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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, 26 Nov 2009 13:40:39 -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/Nov/26/t1259268102iog0uahmm81lkqb.htm/, Retrieved Wed, 11 Feb 2026 19:58:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60387, Retrieved Wed, 11 Feb 2026 19:58:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact398

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS8] [2009-11-24 18:55:10] [b8b64ced21f32e31669b267b64eede7f]
-   P             [(Partial) Autocorrelation Function] [WS8] [2009-11-26 20:40:39] [9a1fef436e1d399a5ecd6808bfbd8489] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3922
3759
4138
4634
3995
4308
4143
4429
5219
4929
5755
5592
4163
4962
5208
4755
4491
5732
5731
5040
6102
4904
5369
5578
4619
4731
5011
5299
4146
4625
4736
4219
5116
4205
4121
5103
4300
4578
3809
5526
4247
3830
4394
4826
4409
4569
4106
4794
3914
3793
4405
4022
4100
4788
3163
3585
3903
4178
3863
4187

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=60387&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=60387&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60387&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
1-0.4023-2.7580.004129
2-0.283584-1.94420.028938
30.284411.94980.028589
40.0016110.0110.495617
5-0.11238-0.77040.222447
6-0.027384-0.18770.425945
70.1523711.04460.150774
8-0.046572-0.31930.375463
9-0.170663-1.170.123948
100.2662151.82510.037174
11-0.093095-0.63820.263212
12-0.231322-1.58590.059738
130.2823381.93560.029472
14-0.085947-0.58920.279266
15-0.080273-0.55030.292351
160.0160830.11030.456335
170.0343250.23530.407491
18-0.067438-0.46230.322989
190.0981070.67260.252251
20-0.044895-0.30780.379803
21-0.08297-0.56880.286095
220.0923930.63340.264767
230.112160.76890.222891
24-0.254424-1.74420.043827
250.061510.42170.337587
260.2180451.49480.07082
27-0.128128-0.87840.192098
28-0.095631-0.65560.257634
290.1201010.82340.207228
300.0453650.3110.378586
31-0.180486-1.23730.111052
320.10670.73150.234053
330.0530740.36390.358797
34-0.084175-0.57710.283322
350.0198950.13640.446047
360.0787230.53970.295978

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.4023 & -2.758 & 0.004129 \tabularnewline
2 & -0.283584 & -1.9442 & 0.028938 \tabularnewline
3 & 0.28441 & 1.9498 & 0.028589 \tabularnewline
4 & 0.001611 & 0.011 & 0.495617 \tabularnewline
5 & -0.11238 & -0.7704 & 0.222447 \tabularnewline
6 & -0.027384 & -0.1877 & 0.425945 \tabularnewline
7 & 0.152371 & 1.0446 & 0.150774 \tabularnewline
8 & -0.046572 & -0.3193 & 0.375463 \tabularnewline
9 & -0.170663 & -1.17 & 0.123948 \tabularnewline
10 & 0.266215 & 1.8251 & 0.037174 \tabularnewline
11 & -0.093095 & -0.6382 & 0.263212 \tabularnewline
12 & -0.231322 & -1.5859 & 0.059738 \tabularnewline
