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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 computationWed, 02 Dec 2009 13:15:15 -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/2009/Dec/02/t125978497497qxne8njx2j60c.htm/, Retrieved Sat, 27 Apr 2024 14:11:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62568, Retrieved Sat, 27 Apr 2024 14:11:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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  D        [(Partial) Autocorrelation Function] [ACF Link 2] [2009-11-25 18:57:31] [1f74ef2f756548f1f3a7b6136ea56d7f]
-    D          [(Partial) Autocorrelation Function] [ACF d=1 D=0] [2009-12-02 19:11:03] [1f74ef2f756548f1f3a7b6136ea56d7f]
-                   [(Partial) Autocorrelation Function] [ACF d=1 D=1] [2009-12-02 20:15:15] [026d431dc78a3ce53a040b5408fc0322] [Current]
-   PD                [(Partial) Autocorrelation Function] [WS 9 ACF : d=2, D...] [2009-12-04 14:11:55] [af8eb90b4bf1bcfcc4325c143dbee260]
-   PD                  [(Partial) Autocorrelation Function] [WS 9 D=1, d=1] [2009-12-09 16:35:12] [aba88da643e3763d32ff92bd8f92a385]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
111.5
108.1
124.5
106.3
111.1
121.3
116.5
117.4
123.6
98.4
107.2
118.9
111.9
115.2
124.4
104.6
117
126.2
117.5
122.2
124.1
105.8
107.5
125.6
112.1
120.1
130.6
109.8
122.1
129.5
132.1
133.3
128.4
114.7
114.1
136.9
123.4
134
137
127.8
140.1
140.4
157.8
151.8
141.1
138.8
141.1
139.5
150.7
144.4
146
143.6
143.1
156.4
164.8
145.1
153.4
133.2
131.4
145.9

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=62568&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=62568&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62568&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
1-0.583049-3.99720.000112
2-0.07444-0.51030.306103
30.4525913.10280.00162
4-0.391826-2.68620.004978
50.1206220.82690.206224
60.1407570.9650.169747
7-0.260024-1.78260.040553
80.2090361.43310.079227
9-0.036082-0.24740.402851
10-0.157507-1.07980.142868
110.2258491.54830.064124
12-0.126057-0.86420.195933
13-0.10909-0.74790.229129
140.2059451.41190.082285
15-0.111924-0.76730.223368
16-0.045097-0.30920.37928
170.0733880.50310.308613
18-0.014181-0.09720.461483
19-0.049954-0.34250.366763
200.0653970.44830.327984
21-0.011725-0.08040.468136
22-0.09987-0.68470.248457
230.1691781.15980.125989
24-0.123819-0.84890.20013
250.0204290.14010.444608
260.0508880.34890.364372
27-0.017105-0.11730.453574
28-0.089471-0.61340.271291
290.0884070.60610.273686
300.0222370.15250.439741
31-0.086474-0.59280.278066
320.0501960.34410.366142
330.0392060.26880.394636
34-0.097579-0.6690.253395
350.1024980.70270.242858
36-0.070359-0.48240.315896

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.583049 & -3.9972 & 0.000112 \tabularnewline
2 & -0.07444 & -0.5103 & 0.306103 \tabularnewline
3 & 0.452591 & 3.1028 & 0.00162 \tabularnewline
