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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, 28 Nov 2009 07:08:05 -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/28/t1259417321x437wo47ygzooe7.htm/, Retrieved Wed, 11 Feb 2026 02:08:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61469, Retrieved Wed, 11 Feb 2026 02:08:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact351

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]
-   PD          [(Partial) Autocorrelation Function] [] [2009-11-28 14:08:05] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-11-28 14:11:22] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95,5
76,7
79,4
55,2
60
64,8
82,3
210,5
106
80,8
97,3
189,5
90
69,3
87,3
57,4
56,2
61,6
77,7
177,2
97,6
81,6
96,8
191,3
106
75,1
72
63,5
57,4
62,3
79,4
178,1
109,3
85,2
102,7
193,7
108,4
73,4
85,9
58,5
58,6
62,7
77,5
180,5
102,2
82,6
97,8
197,8
93,8
72,4
77,7
58,7
53,1
64,3
76,4
188,4
105,5
79,8
96,1
202,5

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=61469&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=61469&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61469&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
10.1077210.74630.229559
20.0757190.52460.30114
30.0742650.51450.304625
40.0436170.30220.381908
5-0.281052-1.94720.028688
60.0364440.25250.400868
70.172291.19370.119239
8-0.025657-0.17780.429831
90.0632470.43820.331608
10-0.027357-0.18950.425236
11-0.041268-0.28590.388089
12-0.279046-1.93330.029556
13-0.059408-0.41160.341236
14-0.090953-0.63010.265796
15-0.130959-0.90730.184387
16-0.140358-0.97240.167856
17-0.043721-0.30290.381634
18-0.012973-0.08990.46438
19-0.172856-1.19760.11848
20-0.025414-0.17610.430488
21-0.072017-0.49890.310047
220.0294270.20390.419656
230.021920.15190.439964
24-0.001238-0.00860.496597
25-0.005853-0.04050.483912
260.032190.2230.412234
270.0418020.28960.38668
28-0.004426-0.03070.487832
290.1353240.93760.176585
300.013690.09480.462416
310.1591151.10240.137897
320.0818610.56720.286627
330.0306510.21240.416364
34-0.046865-0.32470.373413
350.0309680.21460.415513
36-0.096766-0.67040.252903

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.107721 & 0.7463 & 0.229559 \tabularnewline
2 & 0.075719 & 0.5246 & 0.30114 \tabularnewline
3 & 0.074265 & 0.5145 & 0.304625 \tabularnewline
4 & 0.043617 & 0.3022 & 0.381908 \tabularnewline
5 & -0.281052 & -1.9472 & 0.028688 \tabularnewline
6 & 0.036444 & 0.2525 & 0.400868 \tabularnewline
7 & 0.17229 & 1.1937 & 0.119239 \tabularnewline
8 & -0.025657 & -0.1778 & 0.429831 \tabularnewline
9 & 0.063247 & 0.4382 & 0.331608 \tabularnewline
10 & -0.027357 & -0.1895 & 0.425236 \tabularnewline
11 & -0.041268 & -0.2859 & 0.388089 \tabularnewline
12 & -0.279046 & -1.9333 & 0.029556 \tabularnewline