13 & 0.282338 & 1.9356 & 0.029472 \tabularnewline
14 & -0.085947 & -0.5892 & 0.279266 \tabularnewline
15 & -0.080273 & -0.5503 & 0.292351 \tabularnewline
16 & 0.016083 & 0.1103 & 0.456335 \tabularnewline
17 & 0.034325 & 0.2353 & 0.407491 \tabularnewline
18 & -0.067438 & -0.4623 & 0.322989 \tabularnewline
19 & 0.098107 & 0.6726 & 0.252251 \tabularnewline
20 & -0.044895 & -0.3078 & 0.379803 \tabularnewline
21 & -0.08297 & -0.5688 & 0.286095 \tabularnewline
22 & 0.092393 & 0.6334 & 0.264767 \tabularnewline
23 & 0.11216 & 0.7689 & 0.222891 \tabularnewline
24 & -0.254424 & -1.7442 & 0.043827 \tabularnewline
25 & 0.06151 & 0.4217 & 0.337587 \tabularnewline
26 & 0.218045 & 1.4948 & 0.07082 \tabularnewline
27 & -0.128128 & -0.8784 & 0.192098 \tabularnewline
28 & -0.095631 & -0.6556 & 0.257634 \tabularnewline
29 & 0.120101 & 0.8234 & 0.207228 \tabularnewline
30 & 0.045365 & 0.311 & 0.378586 \tabularnewline
31 & -0.180486 & -1.2373 & 0.111052 \tabularnewline
32 & 0.1067 & 0.7315 & 0.234053 \tabularnewline
33 & 0.053074 & 0.3639 & 0.358797 \tabularnewline
34 & -0.084175 & -0.5771 & 0.283322 \tabularnewline
35 & 0.019895 & 0.1364 & 0.446047 \tabularnewline
36 & 0.078723 & 0.5397 & 0.295978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60387&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]-0.4023[/C][C]-2.758[/C][C]0.004129[/C][/ROW]
[ROW][C]2[/C][C]-0.283584[/C][C]-1.9442[/C][C]0.028938[/C][/ROW]
[ROW][C]3[/C][C]0.28441[/C][C]1.9498[/C][C]0.028589[/C][/ROW]
[ROW][C]4[/C][C]0.001611[/C][C]0.011[/C][C]0.495617[/C][/ROW]
[ROW][C]5[/C][C]-0.11238[/C][C]-0.7704[/C][C]0.222447[/C][/ROW]
[ROW][C]6[/C][C]-0.027384[/C][C]-0.1877[/C][C]0.425945[/C][/ROW]
[ROW][C]7[/C][C]0.152371[/C][C]1.0446[/C][C]0.150774[/C][/ROW]
[ROW][C]8[/C][C]-0.046572[/C][C]-0.3193[/C][C]0.375463[/C][/ROW]
[ROW][C]9[/C][C]-0.170663[/C][C]-1.17[/C][C]0.123948[/C][/ROW]
[ROW][C]10[/C][C]0.266215[/C][C]1.8251[/C][C]0.037174[/C][/ROW]
[ROW][C]11[/C][C]-0.093095[/C][C]-0.6382[/C][C]0.263212[/C][/ROW]
[ROW][C]12[/C][C]-0.231322[/C][C]-1.5859[/C][C]0.059738[/C][/ROW]
[ROW][C]13[/C][C]0.282338[/C][C]1.9356[/C][C]0.029472[/C][/ROW]
[ROW][C]14[/C][C]-0.085947[/C][C]-0.5892[/C][C]0.279266[/C][/ROW]
[ROW][C]15[/C][C]-0.080273[/C][C]-0.5503[/C][C]0.292351[/C][/ROW]
[ROW][C]16[/C][C]0.016083[/C][C]0.1103[/C][C]0.456335[/C][/ROW]
[ROW][C]17[/C][C]0.034325[/C][C]0.2353[/C][C]0.407491[/C][/ROW]
[ROW][C]18[/C][C]-0.067438[/C][C]-0.4623[/C][C]0.322989[/C][/ROW]
[ROW][C]19[/C][C]0.098107[/C][C]0.6726[/C][C]0.252251[/C][/ROW]
[ROW][C]20[/C][C]-0.044895[/C][C]-0.3078[/C][C]0.379803[/C][/ROW]
[ROW][C]21[/C][C]-0.08297[/C][C]-0.5688[/C][C]0.286095[/C][/ROW]
[ROW][C]22[/C][C]0.092393[/C][C]0.6334[/C][C]0.264767[/C][/ROW]
[ROW][C]23[/C][C]0.11216[/C][C]0.7689[/C][C]0.222891[/C][/ROW]
