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Description of Statistical Computation

Author's title

Method-1: ACF - d=0, D=1, lambda =1 - Totale industriële productie index me...

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 12:48:42 -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/t1261338559ehwuker3udgz8c2.htm/, Retrieved Sat, 27 Apr 2024 10:27:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70003, Retrieved Sat, 27 Apr 2024 10:27:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

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 13:46:33] [74be16979710d4c4e7c6647856088456]
- R P               [(Partial) Autocorrelation Function] [Method-1: ACF - d...] [2009-12-20 19:48:42] [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 time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70003&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]2 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=70003&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70003&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1140990.79870.214161
20.3472552.43080.009386
30.3256832.27980.013506
40.0087250.06110.475775
50.1870891.30960.098215
60.1019960.7140.239317
70.0096680.06770.473159
80.0737440.51620.304014
9-0.023383-0.16370.435329
100.0403630.28250.389358
11-0.020399-0.14280.44352
12-0.054968-0.38480.351035
130.0074390.05210.479341
14-0.038736-0.27120.393707
15-0.046939-0.32860.371939
16-0.082102-0.57470.284057
17-0.050101-0.35070.363656
18-0.085562-0.59890.275988
19-0.142032-0.99420.162499
20-0.025429-0.1780.429726
21-0.10667-0.74670.229409
22-0.219384-1.53570.065524
230.0429340.30050.382519
24-0.254743-1.78320.040374
25-0.086843-0.60790.273031
26-0.044246-0.30970.379044
27-0.219316-1.53520.065582
28-0.081885-0.57320.284568
29-0.101966-0.71380.23938
30-0.14588-1.02120.156096
31-0.103202-0.72240.236736
32-0.152578-1.0680.145367
33-0.10551-0.73860.231846
34-0.133633-0.93540.177077
35-0.099454-0.69620.244804
36-0.02444-0.17110.432433

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.114099 & 0.7987 & 0.214161 \tabularnewline
2 & 0.347255 & 2.4308 & 0.009386 \tabularnewline
3 & 0.325683 & 2.2798 & 0.013506 \tabularnewline
4 & 0.008725 & 0.0611 & 0.475775 \tabularnewline
5 & 0.187089 & 1.3096 & 0.098215 \tabularnewline
6 & 0.101996 & 0.714 & 0.239317 \tabularnewline
7 & 0.009668 & 0.0677 & 0.473159 \tabularnewline
8 & 0.073744 & 0.5162 & 0.304014 \tabularnewline
9 & -0.023383 & -0.1637 & 0.435329 \tabularnewline
10 & 0.040363 & 0.2825 & 0.389358 \tabularnewline
11 & -0.020399 & -0.1428 & 0.44352 \tabularnewline
12 & -0.054968 & -0.3848 & 0.351035 \tabularnewline
13 & 0.007439 & 0.0521 & 0.479341 \tabularnewline
14 & -0.038736 & -0.2712 & 0.393707 \tabularnewline
