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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, 02 Dec 2008 10:02:13 -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/02/t1228237414mezxphnmwwovner.htm/, Retrieved Sun, 19 May 2024 09:20:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28080, Retrieved Sun, 19 May 2024 09:20:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [nsts Q8 (1)] [2008-12-02 16:54:05] [b1bd16d1f47bfe13feacf1c27a0abba5]
F   PD  [(Partial) Autocorrelation Function] [nsts Q8 (2)] [2008-12-02 16:58:46] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   P       [(Partial) Autocorrelation Function] [nsts Q8 (3)] [2008-12-02 17:02:13] [e7b1048c2c3a353441b9143db4404b91] [Current]
F   P         [(Partial) Autocorrelation Function] [nsts Q8 (9)] [2008-12-02 17:59:47] [b1bd16d1f47bfe13feacf1c27a0abba5]
F RMPD        [Standard Deviation-Mean Plot] [nsts Q8 (9)] [2008-12-02 18:06:48] [b1bd16d1f47bfe13feacf1c27a0abba5]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
78.4
114.6
113.3
117.0
99.6
99.4
101.9
115.2
108.5
113.8
121.0
92.2
90.2
101.5
126.6
93.9
89.8
93.4
101.5
110.4
105.9
108.4
113.9
86.1
69.4
101.2
100.5
98.0
106.6
90.1
96.9
125.9
112.0
100.0
123.9
79.8
83.4
113.6
112.9
104.0
109.9
99.0
106.3
128.9
111.1
102.9
130.0
87.0
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137.0
91.0
90.5
122.4
123.3
124.3
120.0
118.1
119.0
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128.0
121.6
135.8
143.8
147.5
136.2
156.6
123.3
100.4

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=28080&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=28080&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28080&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
1-0.6069-5.14971e-06
20.1161860.98590.163748
30.073740.62570.266743
4-0.06646-0.56390.287278
5-0.051965-0.44090.33029
60.1279431.08560.140632
7-0.101574-0.86190.195806
8-0.050482-0.42840.334835
90.1664981.41280.081014
10-0.147351-1.25030.107616
110.2648232.24710.01385
12-0.303152-2.57230.006082
130.1141610.96870.167971
14-0.00479-0.04060.483847
15-0.022389-0.190.424931
16-0.050663-0.42990.33428
170.0972370.82510.206025
18-0.033848-0.28720.387387
19-0.076809-0.65170.258319
200.1203571.02130.155275
21-0.001273-0.01080.495707
22-0.144865-1.22920.111496
230.1189041.00890.158193
24-0.037373-0.31710.376034
25-0.079849-0.67750.250117
260.1628641.38190.085631
27-0.060358-0.51220.305057
28-0.078239-0.66390.254443
290.0936790.79490.214645
30-0.007318-0.06210.47533
31-0.051099-0.43360.33294
320.0763020.64740.259703
33-0.136971-1.16220.124489
340.1204131.02170.155162
350.034840.29560.384182
36-0.143124-1.21440.114273

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.6069 & -5.1497 & 1e-06 \tabularnewline
2 & 0.116186 & 0.9859 & 0.163748 \tabularnewline
3 & 0.07374 & 0.6257 & 0.266743 \tabularnewline
4 & -0.06646 & -0.5639 & 0.287278 \tabularnewline
