FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 08 Dec 2008 13:25:32 -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/08/t1228767983nqmc83uvfh7o39q.htm/, Retrieved Thu, 16 May 2024 03:35:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30958, Retrieved Thu, 16 May 2024 03:35:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [Aanvulling Q8] [2008-12-08 18:54:28] [b1bd16d1f47bfe13feacf1c27a0abba5]
-    D  [Spectral Analysis] [Aanvulling Q8(2)] [2008-12-08 19:19:21] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   PD    [Spectral Analysis] [Aanvulling Q8 (3)] [2008-12-08 19:22:47] [b1bd16d1f47bfe13feacf1c27a0abba5]
F RMPD      [(Partial) Autocorrelation Function] [eigen reeks stap ...] [2008-12-08 20:06:09] [b1bd16d1f47bfe13feacf1c27a0abba5]
F   PD          [(Partial) Autocorrelation Function] [step 3 ACF] [2008-12-08 20:25:32] [e7b1048c2c3a353441b9143db4404b91] [Current]
Feedback Forum
2008-12-14 16:38:54 [Sofie Mertens] [reply] 
De tijdreeks is stationair wat betreft het niveau.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97.8
107.4
117.5
105.6
97.4
99.5
98.0
104.3
100.6
101.1
103.9
96.9
95.5
108.4
117.0
103.8
100.8
110.6
104.0
112.6
107.3
98.9
109.8
104.9
102.2
123.9
124.9
112.7
121.9
100.6
104.3
120.4
107.5
102.9
125.6
107.5
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111.0
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128.0
129.6
125.8
119.5
115.7
113.6
129.7
112.0
116.8
127.0
112.1
114.2
121.1
131.6
125.0
120.4
117.7
117.5
120.6
127.5
112.3
124.5
115.2
105.4

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30958&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30958&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30958&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0494470.42250.33696
20.0753380.64370.260898
30.2559442.18680.015982
4-0.079086-0.67570.250679
50.0695570.59430.277076
60.2024071.72940.043985
7-0.123561-1.05570.147292
80.0982890.83980.201887
90.2458972.10090.01955
10-0.142219-1.21510.114117
11-0.061772-0.52780.299626
12-0.123248-1.0530.1479
13-0.217966-1.86230.033292
140.0675230.57690.282885
15-0.044216-0.37780.353344
16-0.115137-0.98370.164249
170.1748721.49410.069729
18-0.003031-0.02590.489706
19-0.213824-1.82690.0359
20-0.008931-0.07630.469693
21-0.005941-0.05080.479829
22-0.156868-1.34030.092155
230.1479191.26380.105158
24-0.247278-2.11270.019021
25-0.096518-0.82470.206128
260.0466570.39860.345662
27-0.001879-0.01610.493619
28-0.102246-0.87360.192603
290.0396620.33890.367838
30-0.021062-0.180.428844
310.0707440.60440.273714
320.1427291.21950.113295
33-0.130517-1.11510.134225
340.0590940.50490.307574
350.152311.30130.098617
360.0496510.42420.336327

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.049447 & 0.4225 & 0.33696 \tabularnewline
2 & 0.075338 & 0.6437 & 0.260898 \tabularnewline
3 & 0.255944 & 2.1868 & 0.015982 \tabularnewline
