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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 computationSat, 12 Dec 2009 11:25:21 -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/12/t1260643622bkzkynhd7oay10y.htm/, Retrieved Mon, 29 Apr 2024 15:17:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67122, Retrieved Mon, 29 Apr 2024 15:17:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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] [WS8 D=0 en d=0] [2009-11-25 16:06:53] [445b292c553470d9fed8bc2796fd3a00]
-    D          [(Partial) Autocorrelation Function] [ws 8 d=0 D=0] [2009-11-25 20:46:27] [134dc66689e3d457a82860db6471d419]
-   P               [(Partial) Autocorrelation Function] [Paper PAF IGP d=1...] [2009-12-12 18:25:21] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.01
103.84
104.48
95.43
104.80
108.64
105.65
108.42
115.35
113.64
115.24
100.33
101.29
104.48
99.26
100.11
103.52
101.18
96.39
97.56
96.39
85.10
79.77
79.13
80.84
82.75
92.55
96.60
96.92
95.32
98.52
100.22
104.91
103.10
97.13
103.42
111.72
118.11
111.62
100.22
102.03
105.76
107.68
110.77
105.44
112.26
114.07
117.90
124.72
126.42
134.73
135.79
143.36
140.37
144.74
151.98
150.92
163.38
154.43
146.66
157.95
162.10
180.42
179.57
171.58
185.43
190.64
203.00
202.36
193.41
186.17
192.24
209.60
206.41
209.82
230.37
235.80
232.07
244.64
242.19
217.48
209.39
211.73
221.00
203.11
214.71
224.19
238.04
238.36
246.24
259.87
249.97
266.48
282.98
306.31
301.73
314.62
332.62
355.51
370.32
408.13
433.58
440.51
386.29
342.84
254.97
203.42
170.09
174.03
167.85
177.01
188.19
211.20
240.91
230.26
251.25
241.66

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=67122&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=67122&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67122&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
10.2581512.63260.004882
2-0.027197-0.27740.391029
30.0598220.61010.271576
40.0958990.9780.165177
50.0408430.41650.338944
6-0.10394-1.060.145803
7-0.115763-1.18060.120237
8-0.15572-1.5880.057656
9-0.131882-1.34490.090785
100.081810.83430.203013
110.0124780.12730.449494
12-0.367633-3.74910.000146
13-0.303541-3.09550.001262
14-0.073859-0.75320.22651
150.0554130.56510.286611
16-0.050791-0.5180.302792
170.0380440.3880.349415
180.0129960.13250.447409
190.0524680.53510.296872
200.1844361.88090.031392
210.1054741.07560.142291
220.0859130.87610.191487
23-0.08711-0.88830.188201
24-0.034455-0.35140.363009
250.1729841.76410.040326
260.066810.68130.248588
27-0.008875-0.09050.46403
28-0.02543-0.25930.397945
29-0.123482-1.25930.105376
300.0647950.66080.255107
310.0106260.10840.456958
32-0.069507-0.70880.240007
33-0.085122-0.86810.193676
34-0.136822-1.39530.082946
350.0546720.55750.289176
360.0168190.17150.432073

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.258151 & 2.6326 & 0.004882 \tabularnewline
2 & -0.027197 & -0.2774 & 0.391029 \tabularnewline
