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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 computationThu, 03 Dec 2009 05:13:55 -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/03/t125984245954yjqkdejfz0x9f.htm/, Retrieved Thu, 18 Apr 2024 20:37:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62689, Retrieved Thu, 18 Apr 2024 20:37:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [] [2009-12-03 12:09:45] [875a981b2b01315c1c471abd4dd66675]
-   PD        [(Partial) Autocorrelation Function] [] [2009-12-03 12:13:55] [8551abdd6804649d94d88b1829ac2b1a] [Current]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 12:15:21] [875a981b2b01315c1c471abd4dd66675]
- RMP           [ARIMA Backward Selection] [] [2009-12-11 17:32:13] [875a981b2b01315c1c471abd4dd66675]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
128.7
136.9
156.9
109.1
122.3
123.9
90.9
77.9
120.3
118.9
125.5
98.9
102.9
105.9
117.6
113.6
115.9
118.9
77.6
81.2
123.1
136.6
112.1
95.1
96.3
105.7
115.8
105.7
105.7
111.1
82.4
60
107.3
99.3
113.5
108.9
100.2
103.9
138.7
120.2
100.2
143.2
70.9
85.2
133
136.6
117.9
106.3
122.3
125.5
148.4
126.3
99.6
140.4
80.3
92.6
138.5
110.9
119.6
105
109
129.4
148.6
101.4
134.8
143.7
81.6
90.3
141.5
140.7
140.2
100.2
125.7
119.6
134.7
109
116.3
146.9
97.4
89.4
132.1
139.8
129
112.5
121.9
121.7
123.1
131.6
119.3
132.5
98.3
85.1
131.7
129.3
90.7
78.6
68.9
79.1
83.5
74.1
59.7
93.3
61.3
56.6
98.5

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=62689&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=62689&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62689&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
1-0.281081-2.86650.002512
2-0.373939-3.81340.000116
30.1712871.74680.041813
4-0.019239-0.19620.422417
5-0.006578-0.06710.473321
60.0789910.80560.211168
7-0.039489-0.40270.343993
80.0123750.12620.44991
90.132921.35550.089093
10-0.363681-3.70880.000168
11-0.125147-1.27630.102354
120.6656746.78860
13-0.1632-1.66430.049529
14-0.340546-3.47290.000376
150.1611141.64310.051696
16-0.023996-0.24470.403582
170.0085310.0870.465419
180.0004620.00470.498125
190.0253130.25810.398405
200.0138360.14110.444031
210.1137941.16050.124256
22-0.326731-3.3320.000597
23-0.097165-0.99090.162018
240.5847355.96320
25-0.12793-1.30460.097448
26-0.307426-3.13510.001117
270.1203341.22720.111264
280.0172810.17620.430225
29-0.005896-0.06010.476087
30-0.001163-0.01190.49528
310.0361480.36860.356573
32-0.035235-0.35930.360039
330.0853460.87040.193053
34-0.196137-2.00020.024042
35-0.142641-1.45470.074388
360.4813844.90922e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.281081 & -2.8665 & 0.002512 \tabularnewline
2 & -0.373939 & -3.8134 & 0.000116 \tabularnewline
3 & 0.171287 & 1.7468 & 0.041813 \tabularnewline
4 & -0.019239 & -0.1962 & 0.422417 \tabularnewline
5 & -0.006578 & -0.0671 & 0.473321 \tabularnewline