5 & -0.051965 & -0.4409 & 0.33029 \tabularnewline
6 & 0.127943 & 1.0856 & 0.140632 \tabularnewline
7 & -0.101574 & -0.8619 & 0.195806 \tabularnewline
8 & -0.050482 & -0.4284 & 0.334835 \tabularnewline
9 & 0.166498 & 1.4128 & 0.081014 \tabularnewline
10 & -0.147351 & -1.2503 & 0.107616 \tabularnewline
11 & 0.264823 & 2.2471 & 0.01385 \tabularnewline
12 & -0.303152 & -2.5723 & 0.006082 \tabularnewline
13 & 0.114161 & 0.9687 & 0.167971 \tabularnewline
14 & -0.00479 & -0.0406 & 0.483847 \tabularnewline
15 & -0.022389 & -0.19 & 0.424931 \tabularnewline
16 & -0.050663 & -0.4299 & 0.33428 \tabularnewline
17 & 0.097237 & 0.8251 & 0.206025 \tabularnewline
18 & -0.033848 & -0.2872 & 0.387387 \tabularnewline
19 & -0.076809 & -0.6517 & 0.258319 \tabularnewline
20 & 0.120357 & 1.0213 & 0.155275 \tabularnewline
21 & -0.001273 & -0.0108 & 0.495707 \tabularnewline
22 & -0.144865 & -1.2292 & 0.111496 \tabularnewline
23 & 0.118904 & 1.0089 & 0.158193 \tabularnewline
24 & -0.037373 & -0.3171 & 0.376034 \tabularnewline
25 & -0.079849 & -0.6775 & 0.250117 \tabularnewline
26 & 0.162864 & 1.3819 & 0.085631 \tabularnewline
27 & -0.060358 & -0.5122 & 0.305057 \tabularnewline
28 & -0.078239 & -0.6639 & 0.254443 \tabularnewline
29 & 0.093679 & 0.7949 & 0.214645 \tabularnewline
30 & -0.007318 & -0.0621 & 0.47533 \tabularnewline
31 & -0.051099 & -0.4336 & 0.33294 \tabularnewline
32 & 0.076302 & 0.6474 & 0.259703 \tabularnewline
33 & -0.136971 & -1.1622 & 0.124489 \tabularnewline
34 & 0.120413 & 1.0217 & 0.155162 \tabularnewline
35 & 0.03484 & 0.2956 & 0.384182 \tabularnewline
36 & -0.143124 & -1.2144 & 0.114273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28080&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]-0.6069[/C][C]-5.1497[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.116186[/C][C]0.9859[/C][C]0.163748[/C][/ROW]
[ROW][C]3[/C][C]0.07374[/C][C]0.6257[/C][C]0.266743[/C][/ROW]
[ROW][C]4[/C][C]-0.06646[/C][C]-0.5639[/C][C]0.287278[/C][/ROW]
[ROW][C]5[/C][C]-0.051965[/C][C]-0.4409[/C][C]0.33029[/C][/ROW]
[ROW][C]6[/C][C]0.127943[/C][C]1.0856[/C][C]0.140632[/C][/ROW]
[ROW][C]7[/C][C]-0.101574[/C][C]-0.8619[/C][C]0.195806[/C][/ROW]
[ROW][C]8[/C][C]-0.050482[/C][C]-0.4284[/C][C]0.334835[/C][/ROW]
[ROW][C]9[/C][C]0.166498[/C][C]1.4128[/C][C]0.081014[/C][/ROW]
[ROW][C]10[/C][C]-0.147351[/C][C]-1.2503[/C][C]0.107616[/C][/ROW]
[ROW][C]11[/C][C]0.264823[/C][C]2.2471[/C][C]0.01385[/C][/ROW]
[ROW][C]12[/C][C]-0.303152[/C][C]-2.5723[/C][C]0.006082[/C][/ROW]
[ROW][C]13[/C][C]0.114161[/C][C]0.9687[/C][C]0.167971[/C][/ROW]
[ROW][C]14[/C][C]-0.00479[/C][C]-0.0406[/C][C]0.483847[/C][/ROW]
[ROW][C]15[/C][C]-0.022389[/C][C]-0.19[/C][C]0.424931[/C][/ROW]
[ROW][C]16[/C][C]-0.050663[/C][C]-0.4299[/C][C]0.33428[/C][/ROW]
[ROW][C]17[/C][C]0.097237[/C][C]0.8251[/C][C]0.206025[/C][/ROW]
[ROW][C]18[/C][C]-0.033848[/C][C]-0.2872[/C][C]0.387387[/C][/ROW]
