/C][/ROW]
[ROW][C]8[/C][C]-0.057511[/C][C]-0.4492[/C][C]0.327449[/C][/ROW]
[ROW][C]9[/C][C]-0.076246[/C][C]-0.5955[/C][C]0.276855[/C][/ROW]
[ROW][C]10[/C][C]-0.211807[/C][C]-1.6543[/C][C]0.051605[/C][/ROW]
[ROW][C]11[/C][C]0.05793[/C][C]0.4524[/C][C]0.326276[/C][/ROW]
[ROW][C]12[/C][C]0.622317[/C][C]4.8605[/C][C]4e-06[/C][/ROW]
[ROW][C]13[/C][C]0.00354[/C][C]0.0277[/C][C]0.489016[/C][/ROW]
[ROW][C]14[/C][C]-0.238898[/C][C]-1.8659[/C][C]0.033436[/C][/ROW]
[ROW][C]15[/C][C]-0.068367[/C][C]-0.534[/C][C]0.297653[/C][/ROW]
[ROW][C]16[/C][C]-0.101209[/C][C]-0.7905[/C][C]0.216158[/C][/ROW]
[ROW][C]17[/C][C]0.143757[/C][C]1.1228[/C][C]0.132965[/C][/ROW]
[ROW][C]18[/C][C]0.202317[/C][C]1.5801[/C][C]0.059623[/C][/ROW]
[ROW][C]19[/C][C]0.026885[/C][C]0.21[/C][C]0.417192[/C][/ROW]
[ROW][C]20[/C][C]-0.138784[/C][C]-1.0839[/C][C]0.141328[/C][/ROW]
[ROW][C]21[/C][C]-0.131616[/C][C]-1.028[/C][C]0.154015[/C][/ROW]
[ROW][C]22[/C][C]-0.269356[/C][C]-2.1037[/C][C]0.019766[/C][/ROW]
[ROW][C]23[/C][C]0.019453[/C][C]0.1519[/C][C]0.43987[/C][/ROW]
[ROW][C]24[/C][C]0.340164[/C][C]2.6568[/C][C]0.005028[/C][/ROW]
[ROW][C]25[/C][C]-0.07083[/C][C]-0.5532[/C][C]0.291075[/C][/ROW]
[ROW][C]26[/C][C]-0.256608[/C][C]-2.0042[/C][C]0.024749[/C][/ROW]
[ROW][C]27[/C][C]-0.179473[/C][C]-1.4017[/C][C]0.083032[/C][/ROW]
[ROW][C]28[/C][C]-0.103451[/C][C]-0.808[/C][C]0.211121[/C][/ROW]
[ROW][C]29[/C][C]0.062454[/C][C]0.4878[/C][C]0.313726[/C][/ROW]
[ROW][C]30[/C][C]0.078256[/C][C]0.6112[/C][C]0.271669[/C][/ROW]
[ROW][C]31[/C][C]-0.024947[/C][C]-0.1948[/C][C]0.423083[/C][/ROW]
[ROW][C]32[/C][C]-0.173715[/C][C]-1.3568[/C][C]0.089929[/C][/ROW]
[ROW][C]33[/C][C]-0.166067[/C][C]-1.297[/C][C]0.099754[/C][/ROW]
[ROW][C]34[/C][C]-0.164418[/C][C]-1.2841[/C][C]0.101974[/C][/ROW]
[ROW][C]35[/C][C]-0.040409[/C][C]-0.3156[/C][C]0.37669[/C][/ROW]
[ROW][C]36[/C][C]0.182082[/C][C]1.4221[/C][C]0.080044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70002&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70002&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
10.1063140.83030.204793
2-0.180062-1.40630.08235
30.0278120.21720.414382
4-0.040386-0.31540.376759
50.2489161.94410.02825
60.337762.6380.005284
70.1520761.18770.119768
8-0.057511-0.44920.327449
9-0.076246-0.59550.276855
10-0.211807-1.65430.051605
110.057930.45240.326276
120.6223174.86054e-06
130.003540.02770.489016
14-0.238898-1.86590.033436
15-0.068367-0.5340.297653
16-0.101209-0.79050.216158
170.1437571.12280.132965
180.2023171.58010.059623
190.0268850.210.417192
20-0.138784-1.08390.141328
21-0.131616-1.0280.154015
22-0.269356-2.10370.019766
230.0194530.15190.43987
240.3401642.65680.005028
25-0.07083-0.55320.291075
26-0.256608-2.00420.024749
27-0.179473-1.40170.083032
28-0.103451-0.8080.211121
290.0624540.48780.313726
300.0782560.61120.271669
31-0.024947-0.19480.423083
32-0.173715-1.35680.089929
33-0.166067-1.2970.099754
34-0.164418-1.28410.101974
35-0.040409-0.31560.37669
360.1820821.42210.080044






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1063140.83030.204793
2-0.193553-1.51170.067888
30.0748560.58460.280471
4-0.093876-0.73320.233123
50.3059062.38920.009996