6 & 0.078991 & 0.8056 & 0.211168 \tabularnewline
7 & -0.039489 & -0.4027 & 0.343993 \tabularnewline
8 & 0.012375 & 0.1262 & 0.44991 \tabularnewline
9 & 0.13292 & 1.3555 & 0.089093 \tabularnewline
10 & -0.363681 & -3.7088 & 0.000168 \tabularnewline
11 & -0.125147 & -1.2763 & 0.102354 \tabularnewline
12 & 0.665674 & 6.7886 & 0 \tabularnewline
13 & -0.1632 & -1.6643 & 0.049529 \tabularnewline
14 & -0.340546 & -3.4729 & 0.000376 \tabularnewline
15 & 0.161114 & 1.6431 & 0.051696 \tabularnewline
16 & -0.023996 & -0.2447 & 0.403582 \tabularnewline
17 & 0.008531 & 0.087 & 0.465419 \tabularnewline
18 & 0.000462 & 0.0047 & 0.498125 \tabularnewline
19 & 0.025313 & 0.2581 & 0.398405 \tabularnewline
20 & 0.013836 & 0.1411 & 0.444031 \tabularnewline
21 & 0.113794 & 1.1605 & 0.124256 \tabularnewline
22 & -0.326731 & -3.332 & 0.000597 \tabularnewline
23 & -0.097165 & -0.9909 & 0.162018 \tabularnewline
24 & 0.584735 & 5.9632 & 0 \tabularnewline
25 & -0.12793 & -1.3046 & 0.097448 \tabularnewline
26 & -0.307426 & -3.1351 & 0.001117 \tabularnewline
27 & 0.120334 & 1.2272 & 0.111264 \tabularnewline
28 & 0.017281 & 0.1762 & 0.430225 \tabularnewline
29 & -0.005896 & -0.0601 & 0.476087 \tabularnewline
30 & -0.001163 & -0.0119 & 0.49528 \tabularnewline
31 & 0.036148 & 0.3686 & 0.356573 \tabularnewline
32 & -0.035235 & -0.3593 & 0.360039 \tabularnewline
33 & 0.085346 & 0.8704 & 0.193053 \tabularnewline
34 & -0.196137 & -2.0002 & 0.024042 \tabularnewline
35 & -0.142641 & -1.4547 & 0.074388 \tabularnewline
36 & 0.481384 & 4.9092 & 2e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62689&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]-0.281081[/C][C]-2.8665[/C][C]0.002512[/C][/ROW]
[ROW][C]2[/C][C]-0.373939[/C][C]-3.8134[/C][C]0.000116[/C][/ROW]
[ROW][C]3[/C][C]0.171287[/C][C]1.7468[/C][C]0.041813[/C][/ROW]
[ROW][C]4[/C][C]-0.019239[/C][C]-0.1962[/C][C]0.422417[/C][/ROW]
[ROW][C]5[/C][C]-0.006578[/C][C]-0.0671[/C][C]0.473321[/C][/ROW]
[ROW][C]6[/C][C]0.078991[/C][C]0.8056[/C][C]0.211168[/C][/ROW]
[ROW][C]7[/C][C]-0.039489[/C][C]-0.4027[/C][C]0.343993[/C][/ROW]
[ROW][C]8[/C][C]0.012375[/C][C]0.1262[/C][C]0.44991[/C][/ROW]
[ROW][C]9[/C][C]0.13292[/C][C]1.3555[/C][C]0.089093[/C][/ROW]
[ROW][C]10[/C][C]-0.363681[/C][C]-3.7088[/C][C]0.000168[/C][/ROW]
[ROW][C]11[/C][C]-0.125147[/C][C]-1.2763[/C][C]0.102354[/C][/ROW]
[ROW][C]12[/C][C]0.665674[/C][C]6.7886[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.1632[/C][C]-1.6643[/C][C]0.049529[/C][/ROW]
[ROW][C]14[/C][C]-0.340546[/C][C]-3.4729[/C][C]0.000376[/C][/ROW]
[ROW][C]15[/C][C]0.161114[/C][C]1.6431[/C][C]0.051696[/C][/ROW]
[ROW][C]16[/C][C]-0.023996[/C][C]-0.2447[/C][C]0.403582[/C][/ROW]
[ROW][C]17[/C][C]0.008531[/C][C]0.087[/C][C]0.465419[/C][/ROW]
[ROW][C]18[/C][C]0.000462[/C][C]0.0047[/C][C]0.498125[/C][/ROW]
[ROW][C]19[/C][C]0.025313[/C][C]0.2581[/C][C]0.398405[/C][/ROW]