13 & -0.059408 & -0.4116 & 0.341236 \tabularnewline
14 & -0.090953 & -0.6301 & 0.265796 \tabularnewline
15 & -0.130959 & -0.9073 & 0.184387 \tabularnewline
16 & -0.140358 & -0.9724 & 0.167856 \tabularnewline
17 & -0.043721 & -0.3029 & 0.381634 \tabularnewline
18 & -0.012973 & -0.0899 & 0.46438 \tabularnewline
19 & -0.172856 & -1.1976 & 0.11848 \tabularnewline
20 & -0.025414 & -0.1761 & 0.430488 \tabularnewline
21 & -0.072017 & -0.4989 & 0.310047 \tabularnewline
22 & 0.029427 & 0.2039 & 0.419656 \tabularnewline
23 & 0.02192 & 0.1519 & 0.439964 \tabularnewline
24 & -0.001238 & -0.0086 & 0.496597 \tabularnewline
25 & -0.005853 & -0.0405 & 0.483912 \tabularnewline
26 & 0.03219 & 0.223 & 0.412234 \tabularnewline
27 & 0.041802 & 0.2896 & 0.38668 \tabularnewline
28 & -0.004426 & -0.0307 & 0.487832 \tabularnewline
29 & 0.135324 & 0.9376 & 0.176585 \tabularnewline
30 & 0.01369 & 0.0948 & 0.462416 \tabularnewline
31 & 0.159115 & 1.1024 & 0.137897 \tabularnewline
32 & 0.081861 & 0.5672 & 0.286627 \tabularnewline
33 & 0.030651 & 0.2124 & 0.416364 \tabularnewline
34 & -0.046865 & -0.3247 & 0.373413 \tabularnewline
35 & 0.030968 & 0.2146 & 0.415513 \tabularnewline
36 & -0.096766 & -0.6704 & 0.252903 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61469&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]0.107721[/C][C]0.7463[/C][C]0.229559[/C][/ROW]
[ROW][C]2[/C][C]0.075719[/C][C]0.5246[/C][C]0.30114[/C][/ROW]
[ROW][C]3[/C][C]0.074265[/C][C]0.5145[/C][C]0.304625[/C][/ROW]
[ROW][C]4[/C][C]0.043617[/C][C]0.3022[/C][C]0.381908[/C][/ROW]
[ROW][C]5[/C][C]-0.281052[/C][C]-1.9472[/C][C]0.028688[/C][/ROW]
[ROW][C]6[/C][C]0.036444[/C][C]0.2525[/C][C]0.400868[/C][/ROW]
[ROW][C]7[/C][C]0.17229[/C][C]1.1937[/C][C]0.119239[/C][/ROW]
[ROW][C]8[/C][C]-0.025657[/C][C]-0.1778[/C][C]0.429831[/C][/ROW]
[ROW][C]9[/C][C]0.063247[/C][C]0.4382[/C][C]0.331608[/C][/ROW]
[ROW][C]10[/C][C]-0.027357[/C][C]-0.1895[/C][C]0.425236[/C][/ROW]
[ROW][C]11[/C][C]-0.041268[/C][C]-0.2859[/C][C]0.388089[/C][/ROW]
[ROW][C]12[/C][C]-0.279046[/C][C]-1.9333[/C][C]0.029556[/C][/ROW]
[ROW][C]13[/C][C]-0.059408[/C][C]-0.4116[/C][C]0.341236[/C][/ROW]
[ROW][C]14[/C][C]-0.090953[/C][C]-0.6301[/C][C]0.265796[/C][/ROW]
[ROW][C]15[/C][C]-0.130959[/C][C]-0.9073[/C][C]0.184387[/C][/ROW]
[ROW][C]16[/C][C]-0.140358[/C][C]-0.9724[/C][C]0.167856[/C][/ROW]
[ROW][C]17[/C][C]-0.043721[/C][C]-0.3029[/C][C]0.381634[/C][/ROW]
[ROW][C]18[/C][C]-0.012973[/C][C]-0.0899[/C][C]0.46438[/C][/ROW]
[ROW][C]19[/C][C]-0.172856[/C][C]-1.1976[/C][C]0.11848[/C][/ROW]
[ROW][C]20[/C][C]-0.025414[/C][C]-0.1761[/C][C]0.430488[/C][/ROW]
[ROW][C]21[/C][C]-0.072017[/C][C]-0.4989[/C][C]0.310047[/C][/ROW]
[ROW][C]22[/C][C]0.029427[/C][C]0.2039[/C][C]0.419656[/C][/ROW]
[ROW][C]23[/C][C]0.02192[/C][C]0.1519[/C][C]0.439964[/C][/ROW]