4 & -0.079086 & -0.6757 & 0.250679 \tabularnewline
5 & 0.069557 & 0.5943 & 0.277076 \tabularnewline
6 & 0.202407 & 1.7294 & 0.043985 \tabularnewline
7 & -0.123561 & -1.0557 & 0.147292 \tabularnewline
8 & 0.098289 & 0.8398 & 0.201887 \tabularnewline
9 & 0.245897 & 2.1009 & 0.01955 \tabularnewline
10 & -0.142219 & -1.2151 & 0.114117 \tabularnewline
11 & -0.061772 & -0.5278 & 0.299626 \tabularnewline
12 & -0.123248 & -1.053 & 0.1479 \tabularnewline
13 & -0.217966 & -1.8623 & 0.033292 \tabularnewline
14 & 0.067523 & 0.5769 & 0.282885 \tabularnewline
15 & -0.044216 & -0.3778 & 0.353344 \tabularnewline
16 & -0.115137 & -0.9837 & 0.164249 \tabularnewline
17 & 0.174872 & 1.4941 & 0.069729 \tabularnewline
18 & -0.003031 & -0.0259 & 0.489706 \tabularnewline
19 & -0.213824 & -1.8269 & 0.0359 \tabularnewline
20 & -0.008931 & -0.0763 & 0.469693 \tabularnewline
21 & -0.005941 & -0.0508 & 0.479829 \tabularnewline
22 & -0.156868 & -1.3403 & 0.092155 \tabularnewline
23 & 0.147919 & 1.2638 & 0.105158 \tabularnewline
24 & -0.247278 & -2.1127 & 0.019021 \tabularnewline
25 & -0.096518 & -0.8247 & 0.206128 \tabularnewline
26 & 0.046657 & 0.3986 & 0.345662 \tabularnewline
27 & -0.001879 & -0.0161 & 0.493619 \tabularnewline
28 & -0.102246 & -0.8736 & 0.192603 \tabularnewline
29 & 0.039662 & 0.3389 & 0.367838 \tabularnewline
30 & -0.021062 & -0.18 & 0.428844 \tabularnewline
31 & 0.070744 & 0.6044 & 0.273714 \tabularnewline
32 & 0.142729 & 1.2195 & 0.113295 \tabularnewline
33 & -0.130517 & -1.1151 & 0.134225 \tabularnewline
34 & 0.059094 & 0.5049 & 0.307574 \tabularnewline
35 & 0.15231 & 1.3013 & 0.098617 \tabularnewline
36 & 0.049651 & 0.4242 & 0.336327 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30958&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]0.049447[/C][C]0.4225[/C][C]0.33696[/C][/ROW]
[ROW][C]2[/C][C]0.075338[/C][C]0.6437[/C][C]0.260898[/C][/ROW]
[ROW][C]3[/C][C]0.255944[/C][C]2.1868[/C][C]0.015982[/C][/ROW]
[ROW][C]4[/C][C]-0.079086[/C][C]-0.6757[/C][C]0.250679[/C][/ROW]
[ROW][C]5[/C][C]0.069557[/C][C]0.5943[/C][C]0.277076[/C][/ROW]
[ROW][C]6[/C][C]0.202407[/C][C]1.7294[/C][C]0.043985[/C][/ROW]
[ROW][C]7[/C][C]-0.123561[/C][C]-1.0557[/C][C]0.147292[/C][/ROW]
[ROW][C]8[/C][C]0.098289[/C][C]0.8398[/C][C]0.201887[/C][/ROW]
[ROW][C]9[/C][C]0.245897[/C][C]2.1009[/C][C]0.01955[/C][/ROW]
[ROW][C]10[/C][C]-0.142219[/C][C]-1.2151[/C][C]0.114117[/C][/ROW]
[ROW][C]11[/C][C]-0.061772[/C][C]-0.5278[/C][C]0.299626[/C][/ROW]
[ROW][C]12[/C][C]-0.123248[/C][C]-1.053[/C][C]0.1479[/C][/ROW]
[ROW][C]13[/C][C]-0.217966[/C][C]-1.8623[/C][C]0.033292[/C][/ROW]
[ROW][C]14[/C][C]0.067523[/C][C]0.5769[/C][C]0.282885[/C][/ROW]
[ROW][C]15[/C][C]-0.044216[/C][C]-0.3778[/C][C]0.353344[/C][/ROW]
[ROW][C]16[/C][C]-0.115137[/C][C]-0.9837[/C][C]0.164249[/C][/ROW]
[ROW][C]17[/C][C]0.174872[/C][C]1.4941[/C][C]0.069729[/C][/ROW]
[ROW][C]18[/C][C]-0.003031[/C][C]-0.0259[/C][C]0.489706[/C][/ROW]