[ROW][C]20[/C][C]0.013836[/C][C]0.1411[/C][C]0.444031[/C][/ROW]
[ROW][C]21[/C][C]0.113794[/C][C]1.1605[/C][C]0.124256[/C][/ROW]
[ROW][C]22[/C][C]-0.326731[/C][C]-3.332[/C][C]0.000597[/C][/ROW]
[ROW][C]23[/C][C]-0.097165[/C][C]-0.9909[/C][C]0.162018[/C][/ROW]
[ROW][C]24[/C][C]0.584735[/C][C]5.9632[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.12793[/C][C]-1.3046[/C][C]0.097448[/C][/ROW]
[ROW][C]26[/C][C]-0.307426[/C][C]-3.1351[/C][C]0.001117[/C][/ROW]
[ROW][C]27[/C][C]0.120334[/C][C]1.2272[/C][C]0.111264[/C][/ROW]
[ROW][C]28[/C][C]0.017281[/C][C]0.1762[/C][C]0.430225[/C][/ROW]
[ROW][C]29[/C][C]-0.005896[/C][C]-0.0601[/C][C]0.476087[/C][/ROW]
[ROW][C]30[/C][C]-0.001163[/C][C]-0.0119[/C][C]0.49528[/C][/ROW]
[ROW][C]31[/C][C]0.036148[/C][C]0.3686[/C][C]0.356573[/C][/ROW]
[ROW][C]32[/C][C]-0.035235[/C][C]-0.3593[/C][C]0.360039[/C][/ROW]
[ROW][C]33[/C][C]0.085346[/C][C]0.8704[/C][C]0.193053[/C][/ROW]
[ROW][C]34[/C][C]-0.196137[/C][C]-2.0002[/C][C]0.024042[/C][/ROW]
[ROW][C]35[/C][C]-0.142641[/C][C]-1.4547[/C][C]0.074388[/C][/ROW]
[ROW][C]36[/C][C]0.481384[/C][C]4.9092[/C][C]2e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62689&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62689&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
1-0.281081-2.86650.002512
2-0.373939-3.81340.000116
30.1712871.74680.041813
4-0.019239-0.19620.422417
5-0.006578-0.06710.473321
60.0789910.80560.211168
7-0.039489-0.40270.343993
80.0123750.12620.44991
90.132921.35550.089093
10-0.363681-3.70880.000168
11-0.125147-1.27630.102354
120.6656746.78860
13-0.1632-1.66430.049529
14-0.340546-3.47290.000376
150.1611141.64310.051696
16-0.023996-0.24470.403582
170.0085310.0870.465419
180.0004620.00470.498125
190.0253130.25810.398405
200.0138360.14110.444031
210.1137941.16050.124256
22-0.326731-3.3320.000597
23-0.097165-0.99090.162018
240.5847355.96320
25-0.12793-1.30460.097448
26-0.307426-3.13510.001117
270.1203341.22720.111264
280.0172810.17620.430225
29-0.005896-0.06010.476087
30-0.001163-0.01190.49528
310.0361480.36860.356573
32-0.035235-0.35930.360039
330.0853460.87040.193053
34-0.196137-2.00020.024042
35-0.142641-1.45470.074388
360.4813844.90922e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.281081-2.86650.002512
2-0.491801-5.01541e-06
3-0.17723-1.80740.036796
4-0.286847-2.92530.002113
5-0.15104-1.54030.063261
6-0.077525-0.79060.215489
7-0.045116-0.46010.323205
80.0475430.48480.314402
90.2631052.68320.004243
10-0.250693-2.55660.006008
11-0.494582-5.04381e-06
120.2269932.31490.011292
130.1493931.52350.065332
140.0056370.05750.477134
150.0138880.14160.443821
16-0.037237-0.37970.352456
17-0.000917-0.00940.496278
18-0.214183-2.18420.015595
19-0.020779-0.21190.416297
20-0.100271-1.02260.154442
210.0423580.4320.333331
22-0.054835-0.55920.288611
23-0.124822-1.27290.10294
240.1150161.17290.121749
250.1094571.11630.133444
260.0713040.72720.234379