[ROW][C]24[/C][C]-0.254424[/C][C]-1.7442[/C][C]0.043827[/C][/ROW]
[ROW][C]25[/C][C]0.06151[/C][C]0.4217[/C][C]0.337587[/C][/ROW]
[ROW][C]26[/C][C]0.218045[/C][C]1.4948[/C][C]0.07082[/C][/ROW]
[ROW][C]27[/C][C]-0.128128[/C][C]-0.8784[/C][C]0.192098[/C][/ROW]
[ROW][C]28[/C][C]-0.095631[/C][C]-0.6556[/C][C]0.257634[/C][/ROW]
[ROW][C]29[/C][C]0.120101[/C][C]0.8234[/C][C]0.207228[/C][/ROW]
[ROW][C]30[/C][C]0.045365[/C][C]0.311[/C][C]0.378586[/C][/ROW]
[ROW][C]31[/C][C]-0.180486[/C][C]-1.2373[/C][C]0.111052[/C][/ROW]
[ROW][C]32[/C][C]0.1067[/C][C]0.7315[/C][C]0.234053[/C][/ROW]
[ROW][C]33[/C][C]0.053074[/C][C]0.3639[/C][C]0.358797[/C][/ROW]
[ROW][C]34[/C][C]-0.084175[/C][C]-0.5771[/C][C]0.283322[/C][/ROW]
[ROW][C]35[/C][C]0.019895[/C][C]0.1364[/C][C]0.446047[/C][/ROW]
[ROW][C]36[/C][C]0.078723[/C][C]0.5397[/C][C]0.295978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60387&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60387&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
1-0.4023-2.7580.004129
2-0.283584-1.94420.028938
30.284411.94980.028589
40.0016110.0110.495617
5-0.11238-0.77040.222447
6-0.027384-0.18770.425945
70.1523711.04460.150774
8-0.046572-0.31930.375463
9-0.170663-1.170.123948
100.2662151.82510.037174
11-0.093095-0.63820.263212
12-0.231322-1.58590.059738
130.2823381.93560.029472
14-0.085947-0.58920.279266
15-0.080273-0.55030.292351
160.0160830.11030.456335
170.0343250.23530.407491
18-0.067438-0.46230.322989
190.0981070.67260.252251
20-0.044895-0.30780.379803
21-0.08297-0.56880.286095
220.0923930.63340.264767
230.112160.76890.222891
24-0.254424-1.74420.043827
250.061510.42170.337587
260.2180451.49480.07082
27-0.128128-0.87840.192098
28-0.095631-0.65560.257634
290.1201010.82340.207228
300.0453650.3110.378586
31-0.180486-1.23730.111052
320.10670.73150.234053
330.0530740.36390.358797
34-0.084175-0.57710.283322
350.0198950.13640.446047
360.0787230.53970.295978






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.4023-2.7580.004129
2-0.53144-3.64340.000335
3-0.173093-1.18670.120661
4-0.081568-0.55920.28934
5-0.022807-0.15640.438211
6-0.128583-0.88150.19126
70.0387260.26550.395895
80.0461850.31660.376465
9-0.115699-0.79320.215826
100.1485561.01840.15684
110.0311240.21340.415979
12-0.178955-1.22690.112994
130.0165660.11360.455031
14-0.123151-0.84430.201395
15-0.041695-0.28580.388127
16-0.127825-0.87630.192655
17-0.143179-0.98160.165666
18-0.26515-1.81780.037738
190.05730.39280.34811
20-0.098872-0.67780.250601
21-0.159876-1.09610.139319
22-0.007967-0.05460.478336
230.1154510.79150.216317
24-0.165919-1.13750.13055
25-0.073241-0.50210.308965
260.0275180.18870.425589
270.0533350.36560.358134
280.015380.10540.458236
29-0.042116-0.28870.387029
30-0.041331-0.28340.389076
31-0.062586-0.42910.334916
32-0.104285-0.71490.239091