[ROW][C]19[/C][C]-0.076809[/C][C]-0.6517[/C][C]0.258319[/C][/ROW]
[ROW][C]20[/C][C]0.120357[/C][C]1.0213[/C][C]0.155275[/C][/ROW]
[ROW][C]21[/C][C]-0.001273[/C][C]-0.0108[/C][C]0.495707[/C][/ROW]
[ROW][C]22[/C][C]-0.144865[/C][C]-1.2292[/C][C]0.111496[/C][/ROW]
[ROW][C]23[/C][C]0.118904[/C][C]1.0089[/C][C]0.158193[/C][/ROW]
[ROW][C]24[/C][C]-0.037373[/C][C]-0.3171[/C][C]0.376034[/C][/ROW]
[ROW][C]25[/C][C]-0.079849[/C][C]-0.6775[/C][C]0.250117[/C][/ROW]
[ROW][C]26[/C][C]0.162864[/C][C]1.3819[/C][C]0.085631[/C][/ROW]
[ROW][C]27[/C][C]-0.060358[/C][C]-0.5122[/C][C]0.305057[/C][/ROW]
[ROW][C]28[/C][C]-0.078239[/C][C]-0.6639[/C][C]0.254443[/C][/ROW]
[ROW][C]29[/C][C]0.093679[/C][C]0.7949[/C][C]0.214645[/C][/ROW]
[ROW][C]30[/C][C]-0.007318[/C][C]-0.0621[/C][C]0.47533[/C][/ROW]
[ROW][C]31[/C][C]-0.051099[/C][C]-0.4336[/C][C]0.33294[/C][/ROW]
[ROW][C]32[/C][C]0.076302[/C][C]0.6474[/C][C]0.259703[/C][/ROW]
[ROW][C]33[/C][C]-0.136971[/C][C]-1.1622[/C][C]0.124489[/C][/ROW]
[ROW][C]34[/C][C]0.120413[/C][C]1.0217[/C][C]0.155162[/C][/ROW]
[ROW][C]35[/C][C]0.03484[/C][C]0.2956[/C][C]0.384182[/C][/ROW]
[ROW][C]36[/C][C]-0.143124[/C][C]-1.2144[/C][C]0.114273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28080&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28080&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
1-0.6069-5.14971e-06
20.1161860.98590.163748
30.073740.62570.266743
4-0.06646-0.56390.287278
5-0.051965-0.44090.33029
60.1279431.08560.140632
7-0.101574-0.86190.195806
8-0.050482-0.42840.334835
90.1664981.41280.081014
10-0.147351-1.25030.107616
110.2648232.24710.01385
12-0.303152-2.57230.006082
130.1141610.96870.167971
14-0.00479-0.04060.483847
15-0.022389-0.190.424931
16-0.050663-0.42990.33428
170.0972370.82510.206025
18-0.033848-0.28720.387387
19-0.076809-0.65170.258319
200.1203571.02130.155275
21-0.001273-0.01080.495707
22-0.144865-1.22920.111496
230.1189041.00890.158193
24-0.037373-0.31710.376034
25-0.079849-0.67750.250117
260.1628641.38190.085631
27-0.060358-0.51220.305057
28-0.078239-0.66390.254443
290.0936790.79490.214645
30-0.007318-0.06210.47533
31-0.051099-0.43360.33294
320.0763020.64740.259703
33-0.136971-1.16220.124489
340.1204131.02170.155162
350.034840.29560.384182
36-0.143124-1.21440.114273






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.6069-5.14971e-06
2-0.399165-3.3870.000574
3-0.131544-1.11620.134027
4-0.039187-0.33250.370235
5-0.148699-1.26180.105555
6-0.016315-0.13840.44514
7-0.014761-0.12530.450337
8-0.176808-1.50030.068959
9-0.008598-0.0730.471021
10-0.028129-0.23870.406015
110.401533.40710.000539
120.1208541.02550.154284
13-0.086221-0.73160.23339
14-0.144131-1.2230.11266
15-0.111697-0.94780.173205
16-0.155212-1.3170.096005
17-0.104189-0.88410.1898
180.0987270.83770.202479
19-0.018892-0.16030.436546
20-0.213426-1.8110.037158
21-0.009302-0.07890.468653
22-0.14744-1.25110.10748
230.0500350.42460.336212
240.0554190.47020.319802