[ROW][C]19[/C][C]-0.213824[/C][C]-1.8269[/C][C]0.0359[/C][/ROW]
[ROW][C]20[/C][C]-0.008931[/C][C]-0.0763[/C][C]0.469693[/C][/ROW]
[ROW][C]21[/C][C]-0.005941[/C][C]-0.0508[/C][C]0.479829[/C][/ROW]
[ROW][C]22[/C][C]-0.156868[/C][C]-1.3403[/C][C]0.092155[/C][/ROW]
[ROW][C]23[/C][C]0.147919[/C][C]1.2638[/C][C]0.105158[/C][/ROW]
[ROW][C]24[/C][C]-0.247278[/C][C]-2.1127[/C][C]0.019021[/C][/ROW]
[ROW][C]25[/C][C]-0.096518[/C][C]-0.8247[/C][C]0.206128[/C][/ROW]
[ROW][C]26[/C][C]0.046657[/C][C]0.3986[/C][C]0.345662[/C][/ROW]
[ROW][C]27[/C][C]-0.001879[/C][C]-0.0161[/C][C]0.493619[/C][/ROW]
[ROW][C]28[/C][C]-0.102246[/C][C]-0.8736[/C][C]0.192603[/C][/ROW]
[ROW][C]29[/C][C]0.039662[/C][C]0.3389[/C][C]0.367838[/C][/ROW]
[ROW][C]30[/C][C]-0.021062[/C][C]-0.18[/C][C]0.428844[/C][/ROW]
[ROW][C]31[/C][C]0.070744[/C][C]0.6044[/C][C]0.273714[/C][/ROW]
[ROW][C]32[/C][C]0.142729[/C][C]1.2195[/C][C]0.113295[/C][/ROW]
[ROW][C]33[/C][C]-0.130517[/C][C]-1.1151[/C][C]0.134225[/C][/ROW]
[ROW][C]34[/C][C]0.059094[/C][C]0.5049[/C][C]0.307574[/C][/ROW]
[ROW][C]35[/C][C]0.15231[/C][C]1.3013[/C][C]0.098617[/C][/ROW]
[ROW][C]36[/C][C]0.049651[/C][C]0.4242[/C][C]0.336327[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30958&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30958&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
10.0494470.42250.33696
20.0753380.64370.260898
30.2559442.18680.015982
4-0.079086-0.67570.250679
50.0695570.59430.277076
60.2024071.72940.043985
7-0.123561-1.05570.147292
80.0982890.83980.201887
90.2458972.10090.01955
10-0.142219-1.21510.114117
11-0.061772-0.52780.299626
12-0.123248-1.0530.1479
13-0.217966-1.86230.033292
140.0675230.57690.282885
15-0.044216-0.37780.353344
16-0.115137-0.98370.164249
170.1748721.49410.069729
18-0.003031-0.02590.489706
19-0.213824-1.82690.0359
20-0.008931-0.07630.469693
21-0.005941-0.05080.479829
22-0.156868-1.34030.092155
230.1479191.26380.105158
24-0.247278-2.11270.019021
25-0.096518-0.82470.206128
260.0466570.39860.345662
27-0.001879-0.01610.493619
28-0.102246-0.87360.192603
290.0396620.33890.367838
30-0.021062-0.180.428844
310.0707440.60440.273714
320.1427291.21950.113295
33-0.130517-1.11510.134225
340.0590940.50490.307574
350.152311.30130.098617
360.0496510.42420.336327






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0494470.42250.33696
20.0730720.62430.267181
30.2508272.14310.017721
4-0.110957-0.9480.173125
50.0465880.39810.345877
60.1579721.34970.09064
7-0.114228-0.9760.166153
80.0581640.4970.310357
90.2068681.76750.040664
10-0.120288-1.02770.153732
11-0.18138-1.54970.062768
12-0.210512-1.79860.038107
13-0.080539-0.68810.246777
140.0934760.79870.21354
15-0.016977-0.14510.442534
160.006810.05820.476881
170.1751751.49670.069392
180.0307250.26250.396831
19-0.225262-1.92460.029086
20-0.072064-0.61570.269998
210.2359372.01580.023749
22-0.106049-0.90610.183937
