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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, 26 Dec 2009 12:00:19 -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/26/t1261854049d1b221rrp0njfuy.htm/, Retrieved Mon, 29 Apr 2024 03:41:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70774, Retrieved Mon, 29 Apr 2024 03:41:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [paper3: pacf d,D=0] [2009-12-26 18:52:50] [0f0e461427f61416e46aeda5f4901bed]
-   P   [(Partial) Autocorrelation Function] [paper4 pacf d0D1] [2009-12-26 18:57:15] [0f0e461427f61416e46aeda5f4901bed]
-   P       [(Partial) Autocorrelation Function] [paper5 pacf dD1] [2009-12-26 19:00:19] [b090d569c0a4c77894e0b029f4429f19] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
111.6
104.6
91.6
98.3
97.7
106.3
102.3
106.6
108.1
93.8
88.2
108.9
114.2
102.5
94.2
97.4
98.5
106.5
102.9
97.1
103.7
93.4
85.8
108.6
110.2
101.2
101.2
96.9
99.4
118.7
108.0
101.2
119.9
94.8
95.3
118.0
115.9
111.4
108.2
108.8
109.5
124.8
115.3
109.5
124.2
92.9
98.4
120.9
111.7
116.1
109.4
111.7
114.3
133.7
114.3
126.5
131.0
104.0
108.9
128.5
132.4
128.0
116.4
120.9
118.6
133.1
121.1
127.6
135.4
114.9
114.3
128.9
138.9
129.4
115.0
128.0
127.0
128.8
137.9
128.4
135.9
122.2
113.1
136.2
138.0
115.2
111.0
99.2
102.4
112.7
105.5
98.3
116.4
97.4
93.3
117.4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70774&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]3 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=70774&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70774&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.549249-5.00392e-06
2-0.042263-0.3850.350599
30.4710794.29172.4e-05
4-0.410483-3.73970.000169
50.094530.86120.195801
60.2034021.85310.033713
7-0.335696-3.05830.001498
80.2249712.04960.021781
9-0.043997-0.40080.344788
10-0.14997-1.36630.087769
110.1737191.58270.058652
12-0.098167-0.89430.186863
13-0.103492-0.94290.174245
140.1932481.76060.040997
15-0.096272-0.87710.191488
16-0.083345-0.75930.224908
170.1279381.16560.123563
180.0259870.23680.406715
19-0.19814-1.80510.037339
200.1836261.67290.049055
210.0371010.3380.368106
22-0.280456-2.55510.006221
230.4145633.77690.000149
24-0.243934-2.22230.01449
25-0.051646-0.47050.319608
260.2992312.72610.003908
27-0.273924-2.49560.007278
280.0397310.3620.359149
290.1956061.78210.039199
30-0.27503-2.50560.007088
310.1425891.29910.098762
320.0094520.08610.465794
33-0.15378-1.4010.08247
340.1391971.26810.104147
35-0.03219-0.29330.385025
36-0.13402-1.2210.112775

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.549249 & -5.0039 & 2e-06 \tabularnewline
2 & -0.042263 & -0.385 & 0.350599 \tabularnewline
3 & 0.471079 & 4.2917 & 2.4e-05 \tabularnewline
4 & -0.410483 & -3.7397 & 0.000169 \tabularnewline
5 & 0.09453 & 0.8612 & 0.195801 \tabularnewline
6 & 0.203402 & 1.8531 & 0.033713 \tabularnewline