3 & 0.059822 & 0.6101 & 0.271576 \tabularnewline
4 & 0.095899 & 0.978 & 0.165177 \tabularnewline
5 & 0.040843 & 0.4165 & 0.338944 \tabularnewline
6 & -0.10394 & -1.06 & 0.145803 \tabularnewline
7 & -0.115763 & -1.1806 & 0.120237 \tabularnewline
8 & -0.15572 & -1.588 & 0.057656 \tabularnewline
9 & -0.131882 & -1.3449 & 0.090785 \tabularnewline
10 & 0.08181 & 0.8343 & 0.203013 \tabularnewline
11 & 0.012478 & 0.1273 & 0.449494 \tabularnewline
12 & -0.367633 & -3.7491 & 0.000146 \tabularnewline
13 & -0.303541 & -3.0955 & 0.001262 \tabularnewline
14 & -0.073859 & -0.7532 & 0.22651 \tabularnewline
15 & 0.055413 & 0.5651 & 0.286611 \tabularnewline
16 & -0.050791 & -0.518 & 0.302792 \tabularnewline
17 & 0.038044 & 0.388 & 0.349415 \tabularnewline
18 & 0.012996 & 0.1325 & 0.447409 \tabularnewline
19 & 0.052468 & 0.5351 & 0.296872 \tabularnewline
20 & 0.184436 & 1.8809 & 0.031392 \tabularnewline
21 & 0.105474 & 1.0756 & 0.142291 \tabularnewline
22 & 0.085913 & 0.8761 & 0.191487 \tabularnewline
23 & -0.08711 & -0.8883 & 0.188201 \tabularnewline
24 & -0.034455 & -0.3514 & 0.363009 \tabularnewline
25 & 0.172984 & 1.7641 & 0.040326 \tabularnewline
26 & 0.06681 & 0.6813 & 0.248588 \tabularnewline
27 & -0.008875 & -0.0905 & 0.46403 \tabularnewline
28 & -0.02543 & -0.2593 & 0.397945 \tabularnewline
29 & -0.123482 & -1.2593 & 0.105376 \tabularnewline
30 & 0.064795 & 0.6608 & 0.255107 \tabularnewline
31 & 0.010626 & 0.1084 & 0.456958 \tabularnewline
32 & -0.069507 & -0.7088 & 0.240007 \tabularnewline
33 & -0.085122 & -0.8681 & 0.193676 \tabularnewline
34 & -0.136822 & -1.3953 & 0.082946 \tabularnewline
35 & 0.054672 & 0.5575 & 0.289176 \tabularnewline
36 & 0.016819 & 0.1715 & 0.432073 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67122&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]0.258151[/C][C]2.6326[/C][C]0.004882[/C][/ROW]
[ROW][C]2[/C][C]-0.027197[/C][C]-0.2774[/C][C]0.391029[/C][/ROW]
[ROW][C]3[/C][C]0.059822[/C][C]0.6101[/C][C]0.271576[/C][/ROW]
[ROW][C]4[/C][C]0.095899[/C][C]0.978[/C][C]0.165177[/C][/ROW]
[ROW][C]5[/C][C]0.040843[/C][C]0.4165[/C][C]0.338944[/C][/ROW]
[ROW][C]6[/C][C]-0.10394[/C][C]-1.06[/C][C]0.145803[/C][/ROW]
[ROW][C]7[/C][C]-0.115763[/C][C]-1.1806[/C][C]0.120237[/C][/ROW]
[ROW][C]8[/C][C]-0.15572[/C][C]-1.588[/C][C]0.057656[/C][/ROW]
[ROW][C]9[/C][C]-0.131882[/C][C]-1.3449[/C][C]0.090785[/C][/ROW]
[ROW][C]10[/C][C]0.08181[/C][C]0.8343[/C][C]0.203013[/C][/ROW]
[ROW][C]11[/C][C]0.012478[/C][C]0.1273[/C][C]0.449494[/C][/ROW]
[ROW][C]12[/C][C]-0.367633[/C][C]-3.7491[/C][C]0.000146[/C][/ROW]
[ROW][C]13[/C][C]-0.303541[/C][C]-3.0955[/C][C]0.001262[/C][/ROW]
[ROW][C]14[/C][C]-0.073859[/C][C]-0.7532[/C][C]0.22651[/C][/ROW]
[ROW][C]15[/C][C]0.055413[/C][C]0.5651[/C][C]0.286611[/C][/ROW]
[ROW][C]16[/C][C]-0.050791[/C][C]-0.518[/C][C]0.302792[/C][/ROW]
[ROW][C]17[/C][C]0.038044[/C][C]0.388[/C][C]0.349415[/C][/ROW]
[ROW][C]18[/C][C]0.012996[/C][C]0.1325[/C][C]0.447409[/C][/ROW]