60.2607252.03630.023033
70.2497721.95080.02784
80.0015640.01220.495146
9-0.000994-0.00780.496915
10-0.384636-3.00410.00193
11-0.124642-0.97350.167078
120.4751333.71090.000224
13-0.086725-0.67730.250375
14-0.035895-0.28040.390078
15-0.048446-0.37840.353233
160.0235440.18390.427355
17-0.087645-0.68450.248118
18-0.07045-0.55020.292086
19-0.049093-0.38340.351368
20-0.095218-0.74370.229964
210.0086150.06730.473288
22-0.144396-1.12780.131917
230.0364160.28440.388526
24-0.131918-1.03030.153465
250.0675690.52770.299801
26-0.0577-0.45060.326921
27-0.031989-0.24980.401773
280.0457080.3570.361165
29-0.027935-0.21820.41401
30-0.046818-0.36570.357941
31-0.034147-0.26670.395302
32-0.039219-0.30630.380205
33-0.097018-0.75770.225764
340.1348081.05290.148273
35-0.176074-1.37520.087052
360.0097150.07590.469882

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.106314 & 0.8303 & 0.204793 \tabularnewline
2 & -0.193553 & -1.5117 & 0.067888 \tabularnewline
3 & 0.074856 & 0.5846 & 0.280471 \tabularnewline
4 & -0.093876 & -0.7332 & 0.233123 \tabularnewline
5 & 0.305906 & 2.3892 & 0.009996 \tabularnewline
6 & 0.260725 & 2.0363 & 0.023033 \tabularnewline
7 & 0.249772 & 1.9508 & 0.02784 \tabularnewline
8 & 0.001564 & 0.0122 & 0.495146 \tabularnewline
9 & -0.000994 & -0.0078 & 0.496915 \tabularnewline
10 & -0.384636 & -3.0041 & 0.00193 \tabularnewline
11 & -0.124642 & -0.9735 & 0.167078 \tabularnewline
12 & 0.475133 & 3.7109 & 0.000224 \tabularnewline
13 & -0.086725 & -0.6773 & 0.250375 \tabularnewline
14 & -0.035895 & -0.2804 & 0.390078 \tabularnewline
15 & -0.048446 & -0.3784 & 0.353233 \tabularnewline
16 & 0.023544 & 0.1839 & 0.427355 \tabularnewline
17 & -0.087645 & -0.6845 & 0.248118 \tabularnewline
18 & -0.07045 & -0.5502 & 0.292086 \tabularnewline
19 & -0.049093 & -0.3834 & 0.351368 \tabularnewline
20 & -0.095218 & -0.7437 & 0.229964 \tabularnewline
21 & 0.008615 & 0.0673 & 0.473288 \tabularnewline
22 & -0.144396 & -1.1278 & 0.131917 \tabularnewline
23 & 0.036416 & 0.2844 & 0.388526 \tabularnewline
24 & -0.131918 & -1.0303 & 0.153465 \tabularnewline
25 & 0.067569 & 0.5277 & 0.299801 \tabularnewline
26 & -0.0577 & -0.4506 & 0.326921 \tabularnewline
27 & -0.031989 & -0.2498 & 0.401773 \tabularnewline
28 & 0.045708 & 0.357 & 0.361165 \tabularnewline
29 & -0.027935 & -0.2182 & 0.41401 \tabularnewline
30 & -0.046818 & -0.3657 & 0.357941 \tabularnewline
31 & -0.034147 & -0.2667 & 0.395302 \tabularnewline
32 & -0.039219 & -0.3063 & 0.380205 \tabularnewline
33 & -0.097018 & -0.7577 & 0.225764 \tabularnewline
34 & 0.134808 & 1.0529 & 0.148273 \tabularnewline
35 & -0.176074 & -1.3752 & 0.087052 \tabularnewline
36 & 0.009715 & 0.0759 & 0.469882 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70002&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]0.106314[/C][C]0.8303[/C][C]0.204793[/C][/ROW]
[ROW][C]2[/C][C]-0.193553[/C][C]-1.5117[/C][C]0.067888[/C][/ROW]
[ROW][C]3[/C][C]0.074856[/C][C]0.5846[/C][C]0.280471[/C][/ROW]
[ROW][C]4[/C][C]-0.093876[/C][C]-0.7332[/C][C]0.233123[/C][/ROW]
[ROW][C]5[/C][C]0.305906[/C][C]2.3892[/C][C]0.009996[/C][/ROW]
[ROW][C]6[/C][C]0.260725[/C][C]2.0363[/C][C]0.023033[/C][/ROW]