7 & -0.335696 & -3.0583 & 0.001498 \tabularnewline
8 & 0.224971 & 2.0496 & 0.021781 \tabularnewline
9 & -0.043997 & -0.4008 & 0.344788 \tabularnewline
10 & -0.14997 & -1.3663 & 0.087769 \tabularnewline
11 & 0.173719 & 1.5827 & 0.058652 \tabularnewline
12 & -0.098167 & -0.8943 & 0.186863 \tabularnewline
13 & -0.103492 & -0.9429 & 0.174245 \tabularnewline
14 & 0.193248 & 1.7606 & 0.040997 \tabularnewline
15 & -0.096272 & -0.8771 & 0.191488 \tabularnewline
16 & -0.083345 & -0.7593 & 0.224908 \tabularnewline
17 & 0.127938 & 1.1656 & 0.123563 \tabularnewline
18 & 0.025987 & 0.2368 & 0.406715 \tabularnewline
19 & -0.19814 & -1.8051 & 0.037339 \tabularnewline
20 & 0.183626 & 1.6729 & 0.049055 \tabularnewline
21 & 0.037101 & 0.338 & 0.368106 \tabularnewline
22 & -0.280456 & -2.5551 & 0.006221 \tabularnewline
23 & 0.414563 & 3.7769 & 0.000149 \tabularnewline
24 & -0.243934 & -2.2223 & 0.01449 \tabularnewline
25 & -0.051646 & -0.4705 & 0.319608 \tabularnewline
26 & 0.299231 & 2.7261 & 0.003908 \tabularnewline
27 & -0.273924 & -2.4956 & 0.007278 \tabularnewline
28 & 0.039731 & 0.362 & 0.359149 \tabularnewline
29 & 0.195606 & 1.7821 & 0.039199 \tabularnewline
30 & -0.27503 & -2.5056 & 0.007088 \tabularnewline
31 & 0.142589 & 1.2991 & 0.098762 \tabularnewline
32 & 0.009452 & 0.0861 & 0.465794 \tabularnewline
33 & -0.15378 & -1.401 & 0.08247 \tabularnewline
34 & 0.139197 & 1.2681 & 0.104147 \tabularnewline
35 & -0.03219 & -0.2933 & 0.385025 \tabularnewline
36 & -0.13402 & -1.221 & 0.112775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70774&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]-0.549249[/C][C]-5.0039[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.042263[/C][C]-0.385[/C][C]0.350599[/C][/ROW]
[ROW][C]3[/C][C]0.471079[/C][C]4.2917[/C][C]2.4e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.410483[/C][C]-3.7397[/C][C]0.000169[/C][/ROW]
[ROW][C]5[/C][C]0.09453[/C][C]0.8612[/C][C]0.195801[/C][/ROW]
[ROW][C]6[/C][C]0.203402[/C][C]1.8531[/C][C]0.033713[/C][/ROW]
[ROW][C]7[/C][C]-0.335696[/C][C]-3.0583[/C][C]0.001498[/C][/ROW]
[ROW][C]8[/C][C]0.224971[/C][C]2.0496[/C][C]0.021781[/C][/ROW]
[ROW][C]9[/C][C]-0.043997[/C][C]-0.4008[/C][C]0.344788[/C][/ROW]
[ROW][C]10[/C][C]-0.14997[/C][C]-1.3663[/C][C]0.087769[/C][/ROW]
[ROW][C]11[/C][C]0.173719[/C][C]1.5827[/C][C]0.058652[/C][/ROW]
[ROW][C]12[/C][C]-0.098167[/C][C]-0.8943[/C][C]0.186863[/C][/ROW]
[ROW][C]13[/C][C]-0.103492[/C][C]-0.9429[/C][C]0.174245[/C][/ROW]
[ROW][C]14[/C][C]0.193248[/C][C]1.7606[/C][C]0.040997[/C][/ROW]
[ROW][C]15[/C][C]-0.096272[/C][C]-0.8771[/C][C]0.191488[/C][/ROW]
[ROW][C]16[/C][C]-0.083345[/C][C]-0.7593[/C][C]0.224908[/C][/ROW]
[ROW][C]17[/C][C]0.127938[/C][C]1.1656[/C][C]0.123563[/C][/ROW]
[ROW][C]18[/C][C]0.025987[/C][C]0.2368[/C][C]0.406715[/C][/ROW]
[ROW][C]19[/C][C]-0.19814[/C][C]-1.8051[/C][C]0.037339[/C][/ROW]