15 & -0.046939 & -0.3286 & 0.371939 \tabularnewline
16 & -0.082102 & -0.5747 & 0.284057 \tabularnewline
17 & -0.050101 & -0.3507 & 0.363656 \tabularnewline
18 & -0.085562 & -0.5989 & 0.275988 \tabularnewline
19 & -0.142032 & -0.9942 & 0.162499 \tabularnewline
20 & -0.025429 & -0.178 & 0.429726 \tabularnewline
21 & -0.10667 & -0.7467 & 0.229409 \tabularnewline
22 & -0.219384 & -1.5357 & 0.065524 \tabularnewline
23 & 0.042934 & 0.3005 & 0.382519 \tabularnewline
24 & -0.254743 & -1.7832 & 0.040374 \tabularnewline
25 & -0.086843 & -0.6079 & 0.273031 \tabularnewline
26 & -0.044246 & -0.3097 & 0.379044 \tabularnewline
27 & -0.219316 & -1.5352 & 0.065582 \tabularnewline
28 & -0.081885 & -0.5732 & 0.284568 \tabularnewline
29 & -0.101966 & -0.7138 & 0.23938 \tabularnewline
30 & -0.14588 & -1.0212 & 0.156096 \tabularnewline
31 & -0.103202 & -0.7224 & 0.236736 \tabularnewline
32 & -0.152578 & -1.068 & 0.145367 \tabularnewline
33 & -0.10551 & -0.7386 & 0.231846 \tabularnewline
34 & -0.133633 & -0.9354 & 0.177077 \tabularnewline
35 & -0.099454 & -0.6962 & 0.244804 \tabularnewline
36 & -0.02444 & -0.1711 & 0.432433 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70003&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]0.114099[/C][C]0.7987[/C][C]0.214161[/C][/ROW]
[ROW][C]2[/C][C]0.347255[/C][C]2.4308[/C][C]0.009386[/C][/ROW]
[ROW][C]3[/C][C]0.325683[/C][C]2.2798[/C][C]0.013506[/C][/ROW]
[ROW][C]4[/C][C]0.008725[/C][C]0.0611[/C][C]0.475775[/C][/ROW]
[ROW][C]5[/C][C]0.187089[/C][C]1.3096[/C][C]0.098215[/C][/ROW]
[ROW][C]6[/C][C]0.101996[/C][C]0.714[/C][C]0.239317[/C][/ROW]
[ROW][C]7[/C][C]0.009668[/C][C]0.0677[/C][C]0.473159[/C][/ROW]
[ROW][C]8[/C][C]0.073744[/C][C]0.5162[/C][C]0.304014[/C][/ROW]
[ROW][C]9[/C][C]-0.023383[/C][C]-0.1637[/C][C]0.435329[/C][/ROW]
[ROW][C]10[/C][C]0.040363[/C][C]0.2825[/C][C]0.389358[/C][/ROW]
[ROW][C]11[/C][C]-0.020399[/C][C]-0.1428[/C][C]0.44352[/C][/ROW]
[ROW][C]12[/C][C]-0.054968[/C][C]-0.3848[/C][C]0.351035[/C][/ROW]
[ROW][C]13[/C][C]0.007439[/C][C]0.0521[/C][C]0.479341[/C][/ROW]
[ROW][C]14[/C][C]-0.038736[/C][C]-0.2712[/C][C]0.393707[/C][/ROW]
[ROW][C]15[/C][C]-0.046939[/C][C]-0.3286[/C][C]0.371939[/C][/ROW]
[ROW][C]16[/C][C]-0.082102[/C][C]-0.5747[/C][C]0.284057[/C][/ROW]
[ROW][C]17[/C][C]-0.050101[/C][C]-0.3507[/C][C]0.363656[/C][/ROW]
[ROW][C]18[/C][C]-0.085562[/C][C]-0.5989[/C][C]0.275988[/C][/ROW]
[ROW][C]19[/C][C]-0.142032[/C][C]-0.9942[/C][C]0.162499[/C][/ROW]
[ROW][C]20[/C][C]-0.025429[/C][C]-0.178[/C][C]0.429726[/C][/ROW]
[ROW][C]21[/C][C]-0.10667[/C][C]-0.7467[/C][C]0.229409[/C][/ROW]
[ROW][C]22[/C][C]-0.219384[/C][C]-1.5357[/C][C]0.065524[/C][/ROW]
[ROW][C]23[/C][C]0.042934[/C][C]0.3005[/C][C]0.382519[/C][/ROW]
[ROW][C]24[/C][C]-0.254743[/C][C]-1.7832[/C][C]0.040374[/C][/ROW]
