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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 computationTue, 16 Dec 2008 14:14:03 -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/16/t1229462099ok20g63mtj5af8w.htm/, Retrieved Wed, 15 May 2024 23:40:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34209, Retrieved Wed, 15 May 2024 23:40:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact233

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-16 18:30:07] [b47fceb71c9525e79a89b5fc6d023d0e]
- RM D  [Variance Reduction Matrix] [Variance Reductio...] [2008-12-16 19:16:23] [b47fceb71c9525e79a89b5fc6d023d0e]
- RMP       [(Partial) Autocorrelation Function] [autocorrelation f...] [2008-12-16 21:14:03] [541f63fa3157af9df10fc4d202b2a90b] [Current]
-   P         [(Partial) Autocorrelation Function] [Autocorrelation F...] [2008-12-17 20:02:19] [b47fceb71c9525e79a89b5fc6d023d0e]
-    D        [(Partial) Autocorrelation Function] [Autocorrelation F...] [2008-12-20 20:00:45] [b47fceb71c9525e79a89b5fc6d023d0e]
-   PD        [(Partial) Autocorrelation Function] [Autocorrelation F...] [2008-12-20 20:03:50] [b47fceb71c9525e79a89b5fc6d023d0e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91.2
99.2
108.2
101.5
106.9
104.4
77.9
60
99.5
95
105.6
102.5
93.3
97.3
127
111.7
96.4
133
72.2
95.8
124.1
127.6
110.7
104.6
112.7
115.3
139.4
119
97.4
154
81.5
88.8
127.7
105.1
114.9
106.4
104.5
121.6
141.4
99
126.7
134.1
81.3
88.6
132.7
132.9
134.4
103.7
119.7
115
132.9
108.5
113.9
142
97.7
92.2
128.8
134.9
128.2
114.8

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34209&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34209&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'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1025130.79410.215145
2-0.102028-0.79030.21623
30.2285191.77010.040896
40.0533310.41310.340503
50.1271850.98520.164249
60.2278231.76470.041351
70.0703320.54480.29396
80.0542660.42030.337868
90.1655451.28230.102334
10-0.186272-1.44290.077131
110.0310980.24090.405234
120.5654094.37962.4e-05
13-0.037461-0.29020.386342
14-0.244997-1.89770.031272
150.0673040.52130.302026
16-0.054954-0.42570.335934
17-0.023036-0.17840.429491
180.0597740.4630.322516
19-0.006792-0.05260.479109
20-0.060872-0.47150.319493
210.0818970.63440.264126
22-0.234008-1.81260.037447
23-0.012885-0.09980.460416
240.3467042.68560.004675
25-0.065447-0.50690.307025
26-0.153126-1.18610.120128
270.02850.22080.413015
28-0.082317-0.63760.263072
29-0.02281-0.17670.430175
300.0450770.34920.364095
31-0.020385-0.15790.437533
32-0.032621-0.25270.400688
33-0.018916-0.14650.442
34-0.149348-1.15680.12596
35-0.035136-0.27220.393214
360.1608481.24590.108818

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.102513 & 0.7941 & 0.215145 \tabularnewline
2 & -0.102028 & -0.7903 & 0.21623 \tabularnewline
3 & 0.228519 & 1.7701 & 0.040896 \tabularnewline