[ROW][C]7[/C][C]0.249772[/C][C]1.9508[/C][C]0.02784[/C][/ROW]
[ROW][C]8[/C][C]0.001564[/C][C]0.0122[/C][C]0.495146[/C][/ROW]
[ROW][C]9[/C][C]-0.000994[/C][C]-0.0078[/C][C]0.496915[/C][/ROW]
[ROW][C]10[/C][C]-0.384636[/C][C]-3.0041[/C][C]0.00193[/C][/ROW]
[ROW][C]11[/C][C]-0.124642[/C][C]-0.9735[/C][C]0.167078[/C][/ROW]
[ROW][C]12[/C][C]0.475133[/C][C]3.7109[/C][C]0.000224[/C][/ROW]
[ROW][C]13[/C][C]-0.086725[/C][C]-0.6773[/C][C]0.250375[/C][/ROW]
[ROW][C]14[/C][C]-0.035895[/C][C]-0.2804[/C][C]0.390078[/C][/ROW]
[ROW][C]15[/C][C]-0.048446[/C][C]-0.3784[/C][C]0.353233[/C][/ROW]
[ROW][C]16[/C][C]0.023544[/C][C]0.1839[/C][C]0.427355[/C][/ROW]
[ROW][C]17[/C][C]-0.087645[/C][C]-0.6845[/C][C]0.248118[/C][/ROW]
[ROW][C]18[/C][C]-0.07045[/C][C]-0.5502[/C][C]0.292086[/C][/ROW]
[ROW][C]19[/C][C]-0.049093[/C][C]-0.3834[/C][C]0.351368[/C][/ROW]
[ROW][C]20[/C][C]-0.095218[/C][C]-0.7437[/C][C]0.229964[/C][/ROW]
[ROW][C]21[/C][C]0.008615[/C][C]0.0673[/C][C]0.473288[/C][/ROW]
[ROW][C]22[/C][C]-0.144396[/C][C]-1.1278[/C][C]0.131917[/C][/ROW]
[ROW][C]23[/C][C]0.036416[/C][C]0.2844[/C][C]0.388526[/C][/ROW]
[ROW][C]24[/C][C]-0.131918[/C][C]-1.0303[/C][C]0.153465[/C][/ROW]
[ROW][C]25[/C][C]0.067569[/C][C]0.5277[/C][C]0.299801[/C][/ROW]
[ROW][C]26[/C][C]-0.0577[/C][C]-0.4506[/C][C]0.326921[/C][/ROW]
[ROW][C]27[/C][C]-0.031989[/C][C]-0.2498[/C][C]0.401773[/C][/ROW]
[ROW][C]28[/C][C]0.045708[/C][C]0.357[/C][C]0.361165[/C][/ROW]
[ROW][C]29[/C][C]-0.027935[/C][C]-0.2182[/C][C]0.41401[/C][/ROW]
[ROW][C]30[/C][C]-0.046818[/C][C]-0.3657[/C][C]0.357941[/C][/ROW]
[ROW][C]31[/C][C]-0.034147[/C][C]-0.2667[/C][C]0.395302[/C][/ROW]
[ROW][C]32[/C][C]-0.039219[/C][C]-0.3063[/C][C]0.380205[/C][/ROW]
[ROW][C]33[/C][C]-0.097018[/C][C]-0.7577[/C][C]0.225764[/C][/ROW]
[ROW][C]34[/C][C]0.134808[/C][C]1.0529[/C][C]0.148273[/C][/ROW]
[ROW][C]35[/C][C]-0.176074[/C][C]-1.3752[/C][C]0.087052[/C][/ROW]
[ROW][C]36[/C][C]0.009715[/C][C]0.0759[/C][C]0.469882[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70002&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70002&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
10.1063140.83030.204793
2-0.193553-1.51170.067888
30.0748560.58460.280471
4-0.093876-0.73320.233123
50.3059062.38920.009996
60.2607252.03630.023033
70.2497721.95080.02784
80.0015640.01220.495146
9-0.000994-0.00780.496915
10-0.384636-3.00410.00193
11-0.124642-0.97350.167078
120.4751333.71090.000224
13-0.086725-0.67730.250375
14-0.035895-0.28040.390078
15-0.048446-0.37840.353233
160.0235440.18390.427355
17-0.087645-0.68450.248118
18-0.07045-0.55020.292086
19-0.049093-0.38340.351368
20-0.095218-0.74370.229964
210.0086150.06730.473288
22-0.144396-1.12780.131917
230.0364160.28440.388526
24-0.131918-1.03030.153465
250.0675690.52770.299801
26-0.0577-0.45060.326921
27-0.031989-0.24980.401773
280.0457080.3570.361165
29-0.027935-0.21820.41401
30-0.046818-0.36570.357941
31-0.034147-0.26670.395302
32-0.039219-0.30630.380205
33-0.097018-0.75770.225764
340.1348081.05290.148273
35-0.176074-1.37520.087052
360.0097150.07590.469882


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 = 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')