4 & -0.391826 & -2.6862 & 0.004978 \tabularnewline
5 & 0.120622 & 0.8269 & 0.206224 \tabularnewline
6 & 0.140757 & 0.965 & 0.169747 \tabularnewline
7 & -0.260024 & -1.7826 & 0.040553 \tabularnewline
8 & 0.209036 & 1.4331 & 0.079227 \tabularnewline
9 & -0.036082 & -0.2474 & 0.402851 \tabularnewline
10 & -0.157507 & -1.0798 & 0.142868 \tabularnewline
11 & 0.225849 & 1.5483 & 0.064124 \tabularnewline
12 & -0.126057 & -0.8642 & 0.195933 \tabularnewline
13 & -0.10909 & -0.7479 & 0.229129 \tabularnewline
14 & 0.205945 & 1.4119 & 0.082285 \tabularnewline
15 & -0.111924 & -0.7673 & 0.223368 \tabularnewline
16 & -0.045097 & -0.3092 & 0.37928 \tabularnewline
17 & 0.073388 & 0.5031 & 0.308613 \tabularnewline
18 & -0.014181 & -0.0972 & 0.461483 \tabularnewline
19 & -0.049954 & -0.3425 & 0.366763 \tabularnewline
20 & 0.065397 & 0.4483 & 0.327984 \tabularnewline
21 & -0.011725 & -0.0804 & 0.468136 \tabularnewline
22 & -0.09987 & -0.6847 & 0.248457 \tabularnewline
23 & 0.169178 & 1.1598 & 0.125989 \tabularnewline
24 & -0.123819 & -0.8489 & 0.20013 \tabularnewline
25 & 0.020429 & 0.1401 & 0.444608 \tabularnewline
26 & 0.050888 & 0.3489 & 0.364372 \tabularnewline
27 & -0.017105 & -0.1173 & 0.453574 \tabularnewline
28 & -0.089471 & -0.6134 & 0.271291 \tabularnewline
29 & 0.088407 & 0.6061 & 0.273686 \tabularnewline
30 & 0.022237 & 0.1525 & 0.439741 \tabularnewline
31 & -0.086474 & -0.5928 & 0.278066 \tabularnewline
32 & 0.050196 & 0.3441 & 0.366142 \tabularnewline
33 & 0.039206 & 0.2688 & 0.394636 \tabularnewline
34 & -0.097579 & -0.669 & 0.253395 \tabularnewline
35 & 0.102498 & 0.7027 & 0.242858 \tabularnewline
36 & -0.070359 & -0.4824 & 0.315896 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62568&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]-0.583049[/C][C]-3.9972[/C][C]0.000112[/C][/ROW]
[ROW][C]2[/C][C]-0.07444[/C][C]-0.5103[/C][C]0.306103[/C][/ROW]
[ROW][C]3[/C][C]0.452591[/C][C]3.1028[/C][C]0.00162[/C][/ROW]
[ROW][C]4[/C][C]-0.391826[/C][C]-2.6862[/C][C]0.004978[/C][/ROW]
[ROW][C]5[/C][C]0.120622[/C][C]0.8269[/C][C]0.206224[/C][/ROW]
[ROW][C]6[/C][C]0.140757[/C][C]0.965[/C][C]0.169747[/C][/ROW]
[ROW][C]7[/C][C]-0.260024[/C][C]-1.7826[/C][C]0.040553[/C][/ROW]
[ROW][C]8[/C][C]0.209036[/C][C]1.4331[/C][C]0.079227[/C][/ROW]
[ROW][C]9[/C][C]-0.036082[/C][C]-0.2474[/C][C]0.402851[/C][/ROW]
[ROW][C]10[/C][C]-0.157507[/C][C]-1.0798[/C][C]0.142868[/C][/ROW]
[ROW][C]11[/C][C]0.225849[/C][C]1.5483[/C][C]0.064124[/C][/ROW]
[ROW][C]12[/C][C]-0.126057[/C][C]-0.8642[/C][C]0.195933[/C][/ROW]
[ROW][C]13[/C][C]-0.10909[/C][C]-0.7479[/C][C]0.229129[/C][/ROW]
[ROW][C]14[/C][C]0.205945[/C][C]1.4119[/C][C]0.082285[/C][/ROW]
[ROW][C]15[/C][C]-0.111924[/C][C]-0.7673[/C][C]0.223368[/C][/ROW]
[ROW][C]16[/C][C]-0.045097[/C][C]-0.3092[/C][C]0.37928[/C][/ROW]
[ROW][C]17[/C][C]0.073388[/C][C]0.5031[/C][C]0.308613[/C][/ROW]
[ROW][C]18[/C][C]-0.014181[/C][C]-0.0972[/C][C]0.461483[/C][/ROW]