[ROW][C]25[/C][C]-0.086843[/C][C]-0.6079[/C][C]0.273031[/C][/ROW]
[ROW][C]26[/C][C]-0.044246[/C][C]-0.3097[/C][C]0.379044[/C][/ROW]
[ROW][C]27[/C][C]-0.219316[/C][C]-1.5352[/C][C]0.065582[/C][/ROW]
[ROW][C]28[/C][C]-0.081885[/C][C]-0.5732[/C][C]0.284568[/C][/ROW]
[ROW][C]29[/C][C]-0.101966[/C][C]-0.7138[/C][C]0.23938[/C][/ROW]
[ROW][C]30[/C][C]-0.14588[/C][C]-1.0212[/C][C]0.156096[/C][/ROW]
[ROW][C]31[/C][C]-0.103202[/C][C]-0.7224[/C][C]0.236736[/C][/ROW]
[ROW][C]32[/C][C]-0.152578[/C][C]-1.068[/C][C]0.145367[/C][/ROW]
[ROW][C]33[/C][C]-0.10551[/C][C]-0.7386[/C][C]0.231846[/C][/ROW]
[ROW][C]34[/C][C]-0.133633[/C][C]-0.9354[/C][C]0.177077[/C][/ROW]
[ROW][C]35[/C][C]-0.099454[/C][C]-0.6962[/C][C]0.244804[/C][/ROW]
[ROW][C]36[/C][C]-0.02444[/C][C]-0.1711[/C][C]0.432433[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70003&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70003&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
10.1140990.79870.214161
20.3472552.43080.009386
30.3256832.27980.013506
40.0087250.06110.475775
50.1870891.30960.098215
60.1019960.7140.239317
70.0096680.06770.473159
80.0737440.51620.304014
9-0.023383-0.16370.435329
100.0403630.28250.389358
11-0.020399-0.14280.44352
12-0.054968-0.38480.351035
130.0074390.05210.479341
14-0.038736-0.27120.393707
15-0.046939-0.32860.371939
16-0.082102-0.57470.284057
17-0.050101-0.35070.363656
18-0.085562-0.59890.275988
19-0.142032-0.99420.162499
20-0.025429-0.1780.429726
21-0.10667-0.74670.229409
22-0.219384-1.53570.065524
230.0429340.30050.382519
24-0.254743-1.78320.040374
25-0.086843-0.60790.273031
26-0.044246-0.30970.379044
27-0.219316-1.53520.065582
28-0.081885-0.57320.284568
29-0.101966-0.71380.23938
30-0.14588-1.02120.156096
31-0.103202-0.72240.236736
32-0.152578-1.0680.145367
33-0.10551-0.73860.231846
34-0.133633-0.93540.177077
35-0.099454-0.69620.244804
36-0.02444-0.17110.432433






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1140990.79870.214161
20.3386452.37050.010871
30.2985142.08960.020934
4-0.159263-1.11480.135178
5-0.021302-0.14910.441039
60.0701820.49130.312712
7-0.008512-0.05960.476364
8-0.043346-0.30340.381428
9-0.054632-0.38240.3519
100.0624260.4370.332023
11-0.022061-0.15440.438953
12-0.081553-0.57090.285349
130.0020750.01450.494234
140.0441890.30930.379194
15-0.030115-0.21080.416956
16-0.1283-0.89810.186763
170.0027430.01920.492379
180.0143660.10060.460155
19-0.115857-0.8110.210644
200.0033960.02380.490565
210.0319810.22390.411896
22-0.190467-1.33330.094305
230.0709410.49660.31085
24-0.10264-0.71850.237936
25-0.020242-0.14170.443952
260.0114990.08050.468087
27-0.082367-0.57660.283436
28-0.095441-0.66810.253606
290.0116460.08150.467679
30-0.006058-0.04240.483175
31-0.121324-0.84930.199931
32-0.081562-0.57090.285327
33-0.009996-0.070.472249
34-0.062534-0.43770.33175