[ROW][C]24[/C][C]-0.001238[/C][C]-0.0086[/C][C]0.496597[/C][/ROW]
[ROW][C]25[/C][C]-0.005853[/C][C]-0.0405[/C][C]0.483912[/C][/ROW]
[ROW][C]26[/C][C]0.03219[/C][C]0.223[/C][C]0.412234[/C][/ROW]
[ROW][C]27[/C][C]0.041802[/C][C]0.2896[/C][C]0.38668[/C][/ROW]
[ROW][C]28[/C][C]-0.004426[/C][C]-0.0307[/C][C]0.487832[/C][/ROW]
[ROW][C]29[/C][C]0.135324[/C][C]0.9376[/C][C]0.176585[/C][/ROW]
[ROW][C]30[/C][C]0.01369[/C][C]0.0948[/C][C]0.462416[/C][/ROW]
[ROW][C]31[/C][C]0.159115[/C][C]1.1024[/C][C]0.137897[/C][/ROW]
[ROW][C]32[/C][C]0.081861[/C][C]0.5672[/C][C]0.286627[/C][/ROW]
[ROW][C]33[/C][C]0.030651[/C][C]0.2124[/C][C]0.416364[/C][/ROW]
[ROW][C]34[/C][C]-0.046865[/C][C]-0.3247[/C][C]0.373413[/C][/ROW]
[ROW][C]35[/C][C]0.030968[/C][C]0.2146[/C][C]0.415513[/C][/ROW]
[ROW][C]36[/C][C]-0.096766[/C][C]-0.6704[/C][C]0.252903[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61469&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61469&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
10.1077210.74630.229559
20.0757190.52460.30114
30.0742650.51450.304625
40.0436170.30220.381908
5-0.281052-1.94720.028688
60.0364440.25250.400868
70.172291.19370.119239
8-0.025657-0.17780.429831
90.0632470.43820.331608
10-0.027357-0.18950.425236
11-0.041268-0.28590.388089
12-0.279046-1.93330.029556
13-0.059408-0.41160.341236
14-0.090953-0.63010.265796
15-0.130959-0.90730.184387
16-0.140358-0.97240.167856
17-0.043721-0.30290.381634
18-0.012973-0.08990.46438
19-0.172856-1.19760.11848
20-0.025414-0.17610.430488
21-0.072017-0.49890.310047
220.0294270.20390.419656
230.021920.15190.439964
24-0.001238-0.00860.496597
25-0.005853-0.04050.483912
260.032190.2230.412234
270.0418020.28960.38668
28-0.004426-0.03070.487832
290.1353240.93760.176585
300.013690.09480.462416
310.1591151.10240.137897
320.0818610.56720.286627
330.0306510.21240.416364
34-0.046865-0.32470.373413
350.0309680.21460.415513
36-0.096766-0.67040.252903






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1077210.74630.229559
20.0648680.44940.327577
30.0606050.41990.338222
40.0259530.17980.429031
5-0.302716-2.09730.02063
60.0955030.66170.255675
70.2198361.52310.067152
8-0.046917-0.32510.373277
90.0559120.38740.350098
10-0.183816-1.27350.104485
11-0.014152-0.0980.461152
12-0.168426-1.16690.12451
13-0.038806-0.26890.394598
14-0.008028-0.05560.477937
15-0.161682-1.12020.134108
16-0.127129-0.88080.191414
17-0.110241-0.76380.224371
180.0552370.38270.35182
19-0.09326-0.64610.260639
20-0.076488-0.52990.299304
21-0.090042-0.62380.267846
220.0351270.24340.40438
230.1198110.83010.205303
24-0.160284-1.11050.136163
25-0.055798-0.38660.350387
26-0.017165-0.11890.452918
270.0128720.08920.464656
280.0111690.07740.469321
29-0.009602-0.06650.473618
30-0.071357-0.49440.311647
310.0825410.57190.285043
320.0247520.17150.43228
33-0.065609-0.45460.32574