[ROW][C]19[/C][C]-0.049954[/C][C]-0.3425[/C][C]0.366763[/C][/ROW]
[ROW][C]20[/C][C]0.065397[/C][C]0.4483[/C][C]0.327984[/C][/ROW]
[ROW][C]21[/C][C]-0.011725[/C][C]-0.0804[/C][C]0.468136[/C][/ROW]
[ROW][C]22[/C][C]-0.09987[/C][C]-0.6847[/C][C]0.248457[/C][/ROW]
[ROW][C]23[/C][C]0.169178[/C][C]1.1598[/C][C]0.125989[/C][/ROW]
[ROW][C]24[/C][C]-0.123819[/C][C]-0.8489[/C][C]0.20013[/C][/ROW]
[ROW][C]25[/C][C]0.020429[/C][C]0.1401[/C][C]0.444608[/C][/ROW]
[ROW][C]26[/C][C]0.050888[/C][C]0.3489[/C][C]0.364372[/C][/ROW]
[ROW][C]27[/C][C]-0.017105[/C][C]-0.1173[/C][C]0.453574[/C][/ROW]
[ROW][C]28[/C][C]-0.089471[/C][C]-0.6134[/C][C]0.271291[/C][/ROW]
[ROW][C]29[/C][C]0.088407[/C][C]0.6061[/C][C]0.273686[/C][/ROW]
[ROW][C]30[/C][C]0.022237[/C][C]0.1525[/C][C]0.439741[/C][/ROW]
[ROW][C]31[/C][C]-0.086474[/C][C]-0.5928[/C][C]0.278066[/C][/ROW]
[ROW][C]32[/C][C]0.050196[/C][C]0.3441[/C][C]0.366142[/C][/ROW]
[ROW][C]33[/C][C]0.039206[/C][C]0.2688[/C][C]0.394636[/C][/ROW]
[ROW][C]34[/C][C]-0.097579[/C][C]-0.669[/C][C]0.253395[/C][/ROW]
[ROW][C]35[/C][C]0.102498[/C][C]0.7027[/C][C]0.242858[/C][/ROW]
[ROW][C]36[/C][C]-0.070359[/C][C]-0.4824[/C][C]0.315896[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62568&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62568&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
1-0.583049-3.99720.000112
2-0.07444-0.51030.306103
30.4525913.10280.00162
4-0.391826-2.68620.004978
50.1206220.82690.206224
60.1407570.9650.169747
7-0.260024-1.78260.040553
80.2090361.43310.079227
9-0.036082-0.24740.402851
10-0.157507-1.07980.142868
110.2258491.54830.064124
12-0.126057-0.86420.195933
13-0.10909-0.74790.229129
140.2059451.41190.082285
15-0.111924-0.76730.223368
16-0.045097-0.30920.37928
170.0733880.50310.308613
18-0.014181-0.09720.461483
19-0.049954-0.34250.366763
200.0653970.44830.327984
21-0.011725-0.08040.468136
22-0.09987-0.68470.248457
230.1691781.15980.125989
24-0.123819-0.84890.20013
250.0204290.14010.444608
260.0508880.34890.364372
27-0.017105-0.11730.453574
28-0.089471-0.61340.271291
290.0884070.60610.273686
300.0222370.15250.439741
31-0.086474-0.59280.278066
320.0501960.34410.366142
330.0392060.26880.394636
34-0.097579-0.6690.253395
350.1024980.70270.242858
36-0.070359-0.48240.315896






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.583049-3.99720.000112
2-0.627808-4.3044.2e-05
30.0397560.27260.393196
40.0142340.09760.461338
50.0846740.58050.282176
60.0827330.56720.286642
7-0.060847-0.41710.339235
80.0125920.08630.465786
90.0287120.19680.4224
10-0.079823-0.54720.293402
11-0.00802-0.0550.478193
120.0116290.07970.468398
13-0.16111-1.10450.137496
14-0.159863-1.0960.139339
15-0.019063-0.13070.448289
160.0374860.2570.399153
17-0.102872-0.70530.242066
18-0.014404-0.09880.460878
19-0.042504-0.29140.386018
200.0171580.11760.453431
210.0854760.5860.280341
22-0.121545-0.83330.204453