4 & 0.053331 & 0.4131 & 0.340503 \tabularnewline
5 & 0.127185 & 0.9852 & 0.164249 \tabularnewline
6 & 0.227823 & 1.7647 & 0.041351 \tabularnewline
7 & 0.070332 & 0.5448 & 0.29396 \tabularnewline
8 & 0.054266 & 0.4203 & 0.337868 \tabularnewline
9 & 0.165545 & 1.2823 & 0.102334 \tabularnewline
10 & -0.186272 & -1.4429 & 0.077131 \tabularnewline
11 & 0.031098 & 0.2409 & 0.405234 \tabularnewline
12 & 0.565409 & 4.3796 & 2.4e-05 \tabularnewline
13 & -0.037461 & -0.2902 & 0.386342 \tabularnewline
14 & -0.244997 & -1.8977 & 0.031272 \tabularnewline
15 & 0.067304 & 0.5213 & 0.302026 \tabularnewline
16 & -0.054954 & -0.4257 & 0.335934 \tabularnewline
17 & -0.023036 & -0.1784 & 0.429491 \tabularnewline
18 & 0.059774 & 0.463 & 0.322516 \tabularnewline
19 & -0.006792 & -0.0526 & 0.479109 \tabularnewline
20 & -0.060872 & -0.4715 & 0.319493 \tabularnewline
21 & 0.081897 & 0.6344 & 0.264126 \tabularnewline
22 & -0.234008 & -1.8126 & 0.037447 \tabularnewline
23 & -0.012885 & -0.0998 & 0.460416 \tabularnewline
24 & 0.346704 & 2.6856 & 0.004675 \tabularnewline
25 & -0.065447 & -0.5069 & 0.307025 \tabularnewline
26 & -0.153126 & -1.1861 & 0.120128 \tabularnewline
27 & 0.0285 & 0.2208 & 0.413015 \tabularnewline
28 & -0.082317 & -0.6376 & 0.263072 \tabularnewline
29 & -0.02281 & -0.1767 & 0.430175 \tabularnewline
30 & 0.045077 & 0.3492 & 0.364095 \tabularnewline
31 & -0.020385 & -0.1579 & 0.437533 \tabularnewline
32 & -0.032621 & -0.2527 & 0.400688 \tabularnewline
33 & -0.018916 & -0.1465 & 0.442 \tabularnewline
34 & -0.149348 & -1.1568 & 0.12596 \tabularnewline
35 & -0.035136 & -0.2722 & 0.393214 \tabularnewline
36 & 0.160848 & 1.2459 & 0.108818 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34209&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]0.102513[/C][C]0.7941[/C][C]0.215145[/C][/ROW]
[ROW][C]2[/C][C]-0.102028[/C][C]-0.7903[/C][C]0.21623[/C][/ROW]
[ROW][C]3[/C][C]0.228519[/C][C]1.7701[/C][C]0.040896[/C][/ROW]
[ROW][C]4[/C][C]0.053331[/C][C]0.4131[/C][C]0.340503[/C][/ROW]
[ROW][C]5[/C][C]0.127185[/C][C]0.9852[/C][C]0.164249[/C][/ROW]
[ROW][C]6[/C][C]0.227823[/C][C]1.7647[/C][C]0.041351[/C][/ROW]
[ROW][C]7[/C][C]0.070332[/C][C]0.5448[/C][C]0.29396[/C][/ROW]
[ROW][C]8[/C][C]0.054266[/C][C]0.4203[/C][C]0.337868[/C][/ROW]
[ROW][C]9[/C][C]0.165545[/C][C]1.2823[/C][C]0.102334[/C][/ROW]
[ROW][C]10[/C][C]-0.186272[/C][C]-1.4429[/C][C]0.077131[/C][/ROW]
[ROW][C]11[/C][C]0.031098[/C][C]0.2409[/C][C]0.405234[/C][/ROW]
[ROW][C]12[/C][C]0.565409[/C][C]4.3796[/C][C]2.4e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.037461[/C][C]-0.2902[/C][C]0.386342[/C][/ROW]
[ROW][C]14[/C][C]-0.244997[/C][C]-1.8977[/C][C]0.031272[/C][/ROW]
[ROW][C]15[/C][C]0.067304[/C][C]0.5213[/C][C]0.302026[/C][/ROW]
[ROW][C]16[/C][C]-0.054954[/C][C]-0.4257[/C][C]0.335934[/C][/ROW]
[ROW][C]17[/C][C]-0.023036[/C][C]-0.1784[/C][C]0.429491[/C][/ROW]