27-0.020034-0.20430.419255
28-0.000937-0.00960.496196
290.0078230.07980.468285
30-0.026968-0.2750.391923
310.0539680.55040.291625
32-0.16197-1.65180.050798
33-0.131842-1.34450.090851
340.0520470.53080.298354
35-0.049393-0.50370.307764
36-0.056922-0.58050.28142

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.281081 & -2.8665 & 0.002512 \tabularnewline
2 & -0.491801 & -5.0154 & 1e-06 \tabularnewline
3 & -0.17723 & -1.8074 & 0.036796 \tabularnewline
4 & -0.286847 & -2.9253 & 0.002113 \tabularnewline
5 & -0.15104 & -1.5403 & 0.063261 \tabularnewline
6 & -0.077525 & -0.7906 & 0.215489 \tabularnewline
7 & -0.045116 & -0.4601 & 0.323205 \tabularnewline
8 & 0.047543 & 0.4848 & 0.314402 \tabularnewline
9 & 0.263105 & 2.6832 & 0.004243 \tabularnewline
10 & -0.250693 & -2.5566 & 0.006008 \tabularnewline
11 & -0.494582 & -5.0438 & 1e-06 \tabularnewline
12 & 0.226993 & 2.3149 & 0.011292 \tabularnewline
13 & 0.149393 & 1.5235 & 0.065332 \tabularnewline
14 & 0.005637 & 0.0575 & 0.477134 \tabularnewline
15 & 0.013888 & 0.1416 & 0.443821 \tabularnewline
16 & -0.037237 & -0.3797 & 0.352456 \tabularnewline
17 & -0.000917 & -0.0094 & 0.496278 \tabularnewline
18 & -0.214183 & -2.1842 & 0.015595 \tabularnewline
19 & -0.020779 & -0.2119 & 0.416297 \tabularnewline
20 & -0.100271 & -1.0226 & 0.154442 \tabularnewline
21 & 0.042358 & 0.432 & 0.333331 \tabularnewline
22 & -0.054835 & -0.5592 & 0.288611 \tabularnewline
23 & -0.124822 & -1.2729 & 0.10294 \tabularnewline
24 & 0.115016 & 1.1729 & 0.121749 \tabularnewline
25 & 0.109457 & 1.1163 & 0.133444 \tabularnewline
26 & 0.071304 & 0.7272 & 0.234379 \tabularnewline
27 & -0.020034 & -0.2043 & 0.419255 \tabularnewline
28 & -0.000937 & -0.0096 & 0.496196 \tabularnewline
29 & 0.007823 & 0.0798 & 0.468285 \tabularnewline
30 & -0.026968 & -0.275 & 0.391923 \tabularnewline
31 & 0.053968 & 0.5504 & 0.291625 \tabularnewline
32 & -0.16197 & -1.6518 & 0.050798 \tabularnewline
33 & -0.131842 & -1.3445 & 0.090851 \tabularnewline
34 & 0.052047 & 0.5308 & 0.298354 \tabularnewline
35 & -0.049393 & -0.5037 & 0.307764 \tabularnewline
36 & -0.056922 & -0.5805 & 0.28142 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62689&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]-0.281081[/C][C]-2.8665[/C][C]0.002512[/C][/ROW]
[ROW][C]2[/C][C]-0.491801[/C][C]-5.0154[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]-0.17723[/C][C]-1.8074[/C][C]0.036796[/C][/ROW]
[ROW][C]4[/C][C]-0.286847[/C][C]-2.9253[/C][C]0.002113[/C][/ROW]
[ROW][C]5[/C][C]-0.15104[/C][C]-1.5403[/C][C]0.063261[/C][/ROW]
[ROW][C]6[/C][C]-0.077525[/C][C]-0.7906[/C][C]0.215489[/C][/ROW]
[ROW][C]7[/C][C]-0.045116[/C][C]-0.4601[/C][C]0.323205[/C][/ROW]
[ROW][C]8[/C][C]0.047543[/C][C]0.4848[/C][C]0.314402[/C][/ROW]
[ROW][C]9[/C][C]0.263105[/C][C]2.6832[/C][C]0.004243[/C][/ROW]
[ROW][C]10[/C][C]-0.250693[/C][C]-2.5566[/C][C]0.006008[/C][/ROW]