23-0.074847-0.63950.262253
24-0.336588-2.87580.002639
250.0120410.10290.45917
26-0.069125-0.59060.278305
270.2091171.78670.039069
280.0736430.62920.26559
290.1489891.2730.103535
300.0007670.00660.497394
31-0.020706-0.17690.430034
320.0532520.4550.325234
330.0145940.12470.450554
340.0283370.24210.404686
350.011950.10210.459478
36-0.008424-0.0720.471411

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.049447 & 0.4225 & 0.33696 \tabularnewline
2 & 0.073072 & 0.6243 & 0.267181 \tabularnewline
3 & 0.250827 & 2.1431 & 0.017721 \tabularnewline
4 & -0.110957 & -0.948 & 0.173125 \tabularnewline
5 & 0.046588 & 0.3981 & 0.345877 \tabularnewline
6 & 0.157972 & 1.3497 & 0.09064 \tabularnewline
7 & -0.114228 & -0.976 & 0.166153 \tabularnewline
8 & 0.058164 & 0.497 & 0.310357 \tabularnewline
9 & 0.206868 & 1.7675 & 0.040664 \tabularnewline
10 & -0.120288 & -1.0277 & 0.153732 \tabularnewline
11 & -0.18138 & -1.5497 & 0.062768 \tabularnewline
12 & -0.210512 & -1.7986 & 0.038107 \tabularnewline
13 & -0.080539 & -0.6881 & 0.246777 \tabularnewline
14 & 0.093476 & 0.7987 & 0.21354 \tabularnewline
15 & -0.016977 & -0.1451 & 0.442534 \tabularnewline
16 & 0.00681 & 0.0582 & 0.476881 \tabularnewline
17 & 0.175175 & 1.4967 & 0.069392 \tabularnewline
18 & 0.030725 & 0.2625 & 0.396831 \tabularnewline
19 & -0.225262 & -1.9246 & 0.029086 \tabularnewline
20 & -0.072064 & -0.6157 & 0.269998 \tabularnewline
21 & 0.235937 & 2.0158 & 0.023749 \tabularnewline
22 & -0.106049 & -0.9061 & 0.183937 \tabularnewline
23 & -0.074847 & -0.6395 & 0.262253 \tabularnewline
24 & -0.336588 & -2.8758 & 0.002639 \tabularnewline
25 & 0.012041 & 0.1029 & 0.45917 \tabularnewline
26 & -0.069125 & -0.5906 & 0.278305 \tabularnewline
27 & 0.209117 & 1.7867 & 0.039069 \tabularnewline
28 & 0.073643 & 0.6292 & 0.26559 \tabularnewline
29 & 0.148989 & 1.273 & 0.103535 \tabularnewline
30 & 0.000767 & 0.0066 & 0.497394 \tabularnewline
31 & -0.020706 & -0.1769 & 0.430034 \tabularnewline
32 & 0.053252 & 0.455 & 0.325234 \tabularnewline
33 & 0.014594 & 0.1247 & 0.450554 \tabularnewline
34 & 0.028337 & 0.2421 & 0.404686 \tabularnewline
35 & 0.01195 & 0.1021 & 0.459478 \tabularnewline
36 & -0.008424 & -0.072 & 0.471411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30958&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]0.049447[/C][C]0.4225[/C][C]0.33696[/C][/ROW]
[ROW][C]2[/C][C]0.073072[/C][C]0.6243[/C][C]0.267181[/C][/ROW]
[ROW][C]3[/C][C]0.250827[/C][C]2.1431[/C][C]0.017721[/C][/ROW]
[ROW][C]4[/C][C]-0.110957[/C][C]-0.948[/C][C]0.173125[/C][/ROW]
[ROW][C]5[/C][C]0.046588[/C][C]0.3981[/C][C]0.345877[/C][/ROW]
[ROW][C]6[/C][C]0.157972[/C][C]1.3497[/C][C]0.09064[/C][/ROW]
[ROW][C]7[/C][C]-0.114228[/C][C]-0.976[/C][C]0.166153[/C][/ROW]
[ROW][C]8[/C][C]0.058164[/C][C]0.497[/C][C]0.310357[/C][/ROW]
[ROW][C]9[/C][C]0.206868[/C][C]1.7675[/C][C]0.040664[/C][/ROW]
[ROW][C]10[/C][C]-0.120288[/C][C]-1.0277[/C][C]0.153732[/C][/ROW]