[ROW][C]18[/C][C]0.059774[/C][C]0.463[/C][C]0.322516[/C][/ROW]
[ROW][C]19[/C][C]-0.006792[/C][C]-0.0526[/C][C]0.479109[/C][/ROW]
[ROW][C]20[/C][C]-0.060872[/C][C]-0.4715[/C][C]0.319493[/C][/ROW]
[ROW][C]21[/C][C]0.081897[/C][C]0.6344[/C][C]0.264126[/C][/ROW]
[ROW][C]22[/C][C]-0.234008[/C][C]-1.8126[/C][C]0.037447[/C][/ROW]
[ROW][C]23[/C][C]-0.012885[/C][C]-0.0998[/C][C]0.460416[/C][/ROW]
[ROW][C]24[/C][C]0.346704[/C][C]2.6856[/C][C]0.004675[/C][/ROW]
[ROW][C]25[/C][C]-0.065447[/C][C]-0.5069[/C][C]0.307025[/C][/ROW]
[ROW][C]26[/C][C]-0.153126[/C][C]-1.1861[/C][C]0.120128[/C][/ROW]
[ROW][C]27[/C][C]0.0285[/C][C]0.2208[/C][C]0.413015[/C][/ROW]
[ROW][C]28[/C][C]-0.082317[/C][C]-0.6376[/C][C]0.263072[/C][/ROW]
[ROW][C]29[/C][C]-0.02281[/C][C]-0.1767[/C][C]0.430175[/C][/ROW]
[ROW][C]30[/C][C]0.045077[/C][C]0.3492[/C][C]0.364095[/C][/ROW]
[ROW][C]31[/C][C]-0.020385[/C][C]-0.1579[/C][C]0.437533[/C][/ROW]
[ROW][C]32[/C][C]-0.032621[/C][C]-0.2527[/C][C]0.400688[/C][/ROW]
[ROW][C]33[/C][C]-0.018916[/C][C]-0.1465[/C][C]0.442[/C][/ROW]
[ROW][C]34[/C][C]-0.149348[/C][C]-1.1568[/C][C]0.12596[/C][/ROW]
[ROW][C]35[/C][C]-0.035136[/C][C]-0.2722[/C][C]0.393214[/C][/ROW]
[ROW][C]36[/C][C]0.160848[/C][C]1.2459[/C][C]0.108818[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34209&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
10.1025130.79410.215145
2-0.102028-0.79030.21623
30.2285191.77010.040896
40.0533310.41310.340503
50.1271850.98520.164249
60.2278231.76470.041351
70.0703320.54480.29396
80.0542660.42030.337868
90.1655451.28230.102334
10-0.186272-1.44290.077131
110.0310980.24090.405234
120.5654094.37962.4e-05
13-0.037461-0.29020.386342
14-0.244997-1.89770.031272
150.0673040.52130.302026
16-0.054954-0.42570.335934
17-0.023036-0.17840.429491
180.0597740.4630.322516
19-0.006792-0.05260.479109
20-0.060872-0.47150.319493
210.0818970.63440.264126
22-0.234008-1.81260.037447
23-0.012885-0.09980.460416
240.3467042.68560.004675
25-0.065447-0.50690.307025
26-0.153126-1.18610.120128
270.02850.22080.413015
28-0.082317-0.63760.263072
29-0.02281-0.17670.430175
300.0450770.34920.364095
31-0.020385-0.15790.437533
32-0.032621-0.25270.400688
33-0.018916-0.14650.442
34-0.149348-1.15680.12596
35-0.035136-0.27220.393214
360.1608481.24590.108818






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1025130.79410.215145
2-0.113732-0.8810.190926
30.2578361.99720.025173
4-0.022483-0.17420.431165
50.1992931.54370.063958
60.1448541.1220.133158
70.0717750.5560.290151
80.0304270.23570.40724
90.1000050.77460.220799
10-0.301666-2.33670.011406
110.0750770.58150.281526
120.462993.58630.000337
13-0.148268-1.14850.127664
14-0.263868-2.04390.02268
15-0.078017-0.60430.273955
16-0.033322-0.25810.398602
17-0.084127-0.65160.25856
18-0.089296-0.69170.245902
190.1361991.0550.14783
20-0.080838-0.62620.266789
210.0886080.68640.247567
22-0.044604-0.34550.365464
230.119950.92910.178273
24-0.054022-0.41850.338555