23-0.000889-0.00610.497581
24-0.023175-0.15890.437222
250.0501140.34360.366353
26-0.104265-0.71480.239133
270.107430.73650.232543
28-0.114443-0.78460.218318
29-0.20225-1.38660.086059
30-0.033593-0.23030.409428
310.0960.65810.256829
320.0178310.12220.451615
330.0625080.42850.335111
34-0.067328-0.46160.323256
35-0.006147-0.04210.483282
36-0.020425-0.140.444618

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.583049 & -3.9972 & 0.000112 \tabularnewline
2 & -0.627808 & -4.304 & 4.2e-05 \tabularnewline
3 & 0.039756 & 0.2726 & 0.393196 \tabularnewline
4 & 0.014234 & 0.0976 & 0.461338 \tabularnewline
5 & 0.084674 & 0.5805 & 0.282176 \tabularnewline
6 & 0.082733 & 0.5672 & 0.286642 \tabularnewline
7 & -0.060847 & -0.4171 & 0.339235 \tabularnewline
8 & 0.012592 & 0.0863 & 0.465786 \tabularnewline
9 & 0.028712 & 0.1968 & 0.4224 \tabularnewline
10 & -0.079823 & -0.5472 & 0.293402 \tabularnewline
11 & -0.00802 & -0.055 & 0.478193 \tabularnewline
12 & 0.011629 & 0.0797 & 0.468398 \tabularnewline
13 & -0.16111 & -1.1045 & 0.137496 \tabularnewline
14 & -0.159863 & -1.096 & 0.139339 \tabularnewline
15 & -0.019063 & -0.1307 & 0.448289 \tabularnewline
16 & 0.037486 & 0.257 & 0.399153 \tabularnewline
17 & -0.102872 & -0.7053 & 0.242066 \tabularnewline
18 & -0.014404 & -0.0988 & 0.460878 \tabularnewline
19 & -0.042504 & -0.2914 & 0.386018 \tabularnewline
20 & 0.017158 & 0.1176 & 0.453431 \tabularnewline
21 & 0.085476 & 0.586 & 0.280341 \tabularnewline
22 & -0.121545 & -0.8333 & 0.204453 \tabularnewline
23 & -0.000889 & -0.0061 & 0.497581 \tabularnewline
24 & -0.023175 & -0.1589 & 0.437222 \tabularnewline
25 & 0.050114 & 0.3436 & 0.366353 \tabularnewline
26 & -0.104265 & -0.7148 & 0.239133 \tabularnewline
27 & 0.10743 & 0.7365 & 0.232543 \tabularnewline
28 & -0.114443 & -0.7846 & 0.218318 \tabularnewline
29 & -0.20225 & -1.3866 & 0.086059 \tabularnewline
30 & -0.033593 & -0.2303 & 0.409428 \tabularnewline
31 & 0.096 & 0.6581 & 0.256829 \tabularnewline
32 & 0.017831 & 0.1222 & 0.451615 \tabularnewline
33 & 0.062508 & 0.4285 & 0.335111 \tabularnewline
34 & -0.067328 & -0.4616 & 0.323256 \tabularnewline
35 & -0.006147 & -0.0421 & 0.483282 \tabularnewline
36 & -0.020425 & -0.14 & 0.444618 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62568&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]-0.583049[/C][C]-3.9972[/C][C]0.000112[/C][/ROW]
[ROW][C]2[/C][C]-0.627808[/C][C]-4.304[/C][C]4.2e-05[/C][/ROW]
[ROW][C]3[/C][C]0.039756[/C][C]0.2726[/C][C]0.393196[/C][/ROW]
[ROW][C]4[/C][C]0.014234[/C][C]0.0976[/C][C]0.461338[/C][/ROW]
[ROW][C]5[/C][C]0.084674[/C][C]0.5805[/C][C]0.282176[/C][/ROW]
[ROW][C]6[/C][C]0.082733[/C][C]0.5672[/C][C]0.286642[/C][/ROW]
[ROW][C]7[/C][C]-0.060847[/C][C]-0.4171[/C][C]0.339235[/C][/ROW]
[ROW][C]8[/C][C]0.012592[/C][C]0.0863[/C][C]0.465786[/C][/ROW]
[ROW][C]9[/C][C]0.028712[/C][C]0.1968[/C][C]0.4224[/C][/ROW]