34-0.058619-0.40610.343228
35-0.04449-0.30820.379619
36-0.153609-1.06420.146274

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.107721 & 0.7463 & 0.229559 \tabularnewline
2 & 0.064868 & 0.4494 & 0.327577 \tabularnewline
3 & 0.060605 & 0.4199 & 0.338222 \tabularnewline
4 & 0.025953 & 0.1798 & 0.429031 \tabularnewline
5 & -0.302716 & -2.0973 & 0.02063 \tabularnewline
6 & 0.095503 & 0.6617 & 0.255675 \tabularnewline
7 & 0.219836 & 1.5231 & 0.067152 \tabularnewline
8 & -0.046917 & -0.3251 & 0.373277 \tabularnewline
9 & 0.055912 & 0.3874 & 0.350098 \tabularnewline
10 & -0.183816 & -1.2735 & 0.104485 \tabularnewline
11 & -0.014152 & -0.098 & 0.461152 \tabularnewline
12 & -0.168426 & -1.1669 & 0.12451 \tabularnewline
13 & -0.038806 & -0.2689 & 0.394598 \tabularnewline
14 & -0.008028 & -0.0556 & 0.477937 \tabularnewline
15 & -0.161682 & -1.1202 & 0.134108 \tabularnewline
16 & -0.127129 & -0.8808 & 0.191414 \tabularnewline
17 & -0.110241 & -0.7638 & 0.224371 \tabularnewline
18 & 0.055237 & 0.3827 & 0.35182 \tabularnewline
19 & -0.09326 & -0.6461 & 0.260639 \tabularnewline
20 & -0.076488 & -0.5299 & 0.299304 \tabularnewline
21 & -0.090042 & -0.6238 & 0.267846 \tabularnewline
22 & 0.035127 & 0.2434 & 0.40438 \tabularnewline
23 & 0.119811 & 0.8301 & 0.205303 \tabularnewline
24 & -0.160284 & -1.1105 & 0.136163 \tabularnewline
25 & -0.055798 & -0.3866 & 0.350387 \tabularnewline
26 & -0.017165 & -0.1189 & 0.452918 \tabularnewline
27 & 0.012872 & 0.0892 & 0.464656 \tabularnewline
28 & 0.011169 & 0.0774 & 0.469321 \tabularnewline
29 & -0.009602 & -0.0665 & 0.473618 \tabularnewline
30 & -0.071357 & -0.4944 & 0.311647 \tabularnewline
31 & 0.082541 & 0.5719 & 0.285043 \tabularnewline
32 & 0.024752 & 0.1715 & 0.43228 \tabularnewline
33 & -0.065609 & -0.4546 & 0.32574 \tabularnewline
34 & -0.058619 & -0.4061 & 0.343228 \tabularnewline
35 & -0.04449 & -0.3082 & 0.379619 \tabularnewline
36 & -0.153609 & -1.0642 & 0.146274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61469&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]0.107721[/C][C]0.7463[/C][C]0.229559[/C][/ROW]
[ROW][C]2[/C][C]0.064868[/C][C]0.4494[/C][C]0.327577[/C][/ROW]
[ROW][C]3[/C][C]0.060605[/C][C]0.4199[/C][C]0.338222[/C][/ROW]
[ROW][C]4[/C][C]0.025953[/C][C]0.1798[/C][C]0.429031[/C][/ROW]
[ROW][C]5[/C][C]-0.302716[/C][C]-2.0973[/C][C]0.02063[/C][/ROW]
[ROW][C]6[/C][C]0.095503[/C][C]0.6617[/C][C]0.255675[/C][/ROW]
[ROW][C]7[/C][C]0.219836[/C][C]1.5231[/C][C]0.067152[/C][/ROW]
[ROW][C]8[/C][C]-0.046917[/C][C]-0.3251[/C][C]0.373277[/C][/ROW]
[ROW][C]9[/C][C]0.055912[/C][C]0.3874[/C][C]0.350098[/C][/ROW]
[ROW][C]10[/C][C]-0.183816[/C][C]-1.2735[/C][C]0.104485[/C][/ROW]
[ROW][C]11[/C][C]-0.014152[/C][C]-0.098[/C][C]0.461152[/C][/ROW]
[ROW][C]12[/C][C]-0.168426[/C][C]-1.1669[/C][C]0.12451[/C][/ROW]