250.0841060.65150.258612
260.1086480.84160.201682
27-0.034851-0.270.39406
28-0.154185-1.19430.118528
290.0490020.37960.352803
30-0.037404-0.28970.386512
31-0.051833-0.40150.34474
32-0.063993-0.49570.310963
33-0.069864-0.54120.295198
340.0575020.44540.328814
35-0.067322-0.52150.301977
36-0.079579-0.61640.269977

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.102513 & 0.7941 & 0.215145 \tabularnewline
2 & -0.113732 & -0.881 & 0.190926 \tabularnewline
3 & 0.257836 & 1.9972 & 0.025173 \tabularnewline
4 & -0.022483 & -0.1742 & 0.431165 \tabularnewline
5 & 0.199293 & 1.5437 & 0.063958 \tabularnewline
6 & 0.144854 & 1.122 & 0.133158 \tabularnewline
7 & 0.071775 & 0.556 & 0.290151 \tabularnewline
8 & 0.030427 & 0.2357 & 0.40724 \tabularnewline
9 & 0.100005 & 0.7746 & 0.220799 \tabularnewline
10 & -0.301666 & -2.3367 & 0.011406 \tabularnewline
11 & 0.075077 & 0.5815 & 0.281526 \tabularnewline
12 & 0.46299 & 3.5863 & 0.000337 \tabularnewline
13 & -0.148268 & -1.1485 & 0.127664 \tabularnewline
14 & -0.263868 & -2.0439 & 0.02268 \tabularnewline
15 & -0.078017 & -0.6043 & 0.273955 \tabularnewline
16 & -0.033322 & -0.2581 & 0.398602 \tabularnewline
17 & -0.084127 & -0.6516 & 0.25856 \tabularnewline
18 & -0.089296 & -0.6917 & 0.245902 \tabularnewline
19 & 0.136199 & 1.055 & 0.14783 \tabularnewline
20 & -0.080838 & -0.6262 & 0.266789 \tabularnewline
21 & 0.088608 & 0.6864 & 0.247567 \tabularnewline
22 & -0.044604 & -0.3455 & 0.365464 \tabularnewline
23 & 0.11995 & 0.9291 & 0.178273 \tabularnewline
24 & -0.054022 & -0.4185 & 0.338555 \tabularnewline
25 & 0.084106 & 0.6515 & 0.258612 \tabularnewline
26 & 0.108648 & 0.8416 & 0.201682 \tabularnewline
27 & -0.034851 & -0.27 & 0.39406 \tabularnewline
28 & -0.154185 & -1.1943 & 0.118528 \tabularnewline
29 & 0.049002 & 0.3796 & 0.352803 \tabularnewline
30 & -0.037404 & -0.2897 & 0.386512 \tabularnewline
31 & -0.051833 & -0.4015 & 0.34474 \tabularnewline
32 & -0.063993 & -0.4957 & 0.310963 \tabularnewline
33 & -0.069864 & -0.5412 & 0.295198 \tabularnewline
34 & 0.057502 & 0.4454 & 0.328814 \tabularnewline
35 & -0.067322 & -0.5215 & 0.301977 \tabularnewline
36 & -0.079579 & -0.6164 & 0.269977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34209&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]0.102513[/C][C]0.7941[/C][C]0.215145[/C][/ROW]
[ROW][C]2[/C][C]-0.113732[/C][C]-0.881[/C][C]0.190926[/C][/ROW]
[ROW][C]3[/C][C]0.257836[/C][C]1.9972[/C][C]0.025173[/C][/ROW]
[ROW][C]4[/C][C]-0.022483[/C][C]-0.1742[/C][C]0.431165[/C][/ROW]
[ROW][C]5[/C][C]0.199293[/C][C]1.5437[/C][C]0.063958[/C][/ROW]
[ROW][C]6[/C][C]0.144854[/C][C]1.122[/C][C]0.133158[/C][/ROW]
[ROW][C]7[/C][C]0.071775[/C][C]0.556[/C][C]0.290151[/C][/ROW]
[ROW][C]8[/C][C]0.030427[/C][C]0.2357[/C][C]0.40724[/C][/ROW]
[ROW][C]9[/C][C]0.100005[/C][C]0.7746[/C][C]0.220799[/C][/ROW]
[ROW][C]10[/C][C]-0.301666[/C][C]-2.3367[/C][C]0.011406[/C][/ROW]