[ROW][C]19[/C][C]0.052468[/C][C]0.5351[/C][C]0.296872[/C][/ROW]
[ROW][C]20[/C][C]0.184436[/C][C]1.8809[/C][C]0.031392[/C][/ROW]
[ROW][C]21[/C][C]0.105474[/C][C]1.0756[/C][C]0.142291[/C][/ROW]
[ROW][C]22[/C][C]0.085913[/C][C]0.8761[/C][C]0.191487[/C][/ROW]
[ROW][C]23[/C][C]-0.08711[/C][C]-0.8883[/C][C]0.188201[/C][/ROW]
[ROW][C]24[/C][C]-0.034455[/C][C]-0.3514[/C][C]0.363009[/C][/ROW]
[ROW][C]25[/C][C]0.172984[/C][C]1.7641[/C][C]0.040326[/C][/ROW]
[ROW][C]26[/C][C]0.06681[/C][C]0.6813[/C][C]0.248588[/C][/ROW]
[ROW][C]27[/C][C]-0.008875[/C][C]-0.0905[/C][C]0.46403[/C][/ROW]
[ROW][C]28[/C][C]-0.02543[/C][C]-0.2593[/C][C]0.397945[/C][/ROW]
[ROW][C]29[/C][C]-0.123482[/C][C]-1.2593[/C][C]0.105376[/C][/ROW]
[ROW][C]30[/C][C]0.064795[/C][C]0.6608[/C][C]0.255107[/C][/ROW]
[ROW][C]31[/C][C]0.010626[/C][C]0.1084[/C][C]0.456958[/C][/ROW]
[ROW][C]32[/C][C]-0.069507[/C][C]-0.7088[/C][C]0.240007[/C][/ROW]
[ROW][C]33[/C][C]-0.085122[/C][C]-0.8681[/C][C]0.193676[/C][/ROW]
[ROW][C]34[/C][C]-0.136822[/C][C]-1.3953[/C][C]0.082946[/C][/ROW]
[ROW][C]35[/C][C]0.054672[/C][C]0.5575[/C][C]0.289176[/C][/ROW]
[ROW][C]36[/C][C]0.016819[/C][C]0.1715[/C][C]0.432073[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67122&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67122&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
10.2581512.63260.004882
2-0.027197-0.27740.391029
30.0598220.61010.271576
40.0958990.9780.165177
50.0408430.41650.338944
6-0.10394-1.060.145803
7-0.115763-1.18060.120237
8-0.15572-1.5880.057656
9-0.131882-1.34490.090785
100.081810.83430.203013
110.0124780.12730.449494
12-0.367633-3.74910.000146
13-0.303541-3.09550.001262
14-0.073859-0.75320.22651
150.0554130.56510.286611
16-0.050791-0.5180.302792
170.0380440.3880.349415
180.0129960.13250.447409
190.0524680.53510.296872
200.1844361.88090.031392
210.1054741.07560.142291
220.0859130.87610.191487
23-0.08711-0.88830.188201
24-0.034455-0.35140.363009
250.1729841.76410.040326
260.066810.68130.248588
27-0.008875-0.09050.46403
28-0.02543-0.25930.397945
29-0.123482-1.25930.105376
300.0647950.66080.255107
310.0106260.10840.456958
32-0.069507-0.70880.240007
33-0.085122-0.86810.193676
34-0.136822-1.39530.082946
350.0546720.55750.289176
360.0168190.17150.432073






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2581512.63260.004882
2-0.100539-1.02530.1538
30.1012021.03210.152219
40.0532040.54260.294292
50.0099280.10120.459774
6-0.120952-1.23350.11009
7-0.066651-0.67970.249098
8-0.146302-1.4920.069364
9-0.064366-0.65640.256507
100.1563331.59430.056953
11-0.026804-0.27330.392563
12-0.371361-3.78720.000128
13-0.16831-1.71640.04453
14-0.066671-0.67990.249035
150.0733420.74790.22809
16-0.010015-0.10210.459423
170.1567461.59850.056483
18-0.119971-1.22350.111959
19-0.027131-0.27670.391286
200.0310170.31630.376198
21-0.076399-0.77910.21884
220.1596641.62830.053248
23-0.055946-0.57050.284771
24-0.126364-1.28870.100187