[ROW][C]13[/C][C]-0.038806[/C][C]-0.2689[/C][C]0.394598[/C][/ROW]
[ROW][C]14[/C][C]-0.008028[/C][C]-0.0556[/C][C]0.477937[/C][/ROW]
[ROW][C]15[/C][C]-0.161682[/C][C]-1.1202[/C][C]0.134108[/C][/ROW]
[ROW][C]16[/C][C]-0.127129[/C][C]-0.8808[/C][C]0.191414[/C][/ROW]
[ROW][C]17[/C][C]-0.110241[/C][C]-0.7638[/C][C]0.224371[/C][/ROW]
[ROW][C]18[/C][C]0.055237[/C][C]0.3827[/C][C]0.35182[/C][/ROW]
[ROW][C]19[/C][C]-0.09326[/C][C]-0.6461[/C][C]0.260639[/C][/ROW]
[ROW][C]20[/C][C]-0.076488[/C][C]-0.5299[/C][C]0.299304[/C][/ROW]
[ROW][C]21[/C][C]-0.090042[/C][C]-0.6238[/C][C]0.267846[/C][/ROW]
[ROW][C]22[/C][C]0.035127[/C][C]0.2434[/C][C]0.40438[/C][/ROW]
[ROW][C]23[/C][C]0.119811[/C][C]0.8301[/C][C]0.205303[/C][/ROW]
[ROW][C]24[/C][C]-0.160284[/C][C]-1.1105[/C][C]0.136163[/C][/ROW]
[ROW][C]25[/C][C]-0.055798[/C][C]-0.3866[/C][C]0.350387[/C][/ROW]
[ROW][C]26[/C][C]-0.017165[/C][C]-0.1189[/C][C]0.452918[/C][/ROW]
[ROW][C]27[/C][C]0.012872[/C][C]0.0892[/C][C]0.464656[/C][/ROW]
[ROW][C]28[/C][C]0.011169[/C][C]0.0774[/C][C]0.469321[/C][/ROW]
[ROW][C]29[/C][C]-0.009602[/C][C]-0.0665[/C][C]0.473618[/C][/ROW]
[ROW][C]30[/C][C]-0.071357[/C][C]-0.4944[/C][C]0.311647[/C][/ROW]
[ROW][C]31[/C][C]0.082541[/C][C]0.5719[/C][C]0.285043[/C][/ROW]
[ROW][C]32[/C][C]0.024752[/C][C]0.1715[/C][C]0.43228[/C][/ROW]
[ROW][C]33[/C][C]-0.065609[/C][C]-0.4546[/C][C]0.32574[/C][/ROW]
[ROW][C]34[/C][C]-0.058619[/C][C]-0.4061[/C][C]0.343228[/C][/ROW]
[ROW][C]35[/C][C]-0.04449[/C][C]-0.3082[/C][C]0.379619[/C][/ROW]
[ROW][C]36[/C][C]-0.153609[/C][C]-1.0642[/C][C]0.146274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61469&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61469&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
10.1077210.74630.229559
20.0648680.44940.327577
30.0606050.41990.338222
40.0259530.17980.429031
5-0.302716-2.09730.02063
60.0955030.66170.255675
70.2198361.52310.067152
8-0.046917-0.32510.373277
90.0559120.38740.350098
10-0.183816-1.27350.104485
11-0.014152-0.0980.461152
12-0.168426-1.16690.12451
13-0.038806-0.26890.394598
14-0.008028-0.05560.477937
15-0.161682-1.12020.134108
16-0.127129-0.88080.191414
17-0.110241-0.76380.224371
180.0552370.38270.35182
19-0.09326-0.64610.260639
20-0.076488-0.52990.299304
21-0.090042-0.62380.267846
220.0351270.24340.40438
230.1198110.83010.205303
24-0.160284-1.11050.136163
25-0.055798-0.38660.350387
26-0.017165-0.11890.452918
270.0128720.08920.464656
280.0111690.07740.469321
29-0.009602-0.06650.473618
30-0.071357-0.49440.311647
310.0825410.57190.285043
320.0247520.17150.43228
33-0.065609-0.45460.32574
34-0.058619-0.40610.343228
35-0.04449-0.30820.379619
36-0.153609-1.06420.146274


Figures (Output of Computation)

Input Parameters & R Code

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