[ROW][C]11[/C][C]0.075077[/C][C]0.5815[/C][C]0.281526[/C][/ROW]
[ROW][C]12[/C][C]0.46299[/C][C]3.5863[/C][C]0.000337[/C][/ROW]
[ROW][C]13[/C][C]-0.148268[/C][C]-1.1485[/C][C]0.127664[/C][/ROW]
[ROW][C]14[/C][C]-0.263868[/C][C]-2.0439[/C][C]0.02268[/C][/ROW]
[ROW][C]15[/C][C]-0.078017[/C][C]-0.6043[/C][C]0.273955[/C][/ROW]
[ROW][C]16[/C][C]-0.033322[/C][C]-0.2581[/C][C]0.398602[/C][/ROW]
[ROW][C]17[/C][C]-0.084127[/C][C]-0.6516[/C][C]0.25856[/C][/ROW]
[ROW][C]18[/C][C]-0.089296[/C][C]-0.6917[/C][C]0.245902[/C][/ROW]
[ROW][C]19[/C][C]0.136199[/C][C]1.055[/C][C]0.14783[/C][/ROW]
[ROW][C]20[/C][C]-0.080838[/C][C]-0.6262[/C][C]0.266789[/C][/ROW]
[ROW][C]21[/C][C]0.088608[/C][C]0.6864[/C][C]0.247567[/C][/ROW]
[ROW][C]22[/C][C]-0.044604[/C][C]-0.3455[/C][C]0.365464[/C][/ROW]
[ROW][C]23[/C][C]0.11995[/C][C]0.9291[/C][C]0.178273[/C][/ROW]
[ROW][C]24[/C][C]-0.054022[/C][C]-0.4185[/C][C]0.338555[/C][/ROW]
[ROW][C]25[/C][C]0.084106[/C][C]0.6515[/C][C]0.258612[/C][/ROW]
[ROW][C]26[/C][C]0.108648[/C][C]0.8416[/C][C]0.201682[/C][/ROW]
[ROW][C]27[/C][C]-0.034851[/C][C]-0.27[/C][C]0.39406[/C][/ROW]
[ROW][C]28[/C][C]-0.154185[/C][C]-1.1943[/C][C]0.118528[/C][/ROW]
[ROW][C]29[/C][C]0.049002[/C][C]0.3796[/C][C]0.352803[/C][/ROW]
[ROW][C]30[/C][C]-0.037404[/C][C]-0.2897[/C][C]0.386512[/C][/ROW]
[ROW][C]31[/C][C]-0.051833[/C][C]-0.4015[/C][C]0.34474[/C][/ROW]
[ROW][C]32[/C][C]-0.063993[/C][C]-0.4957[/C][C]0.310963[/C][/ROW]
[ROW][C]33[/C][C]-0.069864[/C][C]-0.5412[/C][C]0.295198[/C][/ROW]
[ROW][C]34[/C][C]0.057502[/C][C]0.4454[/C][C]0.328814[/C][/ROW]
[ROW][C]35[/C][C]-0.067322[/C][C]-0.5215[/C][C]0.301977[/C][/ROW]
[ROW][C]36[/C][C]-0.079579[/C][C]-0.6164[/C][C]0.269977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34209&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34209&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
10.1025130.79410.215145
2-0.113732-0.8810.190926
30.2578361.99720.025173
4-0.022483-0.17420.431165
50.1992931.54370.063958
60.1448541.1220.133158
70.0717750.5560.290151
80.0304270.23570.40724
90.1000050.77460.220799
10-0.301666-2.33670.011406
110.0750770.58150.281526
120.462993.58630.000337
13-0.148268-1.14850.127664
14-0.263868-2.04390.02268
15-0.078017-0.60430.273955
16-0.033322-0.25810.398602
17-0.084127-0.65160.25856
18-0.089296-0.69170.245902
190.1361991.0550.14783
20-0.080838-0.62620.266789
210.0886080.68640.247567
22-0.044604-0.34550.365464
230.119950.92910.178273
24-0.054022-0.41850.338555
250.0841060.65150.258612
260.1086480.84160.201682
27-0.034851-0.270.39406
28-0.154185-1.19430.118528
290.0490020.37960.352803
30-0.037404-0.28970.386512
31-0.051833-0.40150.34474
32-0.063993-0.49570.310963
33-0.069864-0.54120.295198
340.0575020.44540.328814
35-0.067322-0.52150.301977
36-0.079579-0.61640.269977


Figures (Output of Computation)

Input Parameters & R Code

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