[ROW][C]20[/C][C]0.183626[/C][C]1.6729[/C][C]0.049055[/C][/ROW]
[ROW][C]21[/C][C]0.037101[/C][C]0.338[/C][C]0.368106[/C][/ROW]
[ROW][C]22[/C][C]-0.280456[/C][C]-2.5551[/C][C]0.006221[/C][/ROW]
[ROW][C]23[/C][C]0.414563[/C][C]3.7769[/C][C]0.000149[/C][/ROW]
[ROW][C]24[/C][C]-0.243934[/C][C]-2.2223[/C][C]0.01449[/C][/ROW]
[ROW][C]25[/C][C]-0.051646[/C][C]-0.4705[/C][C]0.319608[/C][/ROW]
[ROW][C]26[/C][C]0.299231[/C][C]2.7261[/C][C]0.003908[/C][/ROW]
[ROW][C]27[/C][C]-0.273924[/C][C]-2.4956[/C][C]0.007278[/C][/ROW]
[ROW][C]28[/C][C]0.039731[/C][C]0.362[/C][C]0.359149[/C][/ROW]
[ROW][C]29[/C][C]0.195606[/C][C]1.7821[/C][C]0.039199[/C][/ROW]
[ROW][C]30[/C][C]-0.27503[/C][C]-2.5056[/C][C]0.007088[/C][/ROW]
[ROW][C]31[/C][C]0.142589[/C][C]1.2991[/C][C]0.098762[/C][/ROW]
[ROW][C]32[/C][C]0.009452[/C][C]0.0861[/C][C]0.465794[/C][/ROW]
[ROW][C]33[/C][C]-0.15378[/C][C]-1.401[/C][C]0.08247[/C][/ROW]
[ROW][C]34[/C][C]0.139197[/C][C]1.2681[/C][C]0.104147[/C][/ROW]
[ROW][C]35[/C][C]-0.03219[/C][C]-0.2933[/C][C]0.385025[/C][/ROW]
[ROW][C]36[/C][C]-0.13402[/C][C]-1.221[/C][C]0.112775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70774&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70774&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
1-0.549249-5.00392e-06
2-0.042263-0.3850.350599
30.4710794.29172.4e-05
4-0.410483-3.73970.000169
50.094530.86120.195801
60.2034021.85310.033713
7-0.335696-3.05830.001498
80.2249712.04960.021781
9-0.043997-0.40080.344788
10-0.14997-1.36630.087769
110.1737191.58270.058652
12-0.098167-0.89430.186863
13-0.103492-0.94290.174245
140.1932481.76060.040997
15-0.096272-0.87710.191488
16-0.083345-0.75930.224908
170.1279381.16560.123563
180.0259870.23680.406715
19-0.19814-1.80510.037339
200.1836261.67290.049055
210.0371010.3380.368106
22-0.280456-2.55510.006221
230.4145633.77690.000149
24-0.243934-2.22230.01449
25-0.051646-0.47050.319608
260.2992312.72610.003908
27-0.273924-2.49560.007278
280.0397310.3620.359149
290.1956061.78210.039199
30-0.27503-2.50560.007088
310.1425891.29910.098762
320.0094520.08610.465794
33-0.15378-1.4010.08247
340.1391971.26810.104147
35-0.03219-0.29330.385025
36-0.13402-1.2210.112775






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.549249-5.00392e-06
2-0.492516-4.4871.2e-05
30.3136882.85780.002695
40.1368361.24660.108018
5-0.01753-0.15970.436749
6-0.007928-0.07220.471299
7-0.151578-1.38090.085502
80.0006650.00610.49759
9-0.062788-0.5720.284426
10-0.050619-0.46120.322943
11-0.050947-0.46410.321878
12-0.016677-0.15190.439803
13-0.145149-1.32240.094839
14-0.033013-0.30080.382173
150.1311341.19470.117806
16-0.006257-0.0570.477338
17-0.140485-1.27990.102077
180.1230291.12080.132793
19-0.066255-0.60360.273873
20-0.096983-0.88360.189744
210.1151471.0490.148603
22-0.140116-1.27650.102667
230.2535052.30950.011699
240.0093290.0850.466236
250.0033240.03030.487958