25-0.047095-0.39960.345311
260.0935920.79420.214857
270.1255371.06520.145168
28-0.041773-0.35450.362018
29-0.108546-0.9210.180052
300.0509060.4320.333534
310.0606410.51460.304218
32-0.004369-0.03710.485264
33-0.069128-0.58660.279665
34-0.069472-0.58950.278688
350.1376511.1680.123329
36-0.07883-0.66890.252851

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.6069 & -5.1497 & 1e-06 \tabularnewline
2 & -0.399165 & -3.387 & 0.000574 \tabularnewline
3 & -0.131544 & -1.1162 & 0.134027 \tabularnewline
4 & -0.039187 & -0.3325 & 0.370235 \tabularnewline
5 & -0.148699 & -1.2618 & 0.105555 \tabularnewline
6 & -0.016315 & -0.1384 & 0.44514 \tabularnewline
7 & -0.014761 & -0.1253 & 0.450337 \tabularnewline
8 & -0.176808 & -1.5003 & 0.068959 \tabularnewline
9 & -0.008598 & -0.073 & 0.471021 \tabularnewline
10 & -0.028129 & -0.2387 & 0.406015 \tabularnewline
11 & 0.40153 & 3.4071 & 0.000539 \tabularnewline
12 & 0.120854 & 1.0255 & 0.154284 \tabularnewline
13 & -0.086221 & -0.7316 & 0.23339 \tabularnewline
14 & -0.144131 & -1.223 & 0.11266 \tabularnewline
15 & -0.111697 & -0.9478 & 0.173205 \tabularnewline
16 & -0.155212 & -1.317 & 0.096005 \tabularnewline
17 & -0.104189 & -0.8841 & 0.1898 \tabularnewline
18 & 0.098727 & 0.8377 & 0.202479 \tabularnewline
19 & -0.018892 & -0.1603 & 0.436546 \tabularnewline
20 & -0.213426 & -1.811 & 0.037158 \tabularnewline
21 & -0.009302 & -0.0789 & 0.468653 \tabularnewline
22 & -0.14744 & -1.2511 & 0.10748 \tabularnewline
23 & 0.050035 & 0.4246 & 0.336212 \tabularnewline
24 & 0.055419 & 0.4702 & 0.319802 \tabularnewline
25 & -0.047095 & -0.3996 & 0.345311 \tabularnewline
26 & 0.093592 & 0.7942 & 0.214857 \tabularnewline
27 & 0.125537 & 1.0652 & 0.145168 \tabularnewline
28 & -0.041773 & -0.3545 & 0.362018 \tabularnewline
29 & -0.108546 & -0.921 & 0.180052 \tabularnewline
30 & 0.050906 & 0.432 & 0.333534 \tabularnewline
31 & 0.060641 & 0.5146 & 0.304218 \tabularnewline
32 & -0.004369 & -0.0371 & 0.485264 \tabularnewline
33 & -0.069128 & -0.5866 & 0.279665 \tabularnewline
34 & -0.069472 & -0.5895 & 0.278688 \tabularnewline
35 & 0.137651 & 1.168 & 0.123329 \tabularnewline
36 & -0.07883 & -0.6689 & 0.252851 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28080&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]-0.6069[/C][C]-5.1497[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.399165[/C][C]-3.387[/C][C]0.000574[/C][/ROW]
[ROW][C]3[/C][C]-0.131544[/C][C]-1.1162[/C][C]0.134027[/C][/ROW]
[ROW][C]4[/C][C]-0.039187[/C][C]-0.3325[/C][C]0.370235[/C][/ROW]
[ROW][C]5[/C][C]-0.148699[/C][C]-1.2618[/C][C]0.105555[/C][/ROW]
[ROW][C]6[/C][C]-0.016315[/C][C]-0.1384[/C][C]0.44514[/C][/ROW]
[ROW][C]7[/C][C]-0.014761[/C][C]-0.1253[/C][C]0.450337[/C][/ROW]
[ROW][C]8[/C][C]-0.176808[/C][C]-1.5003[/C][C]0.068959[/C][/ROW]
[ROW][C]9[/C][C]-0.008598[/C][C]-0.073[/C][C]0.471021[/C][/ROW]
[ROW][C]10[/C][C]-0.028129[/C][C]-0.2387[/C][C]0.406015[/C][/ROW]