33-0.201443-1.3810.086901
34-0.039151-0.26840.39478
350.0234410.16070.436508
36-0.09161-0.6280.266507

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.4023 & -2.758 & 0.004129 \tabularnewline
2 & -0.53144 & -3.6434 & 0.000335 \tabularnewline
3 & -0.173093 & -1.1867 & 0.120661 \tabularnewline
4 & -0.081568 & -0.5592 & 0.28934 \tabularnewline
5 & -0.022807 & -0.1564 & 0.438211 \tabularnewline
6 & -0.128583 & -0.8815 & 0.19126 \tabularnewline
7 & 0.038726 & 0.2655 & 0.395895 \tabularnewline
8 & 0.046185 & 0.3166 & 0.376465 \tabularnewline
9 & -0.115699 & -0.7932 & 0.215826 \tabularnewline
10 & 0.148556 & 1.0184 & 0.15684 \tabularnewline
11 & 0.031124 & 0.2134 & 0.415979 \tabularnewline
12 & -0.178955 & -1.2269 & 0.112994 \tabularnewline
13 & 0.016566 & 0.1136 & 0.455031 \tabularnewline
14 & -0.123151 & -0.8443 & 0.201395 \tabularnewline
15 & -0.041695 & -0.2858 & 0.388127 \tabularnewline
16 & -0.127825 & -0.8763 & 0.192655 \tabularnewline
17 & -0.143179 & -0.9816 & 0.165666 \tabularnewline
18 & -0.26515 & -1.8178 & 0.037738 \tabularnewline
19 & 0.0573 & 0.3928 & 0.34811 \tabularnewline
20 & -0.098872 & -0.6778 & 0.250601 \tabularnewline
21 & -0.159876 & -1.0961 & 0.139319 \tabularnewline
22 & -0.007967 & -0.0546 & 0.478336 \tabularnewline
23 & 0.115451 & 0.7915 & 0.216317 \tabularnewline
24 & -0.165919 & -1.1375 & 0.13055 \tabularnewline
25 & -0.073241 & -0.5021 & 0.308965 \tabularnewline
26 & 0.027518 & 0.1887 & 0.425589 \tabularnewline
27 & 0.053335 & 0.3656 & 0.358134 \tabularnewline
28 & 0.01538 & 0.1054 & 0.458236 \tabularnewline
29 & -0.042116 & -0.2887 & 0.387029 \tabularnewline
30 & -0.041331 & -0.2834 & 0.389076 \tabularnewline
31 & -0.062586 & -0.4291 & 0.334916 \tabularnewline
32 & -0.104285 & -0.7149 & 0.239091 \tabularnewline
33 & -0.201443 & -1.381 & 0.086901 \tabularnewline
34 & -0.039151 & -0.2684 & 0.39478 \tabularnewline
35 & 0.023441 & 0.1607 & 0.436508 \tabularnewline
36 & -0.09161 & -0.628 & 0.266507 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60387&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]-0.4023[/C][C]-2.758[/C][C]0.004129[/C][/ROW]
[ROW][C]2[/C][C]-0.53144[/C][C]-3.6434[/C][C]0.000335[/C][/ROW]
[ROW][C]3[/C][C]-0.173093[/C][C]-1.1867[/C][C]0.120661[/C][/ROW]
[ROW][C]4[/C][C]-0.081568[/C][C]-0.5592[/C][C]0.28934[/C][/ROW]
[ROW][C]5[/C][C]-0.022807[/C][C]-0.1564[/C][C]0.438211[/C][/ROW]
[ROW][C]6[/C][C]-0.128583[/C][C]-0.8815[/C][C]0.19126[/C][/ROW]
[ROW][C]7[/C][C]0.038726[/C][C]0.2655[/C][C]0.395895[/C][/ROW]
[ROW][C]8[/C][C]0.046185[/C][C]0.3166[/C][C]0.376465[/C][/ROW]
[ROW][C]9[/C][C]-0.115699[/C][C]-0.7932[/C][C]0.215826[/C][/ROW]
[ROW][C]10[/C][C]0.148556[/C][C]1.0184[/C][C]0.15684[/C][/ROW]
[ROW][C]11[/C][C]0.031124[/C][C]0.2134[/C][C]0.415979[/C][/ROW]
[ROW][C]12[/C][C]-0.178955[/C][C]-1.2269[/C][C]0.112994[/C][/ROW]