[ROW][C]11[/C][C]-0.494582[/C][C]-5.0438[/C][C]1e-06[/C][/ROW]
[ROW][C]12[/C][C]0.226993[/C][C]2.3149[/C][C]0.011292[/C][/ROW]
[ROW][C]13[/C][C]0.149393[/C][C]1.5235[/C][C]0.065332[/C][/ROW]
[ROW][C]14[/C][C]0.005637[/C][C]0.0575[/C][C]0.477134[/C][/ROW]
[ROW][C]15[/C][C]0.013888[/C][C]0.1416[/C][C]0.443821[/C][/ROW]
[ROW][C]16[/C][C]-0.037237[/C][C]-0.3797[/C][C]0.352456[/C][/ROW]
[ROW][C]17[/C][C]-0.000917[/C][C]-0.0094[/C][C]0.496278[/C][/ROW]
[ROW][C]18[/C][C]-0.214183[/C][C]-2.1842[/C][C]0.015595[/C][/ROW]
[ROW][C]19[/C][C]-0.020779[/C][C]-0.2119[/C][C]0.416297[/C][/ROW]
[ROW][C]20[/C][C]-0.100271[/C][C]-1.0226[/C][C]0.154442[/C][/ROW]
[ROW][C]21[/C][C]0.042358[/C][C]0.432[/C][C]0.333331[/C][/ROW]
[ROW][C]22[/C][C]-0.054835[/C][C]-0.5592[/C][C]0.288611[/C][/ROW]
[ROW][C]23[/C][C]-0.124822[/C][C]-1.2729[/C][C]0.10294[/C][/ROW]
[ROW][C]24[/C][C]0.115016[/C][C]1.1729[/C][C]0.121749[/C][/ROW]
[ROW][C]25[/C][C]0.109457[/C][C]1.1163[/C][C]0.133444[/C][/ROW]
[ROW][C]26[/C][C]0.071304[/C][C]0.7272[/C][C]0.234379[/C][/ROW]
[ROW][C]27[/C][C]-0.020034[/C][C]-0.2043[/C][C]0.419255[/C][/ROW]
[ROW][C]28[/C][C]-0.000937[/C][C]-0.0096[/C][C]0.496196[/C][/ROW]
[ROW][C]29[/C][C]0.007823[/C][C]0.0798[/C][C]0.468285[/C][/ROW]
[ROW][C]30[/C][C]-0.026968[/C][C]-0.275[/C][C]0.391923[/C][/ROW]
[ROW][C]31[/C][C]0.053968[/C][C]0.5504[/C][C]0.291625[/C][/ROW]
[ROW][C]32[/C][C]-0.16197[/C][C]-1.6518[/C][C]0.050798[/C][/ROW]
[ROW][C]33[/C][C]-0.131842[/C][C]-1.3445[/C][C]0.090851[/C][/ROW]
[ROW][C]34[/C][C]0.052047[/C][C]0.5308[/C][C]0.298354[/C][/ROW]
[ROW][C]35[/C][C]-0.049393[/C][C]-0.5037[/C][C]0.307764[/C][/ROW]
[ROW][C]36[/C][C]-0.056922[/C][C]-0.5805[/C][C]0.28142[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62689&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62689&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
1-0.281081-2.86650.002512
2-0.491801-5.01541e-06
3-0.17723-1.80740.036796
4-0.286847-2.92530.002113
5-0.15104-1.54030.063261
6-0.077525-0.79060.215489
7-0.045116-0.46010.323205
80.0475430.48480.314402
90.2631052.68320.004243
10-0.250693-2.55660.006008
11-0.494582-5.04381e-06
120.2269932.31490.011292
130.1493931.52350.065332
140.0056370.05750.477134
150.0138880.14160.443821
16-0.037237-0.37970.352456
17-0.000917-0.00940.496278
18-0.214183-2.18420.015595
19-0.020779-0.21190.416297
20-0.100271-1.02260.154442
210.0423580.4320.333331
22-0.054835-0.55920.288611
23-0.124822-1.27290.10294
240.1150161.17290.121749
250.1094571.11630.133444
260.0713040.72720.234379
27-0.020034-0.20430.419255
28-0.000937-0.00960.496196
290.0078230.07980.468285
30-0.026968-0.2750.391923
310.0539680.55040.291625
32-0.16197-1.65180.050798
33-0.131842-1.34450.090851
340.0520470.53080.298354
35-0.049393-0.50370.307764
36-0.056922-0.58050.28142


Figures (Output of Computation)

Input Parameters & R Code

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