35-0.035175-0.24620.403267
360.0501750.35120.363463

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.114099 & 0.7987 & 0.214161 \tabularnewline
2 & 0.338645 & 2.3705 & 0.010871 \tabularnewline
3 & 0.298514 & 2.0896 & 0.020934 \tabularnewline
4 & -0.159263 & -1.1148 & 0.135178 \tabularnewline
5 & -0.021302 & -0.1491 & 0.441039 \tabularnewline
6 & 0.070182 & 0.4913 & 0.312712 \tabularnewline
7 & -0.008512 & -0.0596 & 0.476364 \tabularnewline
8 & -0.043346 & -0.3034 & 0.381428 \tabularnewline
9 & -0.054632 & -0.3824 & 0.3519 \tabularnewline
10 & 0.062426 & 0.437 & 0.332023 \tabularnewline
11 & -0.022061 & -0.1544 & 0.438953 \tabularnewline
12 & -0.081553 & -0.5709 & 0.285349 \tabularnewline
13 & 0.002075 & 0.0145 & 0.494234 \tabularnewline
14 & 0.044189 & 0.3093 & 0.379194 \tabularnewline
15 & -0.030115 & -0.2108 & 0.416956 \tabularnewline
16 & -0.1283 & -0.8981 & 0.186763 \tabularnewline
17 & 0.002743 & 0.0192 & 0.492379 \tabularnewline
18 & 0.014366 & 0.1006 & 0.460155 \tabularnewline
19 & -0.115857 & -0.811 & 0.210644 \tabularnewline
20 & 0.003396 & 0.0238 & 0.490565 \tabularnewline
21 & 0.031981 & 0.2239 & 0.411896 \tabularnewline
22 & -0.190467 & -1.3333 & 0.094305 \tabularnewline
23 & 0.070941 & 0.4966 & 0.31085 \tabularnewline
24 & -0.10264 & -0.7185 & 0.237936 \tabularnewline
25 & -0.020242 & -0.1417 & 0.443952 \tabularnewline
26 & 0.011499 & 0.0805 & 0.468087 \tabularnewline
27 & -0.082367 & -0.5766 & 0.283436 \tabularnewline
28 & -0.095441 & -0.6681 & 0.253606 \tabularnewline
29 & 0.011646 & 0.0815 & 0.467679 \tabularnewline
30 & -0.006058 & -0.0424 & 0.483175 \tabularnewline
31 & -0.121324 & -0.8493 & 0.199931 \tabularnewline
32 & -0.081562 & -0.5709 & 0.285327 \tabularnewline
33 & -0.009996 & -0.07 & 0.472249 \tabularnewline
34 & -0.062534 & -0.4377 & 0.33175 \tabularnewline
35 & -0.035175 & -0.2462 & 0.403267 \tabularnewline
36 & 0.050175 & 0.3512 & 0.363463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70003&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]0.114099[/C][C]0.7987[/C][C]0.214161[/C][/ROW]
[ROW][C]2[/C][C]0.338645[/C][C]2.3705[/C][C]0.010871[/C][/ROW]
[ROW][C]3[/C][C]0.298514[/C][C]2.0896[/C][C]0.020934[/C][/ROW]
[ROW][C]4[/C][C]-0.159263[/C][C]-1.1148[/C][C]0.135178[/C][/ROW]
[ROW][C]5[/C][C]-0.021302[/C][C]-0.1491[/C][C]0.441039[/C][/ROW]
[ROW][C]6[/C][C]0.070182[/C][C]0.4913[/C][C]0.312712[/C][/ROW]
[ROW][C]7[/C][C]-0.008512[/C][C]-0.0596[/C][C]0.476364[/C][/ROW]
[ROW][C]8[/C][C]-0.043346[/C][C]-0.3034[/C][C]0.381428[/C][/ROW]
[ROW][C]9[/C][C]-0.054632[/C][C]-0.3824[/C][C]0.3519[/C][/ROW]
[ROW][C]10[/C][C]0.062426[/C][C]0.437[/C][C]0.332023[/C][/ROW]
[ROW][C]11[/C][C]-0.022061[/C][C]-0.1544[/C][C]0.438953[/C][/ROW]
[ROW][C]12[/C][C]-0.081553[/C][C]-0.5709[/C][C]0.285349[/C][/ROW]