[ROW][C]11[/C][C]-0.18138[/C][C]-1.5497[/C][C]0.062768[/C][/ROW]
[ROW][C]12[/C][C]-0.210512[/C][C]-1.7986[/C][C]0.038107[/C][/ROW]
[ROW][C]13[/C][C]-0.080539[/C][C]-0.6881[/C][C]0.246777[/C][/ROW]
[ROW][C]14[/C][C]0.093476[/C][C]0.7987[/C][C]0.21354[/C][/ROW]
[ROW][C]15[/C][C]-0.016977[/C][C]-0.1451[/C][C]0.442534[/C][/ROW]
[ROW][C]16[/C][C]0.00681[/C][C]0.0582[/C][C]0.476881[/C][/ROW]
[ROW][C]17[/C][C]0.175175[/C][C]1.4967[/C][C]0.069392[/C][/ROW]
[ROW][C]18[/C][C]0.030725[/C][C]0.2625[/C][C]0.396831[/C][/ROW]
[ROW][C]19[/C][C]-0.225262[/C][C]-1.9246[/C][C]0.029086[/C][/ROW]
[ROW][C]20[/C][C]-0.072064[/C][C]-0.6157[/C][C]0.269998[/C][/ROW]
[ROW][C]21[/C][C]0.235937[/C][C]2.0158[/C][C]0.023749[/C][/ROW]
[ROW][C]22[/C][C]-0.106049[/C][C]-0.9061[/C][C]0.183937[/C][/ROW]
[ROW][C]23[/C][C]-0.074847[/C][C]-0.6395[/C][C]0.262253[/C][/ROW]
[ROW][C]24[/C][C]-0.336588[/C][C]-2.8758[/C][C]0.002639[/C][/ROW]
[ROW][C]25[/C][C]0.012041[/C][C]0.1029[/C][C]0.45917[/C][/ROW]
[ROW][C]26[/C][C]-0.069125[/C][C]-0.5906[/C][C]0.278305[/C][/ROW]
[ROW][C]27[/C][C]0.209117[/C][C]1.7867[/C][C]0.039069[/C][/ROW]
[ROW][C]28[/C][C]0.073643[/C][C]0.6292[/C][C]0.26559[/C][/ROW]
[ROW][C]29[/C][C]0.148989[/C][C]1.273[/C][C]0.103535[/C][/ROW]
[ROW][C]30[/C][C]0.000767[/C][C]0.0066[/C][C]0.497394[/C][/ROW]
[ROW][C]31[/C][C]-0.020706[/C][C]-0.1769[/C][C]0.430034[/C][/ROW]
[ROW][C]32[/C][C]0.053252[/C][C]0.455[/C][C]0.325234[/C][/ROW]
[ROW][C]33[/C][C]0.014594[/C][C]0.1247[/C][C]0.450554[/C][/ROW]
[ROW][C]34[/C][C]0.028337[/C][C]0.2421[/C][C]0.404686[/C][/ROW]
[ROW][C]35[/C][C]0.01195[/C][C]0.1021[/C][C]0.459478[/C][/ROW]
[ROW][C]36[/C][C]-0.008424[/C][C]-0.072[/C][C]0.471411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30958&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30958&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
10.0494470.42250.33696
20.0730720.62430.267181
30.2508272.14310.017721
4-0.110957-0.9480.173125
50.0465880.39810.345877
60.1579721.34970.09064
7-0.114228-0.9760.166153
80.0581640.4970.310357
90.2068681.76750.040664
10-0.120288-1.02770.153732
11-0.18138-1.54970.062768
12-0.210512-1.79860.038107
13-0.080539-0.68810.246777
140.0934760.79870.21354
15-0.016977-0.14510.442534
160.006810.05820.476881
170.1751751.49670.069392
180.0307250.26250.396831
19-0.225262-1.92460.029086
20-0.072064-0.61570.269998
210.2359372.01580.023749
22-0.106049-0.90610.183937
23-0.074847-0.63950.262253
24-0.336588-2.87580.002639
250.0120410.10290.45917
26-0.069125-0.59060.278305
270.2091171.78670.039069
280.0736430.62920.26559
290.1489891.2730.103535
300.0007670.00660.497394
31-0.020706-0.17690.430034
320.0532520.4550.325234
330.0145940.12470.450554
340.0283370.24210.404686
350.011950.10210.459478
36-0.008424-0.0720.471411


Figures (Output of Computation)

Input Parameters & R Code

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