26-0.009721-0.08860.464821
270.0808030.73620.231856
28-0.055645-0.5070.306767
29-0.074337-0.67720.250069
300.0736830.67130.251952
31-0.045886-0.4180.338499
32-0.133909-1.220.112965
33-0.027147-0.24730.402636
340.0134160.12220.451508
350.0589970.53750.296184
36-0.047232-0.43030.334044

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.549249 & -5.0039 & 2e-06 \tabularnewline
2 & -0.492516 & -4.487 & 1.2e-05 \tabularnewline
3 & 0.313688 & 2.8578 & 0.002695 \tabularnewline
4 & 0.136836 & 1.2466 & 0.108018 \tabularnewline
5 & -0.01753 & -0.1597 & 0.436749 \tabularnewline
6 & -0.007928 & -0.0722 & 0.471299 \tabularnewline
7 & -0.151578 & -1.3809 & 0.085502 \tabularnewline
8 & 0.000665 & 0.0061 & 0.49759 \tabularnewline
9 & -0.062788 & -0.572 & 0.284426 \tabularnewline
10 & -0.050619 & -0.4612 & 0.322943 \tabularnewline
11 & -0.050947 & -0.4641 & 0.321878 \tabularnewline
12 & -0.016677 & -0.1519 & 0.439803 \tabularnewline
13 & -0.145149 & -1.3224 & 0.094839 \tabularnewline
14 & -0.033013 & -0.3008 & 0.382173 \tabularnewline
15 & 0.131134 & 1.1947 & 0.117806 \tabularnewline
16 & -0.006257 & -0.057 & 0.477338 \tabularnewline
17 & -0.140485 & -1.2799 & 0.102077 \tabularnewline
18 & 0.123029 & 1.1208 & 0.132793 \tabularnewline
19 & -0.066255 & -0.6036 & 0.273873 \tabularnewline
20 & -0.096983 & -0.8836 & 0.189744 \tabularnewline
21 & 0.115147 & 1.049 & 0.148603 \tabularnewline
22 & -0.140116 & -1.2765 & 0.102667 \tabularnewline
23 & 0.253505 & 2.3095 & 0.011699 \tabularnewline
24 & 0.009329 & 0.085 & 0.466236 \tabularnewline
25 & 0.003324 & 0.0303 & 0.487958 \tabularnewline
26 & -0.009721 & -0.0886 & 0.464821 \tabularnewline
27 & 0.080803 & 0.7362 & 0.231856 \tabularnewline
28 & -0.055645 & -0.507 & 0.306767 \tabularnewline
29 & -0.074337 & -0.6772 & 0.250069 \tabularnewline
30 & 0.073683 & 0.6713 & 0.251952 \tabularnewline
31 & -0.045886 & -0.418 & 0.338499 \tabularnewline
32 & -0.133909 & -1.22 & 0.112965 \tabularnewline
33 & -0.027147 & -0.2473 & 0.402636 \tabularnewline
34 & 0.013416 & 0.1222 & 0.451508 \tabularnewline
35 & 0.058997 & 0.5375 & 0.296184 \tabularnewline
36 & -0.047232 & -0.4303 & 0.334044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70774&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]-0.549249[/C][C]-5.0039[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.492516[/C][C]-4.487[/C][C]1.2e-05[/C][/ROW]
[ROW][C]3[/C][C]0.313688[/C][C]2.8578[/C][C]0.002695[/C][/ROW]
[ROW][C]4[/C][C]0.136836[/C][C]1.2466[/C][C]0.108018[/C][/ROW]
[ROW][C]5[/C][C]-0.01753[/C][C]-0.1597[/C][C]0.436749[/C][/ROW]
[ROW][C]6[/C][C]-0.007928[/C][C]-0.0722[/C][C]0.471299[/C][/ROW]
[ROW][C]7[/C][C]-0.151578[/C][C]-1.3809[/C][C]0.085502[/C][/ROW]
[ROW][C]8[/C][C]0.000665[/C][C]0.0061[/C][C]0.49759[/C][/ROW]
[ROW][C]9[/C][C]-0.062788[/C][C]-0.572[/C][C]0.284426[/C][/ROW]
[ROW][C]10[/C][C]-0.050619[/C][C]-0.4612[/C][C]0.322943[/C][/ROW]