[ROW][C]13[/C][C]0.002075[/C][C]0.0145[/C][C]0.494234[/C][/ROW]
[ROW][C]14[/C][C]0.044189[/C][C]0.3093[/C][C]0.379194[/C][/ROW]
[ROW][C]15[/C][C]-0.030115[/C][C]-0.2108[/C][C]0.416956[/C][/ROW]
[ROW][C]16[/C][C]-0.1283[/C][C]-0.8981[/C][C]0.186763[/C][/ROW]
[ROW][C]17[/C][C]0.002743[/C][C]0.0192[/C][C]0.492379[/C][/ROW]
[ROW][C]18[/C][C]0.014366[/C][C]0.1006[/C][C]0.460155[/C][/ROW]
[ROW][C]19[/C][C]-0.115857[/C][C]-0.811[/C][C]0.210644[/C][/ROW]
[ROW][C]20[/C][C]0.003396[/C][C]0.0238[/C][C]0.490565[/C][/ROW]
[ROW][C]21[/C][C]0.031981[/C][C]0.2239[/C][C]0.411896[/C][/ROW]
[ROW][C]22[/C][C]-0.190467[/C][C]-1.3333[/C][C]0.094305[/C][/ROW]
[ROW][C]23[/C][C]0.070941[/C][C]0.4966[/C][C]0.31085[/C][/ROW]
[ROW][C]24[/C][C]-0.10264[/C][C]-0.7185[/C][C]0.237936[/C][/ROW]
[ROW][C]25[/C][C]-0.020242[/C][C]-0.1417[/C][C]0.443952[/C][/ROW]
[ROW][C]26[/C][C]0.011499[/C][C]0.0805[/C][C]0.468087[/C][/ROW]
[ROW][C]27[/C][C]-0.082367[/C][C]-0.5766[/C][C]0.283436[/C][/ROW]
[ROW][C]28[/C][C]-0.095441[/C][C]-0.6681[/C][C]0.253606[/C][/ROW]
[ROW][C]29[/C][C]0.011646[/C][C]0.0815[/C][C]0.467679[/C][/ROW]
[ROW][C]30[/C][C]-0.006058[/C][C]-0.0424[/C][C]0.483175[/C][/ROW]
[ROW][C]31[/C][C]-0.121324[/C][C]-0.8493[/C][C]0.199931[/C][/ROW]
[ROW][C]32[/C][C]-0.081562[/C][C]-0.5709[/C][C]0.285327[/C][/ROW]
[ROW][C]33[/C][C]-0.009996[/C][C]-0.07[/C][C]0.472249[/C][/ROW]
[ROW][C]34[/C][C]-0.062534[/C][C]-0.4377[/C][C]0.33175[/C][/ROW]
[ROW][C]35[/C][C]-0.035175[/C][C]-0.2462[/C][C]0.403267[/C][/ROW]
[ROW][C]36[/C][C]0.050175[/C][C]0.3512[/C][C]0.363463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70003&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70003&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
10.1140990.79870.214161
20.3386452.37050.010871
30.2985142.08960.020934
4-0.159263-1.11480.135178
5-0.021302-0.14910.441039
60.0701820.49130.312712
7-0.008512-0.05960.476364
8-0.043346-0.30340.381428
9-0.054632-0.38240.3519
100.0624260.4370.332023
11-0.022061-0.15440.438953
12-0.081553-0.57090.285349
130.0020750.01450.494234
140.0441890.30930.379194
15-0.030115-0.21080.416956
16-0.1283-0.89810.186763
170.0027430.01920.492379
180.0143660.10060.460155
19-0.115857-0.8110.210644
200.0033960.02380.490565
210.0319810.22390.411896
22-0.190467-1.33330.094305
230.0709410.49660.31085
24-0.10264-0.71850.237936
25-0.020242-0.14170.443952
260.0114990.08050.468087
27-0.082367-0.57660.283436
28-0.095441-0.66810.253606
290.0116460.08150.467679
30-0.006058-0.04240.483175
31-0.121324-0.84930.199931
32-0.081562-0.57090.285327
33-0.009996-0.070.472249
34-0.062534-0.43770.33175
35-0.035175-0.24620.403267
360.0501750.35120.363463


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 = 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')