250.0258460.26360.396313
26-0.04259-0.43430.332471
270.0393780.40160.34441
280.0246020.25090.401195
29-0.094652-0.96530.168326
300.0886810.90440.183944
31-0.035484-0.36190.359092
32-0.013627-0.1390.444871
330.016360.16680.433909
34-0.040783-0.41590.339167
350.0515860.52610.299979
36-0.107068-1.09190.138704

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.258151 & 2.6326 & 0.004882 \tabularnewline
2 & -0.100539 & -1.0253 & 0.1538 \tabularnewline
3 & 0.101202 & 1.0321 & 0.152219 \tabularnewline
4 & 0.053204 & 0.5426 & 0.294292 \tabularnewline
5 & 0.009928 & 0.1012 & 0.459774 \tabularnewline
6 & -0.120952 & -1.2335 & 0.11009 \tabularnewline
7 & -0.066651 & -0.6797 & 0.249098 \tabularnewline
8 & -0.146302 & -1.492 & 0.069364 \tabularnewline
9 & -0.064366 & -0.6564 & 0.256507 \tabularnewline
10 & 0.156333 & 1.5943 & 0.056953 \tabularnewline
11 & -0.026804 & -0.2733 & 0.392563 \tabularnewline
12 & -0.371361 & -3.7872 & 0.000128 \tabularnewline
13 & -0.16831 & -1.7164 & 0.04453 \tabularnewline
14 & -0.066671 & -0.6799 & 0.249035 \tabularnewline
15 & 0.073342 & 0.7479 & 0.22809 \tabularnewline
16 & -0.010015 & -0.1021 & 0.459423 \tabularnewline
17 & 0.156746 & 1.5985 & 0.056483 \tabularnewline
18 & -0.119971 & -1.2235 & 0.111959 \tabularnewline
19 & -0.027131 & -0.2767 & 0.391286 \tabularnewline
20 & 0.031017 & 0.3163 & 0.376198 \tabularnewline
21 & -0.076399 & -0.7791 & 0.21884 \tabularnewline
22 & 0.159664 & 1.6283 & 0.053248 \tabularnewline
23 & -0.055946 & -0.5705 & 0.284771 \tabularnewline
24 & -0.126364 & -1.2887 & 0.100187 \tabularnewline
25 & 0.025846 & 0.2636 & 0.396313 \tabularnewline
26 & -0.04259 & -0.4343 & 0.332471 \tabularnewline
27 & 0.039378 & 0.4016 & 0.34441 \tabularnewline
28 & 0.024602 & 0.2509 & 0.401195 \tabularnewline
29 & -0.094652 & -0.9653 & 0.168326 \tabularnewline
30 & 0.088681 & 0.9044 & 0.183944 \tabularnewline
31 & -0.035484 & -0.3619 & 0.359092 \tabularnewline
32 & -0.013627 & -0.139 & 0.444871 \tabularnewline
33 & 0.01636 & 0.1668 & 0.433909 \tabularnewline
34 & -0.040783 & -0.4159 & 0.339167 \tabularnewline
35 & 0.051586 & 0.5261 & 0.299979 \tabularnewline
36 & -0.107068 & -1.0919 & 0.138704 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67122&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]0.258151[/C][C]2.6326[/C][C]0.004882[/C][/ROW]
[ROW][C]2[/C][C]-0.100539[/C][C]-1.0253[/C][C]0.1538[/C][/ROW]
[ROW][C]3[/C][C]0.101202[/C][C]1.0321[/C][C]0.152219[/C][/ROW]
[ROW][C]4[/C][C]0.053204[/C][C]0.5426[/C][C]0.294292[/C][/ROW]
[ROW][C]5[/C][C]0.009928[/C][C]0.1012[/C][C]0.459774[/C][/ROW]
[ROW][C]6[/C][C]-0.120952[/C][C]-1.2335[/C][C]0.11009[/C][/ROW]
[ROW][C]7[/C][C]-0.066651[/C][C]-0.6797[/C][C]0.249098[/C][/ROW]
[ROW][C]8[/C][C]-0.146302[/C][C]-1.492[/C][C]0.069364[/C][/ROW]
[ROW][C]9[/C][C]-0.064366[/C][C]-0.6564[/C][C]0.256507[/C][/ROW]
[ROW][C]10[/C][C]0.156333[/C][C]1.5943[/C][C]0.056953[/C][/ROW]