[ROW][C]10[/C][C]-0.079823[/C][C]-0.5472[/C][C]0.293402[/C][/ROW]
[ROW][C]11[/C][C]-0.00802[/C][C]-0.055[/C][C]0.478193[/C][/ROW]
[ROW][C]12[/C][C]0.011629[/C][C]0.0797[/C][C]0.468398[/C][/ROW]
[ROW][C]13[/C][C]-0.16111[/C][C]-1.1045[/C][C]0.137496[/C][/ROW]
[ROW][C]14[/C][C]-0.159863[/C][C]-1.096[/C][C]0.139339[/C][/ROW]
[ROW][C]15[/C][C]-0.019063[/C][C]-0.1307[/C][C]0.448289[/C][/ROW]
[ROW][C]16[/C][C]0.037486[/C][C]0.257[/C][C]0.399153[/C][/ROW]
[ROW][C]17[/C][C]-0.102872[/C][C]-0.7053[/C][C]0.242066[/C][/ROW]
[ROW][C]18[/C][C]-0.014404[/C][C]-0.0988[/C][C]0.460878[/C][/ROW]
[ROW][C]19[/C][C]-0.042504[/C][C]-0.2914[/C][C]0.386018[/C][/ROW]
[ROW][C]20[/C][C]0.017158[/C][C]0.1176[/C][C]0.453431[/C][/ROW]
[ROW][C]21[/C][C]0.085476[/C][C]0.586[/C][C]0.280341[/C][/ROW]
[ROW][C]22[/C][C]-0.121545[/C][C]-0.8333[/C][C]0.204453[/C][/ROW]
[ROW][C]23[/C][C]-0.000889[/C][C]-0.0061[/C][C]0.497581[/C][/ROW]
[ROW][C]24[/C][C]-0.023175[/C][C]-0.1589[/C][C]0.437222[/C][/ROW]
[ROW][C]25[/C][C]0.050114[/C][C]0.3436[/C][C]0.366353[/C][/ROW]
[ROW][C]26[/C][C]-0.104265[/C][C]-0.7148[/C][C]0.239133[/C][/ROW]
[ROW][C]27[/C][C]0.10743[/C][C]0.7365[/C][C]0.232543[/C][/ROW]
[ROW][C]28[/C][C]-0.114443[/C][C]-0.7846[/C][C]0.218318[/C][/ROW]
[ROW][C]29[/C][C]-0.20225[/C][C]-1.3866[/C][C]0.086059[/C][/ROW]
[ROW][C]30[/C][C]-0.033593[/C][C]-0.2303[/C][C]0.409428[/C][/ROW]
[ROW][C]31[/C][C]0.096[/C][C]0.6581[/C][C]0.256829[/C][/ROW]
[ROW][C]32[/C][C]0.017831[/C][C]0.1222[/C][C]0.451615[/C][/ROW]
[ROW][C]33[/C][C]0.062508[/C][C]0.4285[/C][C]0.335111[/C][/ROW]
[ROW][C]34[/C][C]-0.067328[/C][C]-0.4616[/C][C]0.323256[/C][/ROW]
[ROW][C]35[/C][C]-0.006147[/C][C]-0.0421[/C][C]0.483282[/C][/ROW]
[ROW][C]36[/C][C]-0.020425[/C][C]-0.14[/C][C]0.444618[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62568&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62568&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
1-0.583049-3.99720.000112
2-0.627808-4.3044.2e-05
30.0397560.27260.393196
40.0142340.09760.461338
50.0846740.58050.282176
60.0827330.56720.286642
7-0.060847-0.41710.339235
80.0125920.08630.465786
90.0287120.19680.4224
10-0.079823-0.54720.293402
11-0.00802-0.0550.478193
120.0116290.07970.468398
13-0.16111-1.10450.137496
14-0.159863-1.0960.139339
15-0.019063-0.13070.448289
160.0374860.2570.399153
17-0.102872-0.70530.242066
18-0.014404-0.09880.460878
19-0.042504-0.29140.386018
200.0171580.11760.453431
210.0854760.5860.280341
22-0.121545-0.83330.204453
23-0.000889-0.00610.497581
24-0.023175-0.15890.437222
250.0501140.34360.366353
26-0.104265-0.71480.239133
270.107430.73650.232543
28-0.114443-0.78460.218318
29-0.20225-1.38660.086059
30-0.033593-0.23030.409428
310.0960.65810.256829
320.0178310.12220.451615
330.0625080.42850.335111
34-0.067328-0.46160.323256
35-0.006147-0.04210.483282
36-0.020425-0.140.444618


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')