[ROW][C]11[/C][C]-0.050947[/C][C]-0.4641[/C][C]0.321878[/C][/ROW]
[ROW][C]12[/C][C]-0.016677[/C][C]-0.1519[/C][C]0.439803[/C][/ROW]
[ROW][C]13[/C][C]-0.145149[/C][C]-1.3224[/C][C]0.094839[/C][/ROW]
[ROW][C]14[/C][C]-0.033013[/C][C]-0.3008[/C][C]0.382173[/C][/ROW]
[ROW][C]15[/C][C]0.131134[/C][C]1.1947[/C][C]0.117806[/C][/ROW]
[ROW][C]16[/C][C]-0.006257[/C][C]-0.057[/C][C]0.477338[/C][/ROW]
[ROW][C]17[/C][C]-0.140485[/C][C]-1.2799[/C][C]0.102077[/C][/ROW]
[ROW][C]18[/C][C]0.123029[/C][C]1.1208[/C][C]0.132793[/C][/ROW]
[ROW][C]19[/C][C]-0.066255[/C][C]-0.6036[/C][C]0.273873[/C][/ROW]
[ROW][C]20[/C][C]-0.096983[/C][C]-0.8836[/C][C]0.189744[/C][/ROW]
[ROW][C]21[/C][C]0.115147[/C][C]1.049[/C][C]0.148603[/C][/ROW]
[ROW][C]22[/C][C]-0.140116[/C][C]-1.2765[/C][C]0.102667[/C][/ROW]
[ROW][C]23[/C][C]0.253505[/C][C]2.3095[/C][C]0.011699[/C][/ROW]
[ROW][C]24[/C][C]0.009329[/C][C]0.085[/C][C]0.466236[/C][/ROW]
[ROW][C]25[/C][C]0.003324[/C][C]0.0303[/C][C]0.487958[/C][/ROW]
[ROW][C]26[/C][C]-0.009721[/C][C]-0.0886[/C][C]0.464821[/C][/ROW]
[ROW][C]27[/C][C]0.080803[/C][C]0.7362[/C][C]0.231856[/C][/ROW]
[ROW][C]28[/C][C]-0.055645[/C][C]-0.507[/C][C]0.306767[/C][/ROW]
[ROW][C]29[/C][C]-0.074337[/C][C]-0.6772[/C][C]0.250069[/C][/ROW]
[ROW][C]30[/C][C]0.073683[/C][C]0.6713[/C][C]0.251952[/C][/ROW]
[ROW][C]31[/C][C]-0.045886[/C][C]-0.418[/C][C]0.338499[/C][/ROW]
[ROW][C]32[/C][C]-0.133909[/C][C]-1.22[/C][C]0.112965[/C][/ROW]
[ROW][C]33[/C][C]-0.027147[/C][C]-0.2473[/C][C]0.402636[/C][/ROW]
[ROW][C]34[/C][C]0.013416[/C][C]0.1222[/C][C]0.451508[/C][/ROW]
[ROW][C]35[/C][C]0.058997[/C][C]0.5375[/C][C]0.296184[/C][/ROW]
[ROW][C]36[/C][C]-0.047232[/C][C]-0.4303[/C][C]0.334044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70774&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70774&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
1-0.549249-5.00392e-06
2-0.492516-4.4871.2e-05
30.3136882.85780.002695
40.1368361.24660.108018
5-0.01753-0.15970.436749
6-0.007928-0.07220.471299
7-0.151578-1.38090.085502
80.0006650.00610.49759
9-0.062788-0.5720.284426
10-0.050619-0.46120.322943
11-0.050947-0.46410.321878
12-0.016677-0.15190.439803
13-0.145149-1.32240.094839
14-0.033013-0.30080.382173
150.1311341.19470.117806
16-0.006257-0.0570.477338
17-0.140485-1.27990.102077
180.1230291.12080.132793
19-0.066255-0.60360.273873
20-0.096983-0.88360.189744
210.1151471.0490.148603
22-0.140116-1.27650.102667
230.2535052.30950.011699
240.0093290.0850.466236
250.0033240.03030.487958
26-0.009721-0.08860.464821
270.0808030.73620.231856
28-0.055645-0.5070.306767
29-0.074337-0.67720.250069
300.0736830.67130.251952
31-0.045886-0.4180.338499
32-0.133909-1.220.112965
33-0.027147-0.24730.402636
340.0134160.12220.451508
350.0589970.53750.296184
36-0.047232-0.43030.334044


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')