[ROW][C]11[/C][C]-0.026804[/C][C]-0.2733[/C][C]0.392563[/C][/ROW]
[ROW][C]12[/C][C]-0.371361[/C][C]-3.7872[/C][C]0.000128[/C][/ROW]
[ROW][C]13[/C][C]-0.16831[/C][C]-1.7164[/C][C]0.04453[/C][/ROW]
[ROW][C]14[/C][C]-0.066671[/C][C]-0.6799[/C][C]0.249035[/C][/ROW]
[ROW][C]15[/C][C]0.073342[/C][C]0.7479[/C][C]0.22809[/C][/ROW]
[ROW][C]16[/C][C]-0.010015[/C][C]-0.1021[/C][C]0.459423[/C][/ROW]
[ROW][C]17[/C][C]0.156746[/C][C]1.5985[/C][C]0.056483[/C][/ROW]
[ROW][C]18[/C][C]-0.119971[/C][C]-1.2235[/C][C]0.111959[/C][/ROW]
[ROW][C]19[/C][C]-0.027131[/C][C]-0.2767[/C][C]0.391286[/C][/ROW]
[ROW][C]20[/C][C]0.031017[/C][C]0.3163[/C][C]0.376198[/C][/ROW]
[ROW][C]21[/C][C]-0.076399[/C][C]-0.7791[/C][C]0.21884[/C][/ROW]
[ROW][C]22[/C][C]0.159664[/C][C]1.6283[/C][C]0.053248[/C][/ROW]
[ROW][C]23[/C][C]-0.055946[/C][C]-0.5705[/C][C]0.284771[/C][/ROW]
[ROW][C]24[/C][C]-0.126364[/C][C]-1.2887[/C][C]0.100187[/C][/ROW]
[ROW][C]25[/C][C]0.025846[/C][C]0.2636[/C][C]0.396313[/C][/ROW]
[ROW][C]26[/C][C]-0.04259[/C][C]-0.4343[/C][C]0.332471[/C][/ROW]
[ROW][C]27[/C][C]0.039378[/C][C]0.4016[/C][C]0.34441[/C][/ROW]
[ROW][C]28[/C][C]0.024602[/C][C]0.2509[/C][C]0.401195[/C][/ROW]
[ROW][C]29[/C][C]-0.094652[/C][C]-0.9653[/C][C]0.168326[/C][/ROW]
[ROW][C]30[/C][C]0.088681[/C][C]0.9044[/C][C]0.183944[/C][/ROW]
[ROW][C]31[/C][C]-0.035484[/C][C]-0.3619[/C][C]0.359092[/C][/ROW]
[ROW][C]32[/C][C]-0.013627[/C][C]-0.139[/C][C]0.444871[/C][/ROW]
[ROW][C]33[/C][C]0.01636[/C][C]0.1668[/C][C]0.433909[/C][/ROW]
[ROW][C]34[/C][C]-0.040783[/C][C]-0.4159[/C][C]0.339167[/C][/ROW]
[ROW][C]35[/C][C]0.051586[/C][C]0.5261[/C][C]0.299979[/C][/ROW]
[ROW][C]36[/C][C]-0.107068[/C][C]-1.0919[/C][C]0.138704[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67122&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67122&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
10.2581512.63260.004882
2-0.100539-1.02530.1538
30.1012021.03210.152219
40.0532040.54260.294292
50.0099280.10120.459774
6-0.120952-1.23350.11009
7-0.066651-0.67970.249098
8-0.146302-1.4920.069364
9-0.064366-0.65640.256507
100.1563331.59430.056953
11-0.026804-0.27330.392563
12-0.371361-3.78720.000128
13-0.16831-1.71640.04453
14-0.066671-0.67990.249035
150.0733420.74790.22809
16-0.010015-0.10210.459423
170.1567461.59850.056483
18-0.119971-1.22350.111959
19-0.027131-0.27670.391286
200.0310170.31630.376198
21-0.076399-0.77910.21884
220.1596641.62830.053248
23-0.055946-0.57050.284771
24-0.126364-1.28870.100187
250.0258460.26360.396313
26-0.04259-0.43430.332471
270.0393780.40160.34441
280.0246020.25090.401195
29-0.094652-0.96530.168326
300.0886810.90440.183944
31-0.035484-0.36190.359092
32-0.013627-0.1390.444871
330.016360.16680.433909
34-0.040783-0.41590.339167
350.0515860.52610.299979
36-0.107068-1.09190.138704


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.7 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.7 ; par3 = 1 ; 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')