[ROW][C]13[/C][C]0.016566[/C][C]0.1136[/C][C]0.455031[/C][/ROW]
[ROW][C]14[/C][C]-0.123151[/C][C]-0.8443[/C][C]0.201395[/C][/ROW]
[ROW][C]15[/C][C]-0.041695[/C][C]-0.2858[/C][C]0.388127[/C][/ROW]
[ROW][C]16[/C][C]-0.127825[/C][C]-0.8763[/C][C]0.192655[/C][/ROW]
[ROW][C]17[/C][C]-0.143179[/C][C]-0.9816[/C][C]0.165666[/C][/ROW]
[ROW][C]18[/C][C]-0.26515[/C][C]-1.8178[/C][C]0.037738[/C][/ROW]
[ROW][C]19[/C][C]0.0573[/C][C]0.3928[/C][C]0.34811[/C][/ROW]
[ROW][C]20[/C][C]-0.098872[/C][C]-0.6778[/C][C]0.250601[/C][/ROW]
[ROW][C]21[/C][C]-0.159876[/C][C]-1.0961[/C][C]0.139319[/C][/ROW]
[ROW][C]22[/C][C]-0.007967[/C][C]-0.0546[/C][C]0.478336[/C][/ROW]
[ROW][C]23[/C][C]0.115451[/C][C]0.7915[/C][C]0.216317[/C][/ROW]
[ROW][C]24[/C][C]-0.165919[/C][C]-1.1375[/C][C]0.13055[/C][/ROW]
[ROW][C]25[/C][C]-0.073241[/C][C]-0.5021[/C][C]0.308965[/C][/ROW]
[ROW][C]26[/C][C]0.027518[/C][C]0.1887[/C][C]0.425589[/C][/ROW]
[ROW][C]27[/C][C]0.053335[/C][C]0.3656[/C][C]0.358134[/C][/ROW]
[ROW][C]28[/C][C]0.01538[/C][C]0.1054[/C][C]0.458236[/C][/ROW]
[ROW][C]29[/C][C]-0.042116[/C][C]-0.2887[/C][C]0.387029[/C][/ROW]
[ROW][C]30[/C][C]-0.041331[/C][C]-0.2834[/C][C]0.389076[/C][/ROW]
[ROW][C]31[/C][C]-0.062586[/C][C]-0.4291[/C][C]0.334916[/C][/ROW]
[ROW][C]32[/C][C]-0.104285[/C][C]-0.7149[/C][C]0.239091[/C][/ROW]
[ROW][C]33[/C][C]-0.201443[/C][C]-1.381[/C][C]0.086901[/C][/ROW]
[ROW][C]34[/C][C]-0.039151[/C][C]-0.2684[/C][C]0.39478[/C][/ROW]
[ROW][C]35[/C][C]0.023441[/C][C]0.1607[/C][C]0.436508[/C][/ROW]
[ROW][C]36[/C][C]-0.09161[/C][C]-0.628[/C][C]0.266507[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60387&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60387&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
1-0.4023-2.7580.004129
2-0.53144-3.64340.000335
3-0.173093-1.18670.120661
4-0.081568-0.55920.28934
5-0.022807-0.15640.438211
6-0.128583-0.88150.19126
70.0387260.26550.395895
80.0461850.31660.376465
9-0.115699-0.79320.215826
100.1485561.01840.15684
110.0311240.21340.415979
12-0.178955-1.22690.112994
130.0165660.11360.455031
14-0.123151-0.84430.201395
15-0.041695-0.28580.388127
16-0.127825-0.87630.192655
17-0.143179-0.98160.165666
18-0.26515-1.81780.037738
190.05730.39280.34811
20-0.098872-0.67780.250601
21-0.159876-1.09610.139319
22-0.007967-0.05460.478336
230.1154510.79150.216317
24-0.165919-1.13750.13055
25-0.073241-0.50210.308965
260.0275180.18870.425589
270.0533350.36560.358134
280.015380.10540.458236
29-0.042116-0.28870.387029
30-0.041331-0.28340.389076
31-0.062586-0.42910.334916
32-0.104285-0.71490.239091
33-0.201443-1.3810.086901
34-0.039151-0.26840.39478
350.0234410.16070.436508
36-0.09161-0.6280.266507


Figures (Output of Computation)

Input Parameters & R Code

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