[ROW][C]11[/C][C]0.40153[/C][C]3.4071[/C][C]0.000539[/C][/ROW]
[ROW][C]12[/C][C]0.120854[/C][C]1.0255[/C][C]0.154284[/C][/ROW]
[ROW][C]13[/C][C]-0.086221[/C][C]-0.7316[/C][C]0.23339[/C][/ROW]
[ROW][C]14[/C][C]-0.144131[/C][C]-1.223[/C][C]0.11266[/C][/ROW]
[ROW][C]15[/C][C]-0.111697[/C][C]-0.9478[/C][C]0.173205[/C][/ROW]
[ROW][C]16[/C][C]-0.155212[/C][C]-1.317[/C][C]0.096005[/C][/ROW]
[ROW][C]17[/C][C]-0.104189[/C][C]-0.8841[/C][C]0.1898[/C][/ROW]
[ROW][C]18[/C][C]0.098727[/C][C]0.8377[/C][C]0.202479[/C][/ROW]
[ROW][C]19[/C][C]-0.018892[/C][C]-0.1603[/C][C]0.436546[/C][/ROW]
[ROW][C]20[/C][C]-0.213426[/C][C]-1.811[/C][C]0.037158[/C][/ROW]
[ROW][C]21[/C][C]-0.009302[/C][C]-0.0789[/C][C]0.468653[/C][/ROW]
[ROW][C]22[/C][C]-0.14744[/C][C]-1.2511[/C][C]0.10748[/C][/ROW]
[ROW][C]23[/C][C]0.050035[/C][C]0.4246[/C][C]0.336212[/C][/ROW]
[ROW][C]24[/C][C]0.055419[/C][C]0.4702[/C][C]0.319802[/C][/ROW]
[ROW][C]25[/C][C]-0.047095[/C][C]-0.3996[/C][C]0.345311[/C][/ROW]
[ROW][C]26[/C][C]0.093592[/C][C]0.7942[/C][C]0.214857[/C][/ROW]
[ROW][C]27[/C][C]0.125537[/C][C]1.0652[/C][C]0.145168[/C][/ROW]
[ROW][C]28[/C][C]-0.041773[/C][C]-0.3545[/C][C]0.362018[/C][/ROW]
[ROW][C]29[/C][C]-0.108546[/C][C]-0.921[/C][C]0.180052[/C][/ROW]
[ROW][C]30[/C][C]0.050906[/C][C]0.432[/C][C]0.333534[/C][/ROW]
[ROW][C]31[/C][C]0.060641[/C][C]0.5146[/C][C]0.304218[/C][/ROW]
[ROW][C]32[/C][C]-0.004369[/C][C]-0.0371[/C][C]0.485264[/C][/ROW]
[ROW][C]33[/C][C]-0.069128[/C][C]-0.5866[/C][C]0.279665[/C][/ROW]
[ROW][C]34[/C][C]-0.069472[/C][C]-0.5895[/C][C]0.278688[/C][/ROW]
[ROW][C]35[/C][C]0.137651[/C][C]1.168[/C][C]0.123329[/C][/ROW]
[ROW][C]36[/C][C]-0.07883[/C][C]-0.6689[/C][C]0.252851[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28080&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28080&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
1-0.6069-5.14971e-06
2-0.399165-3.3870.000574
3-0.131544-1.11620.134027
4-0.039187-0.33250.370235
5-0.148699-1.26180.105555
6-0.016315-0.13840.44514
7-0.014761-0.12530.450337
8-0.176808-1.50030.068959
9-0.008598-0.0730.471021
10-0.028129-0.23870.406015
110.401533.40710.000539
120.1208541.02550.154284
13-0.086221-0.73160.23339
14-0.144131-1.2230.11266
15-0.111697-0.94780.173205
16-0.155212-1.3170.096005
17-0.104189-0.88410.1898
180.0987270.83770.202479
19-0.018892-0.16030.436546
20-0.213426-1.8110.037158
21-0.009302-0.07890.468653
22-0.14744-1.25110.10748
230.0500350.42460.336212
240.0554190.47020.319802
25-0.047095-0.39960.345311
260.0935920.79420.214857
270.1255371.06520.145168
28-0.041773-0.35450.362018
29-0.108546-0.9210.180052
300.0509060.4320.333534
310.0606410.51460.304218
32-0.004369-0.03710.485264
33-0.069128-0.58660.279665
34-0.069472-0.58950.278688
350.1376511.1680.123329
36-0.07883-0.66890.252851


Figures (Output of Computation)

Input Parameters & R Code

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