Free Statistics

of Irreproducible Research!

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 computationFri, 27 Nov 2009 08:19:54 -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/27/t1259335285v0rfwmrorr0dzfd.htm/, Retrieved Sat, 27 Apr 2024 13:38:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60896, Retrieved Sat, 27 Apr 2024 13:38:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
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] [ws 8] [2009-11-24 20:17:54] [b5908418e3090fddbd22f5f0f774653d]
-    D            [(Partial) Autocorrelation Function] [WS8 ACF] [2009-11-27 15:19:54] [557d56ec4b06cd0135c259898de8ce95] [Current]
Feedback Forum

Post a new message
Dataseries X:
10284,5
12792
12823,61538
13845,66667
15335,63636
11188,5
13633,25
12298,46667
15353,63636
12696,15385
12213,93333
13683,72727
11214,14286
13950,23077
11179,13333
11801,875
11188,82353
16456,27273
11110,0625
16530,69231
10038,41176
11681,25
11148,88235
8631
9386,444444
9764,736842
12043,75
12948,06667
10987,125
11648,3125
10633,35294
10219,3
9037,6
10296,31579
11705,41176
10681,94444
9362,947368
11306,35294
10984,45
10062,61905
8118,583333
8867,48
8346,72
8529,307692
10697,18182
8591,84
8695,607143
8125,571429
7009,758621
7883,466667
7527,645161
6763,758621
6682,333333
7855,681818
6738,88
7895,434783
6361,884615
6935,956522
8344,454545
9107,944444




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60896&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]2 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=60896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60896&T=0

As an alternative you can also use a 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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6325684.89994e-06
20.7291625.64810
30.5457614.22744.1e-05
40.5422264.20014.5e-05
50.506823.92580.000113
60.4651853.60330.00032
70.4581293.54870.00038
80.4498063.48420.000464
90.444263.44120.00053
100.3600952.78930.003534
110.3353242.59740.005899
120.2036321.57730.059989
130.2159651.67290.049781
140.1404531.08790.140485
150.1779461.37840.086604
160.1713331.32710.094746
170.092430.7160.238397
180.1132280.87710.191976
19-0.010321-0.07990.468272
20-0.002615-0.02030.491953
21-0.062579-0.48470.314815
22-0.05862-0.45410.325709
23-0.059967-0.46450.321983
24-0.061391-0.47550.318067
25-0.029952-0.2320.40866
26-0.065299-0.50580.307425
27-0.082818-0.64150.26182
28-0.144011-1.11550.134541
29-0.18053-1.39840.083573
30-0.180121-1.39520.084048
31-0.173213-1.34170.092375
32-0.214891-1.66450.05061
33-0.19303-1.49520.070051
34-0.222623-1.72440.04489
35-0.275273-2.13230.018544
36-0.251755-1.95010.027921

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.632568 & 4.8999 & 4e-06 \tabularnewline
2 & 0.729162 & 5.6481 & 0 \tabularnewline
3 & 0.545761 & 4.2274 & 4.1e-05 \tabularnewline
4 & 0.542226 & 4.2001 & 4.5e-05 \tabularnewline
5 & 0.50682 & 3.9258 & 0.000113 \tabularnewline
6 & 0.465185 & 3.6033 & 0.00032 \tabularnewline
7 & 0.458129 & 3.5487 & 0.00038 \tabularnewline
8 & 0.449806 & 3.4842 & 0.000464 \tabularnewline
9 & 0.44426 & 3.4412 & 0.00053 \tabularnewline
10 & 0.360095 & 2.7893 & 0.003534 \tabularnewline
11 & 0.335324 & 2.5974 & 0.005899 \tabularnewline
12 & 0.203632 & 1.5773 & 0.059989 \tabularnewline
13 & 0.215965 & 1.6729 & 0.049781 \tabularnewline
14 & 0.140453 & 1.0879 & 0.140485 \tabularnewline
15 & 0.177946 & 1.3784 & 0.086604 \tabularnewline
16 & 0.171333 & 1.3271 & 0.094746 \tabularnewline
17 & 0.09243 & 0.716 & 0.238397 \tabularnewline
18 & 0.113228 & 0.8771 & 0.191976 \tabularnewline
19 & -0.010321 & -0.0799 & 0.468272 \tabularnewline
20 & -0.002615 & -0.0203 & 0.491953 \tabularnewline
21 & -0.062579 & -0.4847 & 0.314815 \tabularnewline
22 & -0.05862 & -0.4541 & 0.325709 \tabularnewline
23 & -0.059967 & -0.4645 & 0.321983 \tabularnewline
24 & -0.061391 & -0.4755 & 0.318067 \tabularnewline
25 & -0.029952 & -0.232 & 0.40866 \tabularnewline
26 & -0.065299 & -0.5058 & 0.307425 \tabularnewline
27 & -0.082818 & -0.6415 & 0.26182 \tabularnewline
28 & -0.144011 & -1.1155 & 0.134541 \tabularnewline
29 & -0.18053 & -1.3984 & 0.083573 \tabularnewline
30 & -0.180121 & -1.3952 & 0.084048 \tabularnewline
31 & -0.173213 & -1.3417 & 0.092375 \tabularnewline
32 & -0.214891 & -1.6645 & 0.05061 \tabularnewline
33 & -0.19303 & -1.4952 & 0.070051 \tabularnewline
34 & -0.222623 & -1.7244 & 0.04489 \tabularnewline
35 & -0.275273 & -2.1323 & 0.018544 \tabularnewline
36 & -0.251755 & -1.9501 & 0.027921 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60896&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]0.632568[/C][C]4.8999[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]0.729162[/C][C]5.6481[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.545761[/C][C]4.2274[/C][C]4.1e-05[/C][/ROW]
[ROW][C]4[/C][C]0.542226[/C][C]4.2001[/C][C]4.5e-05[/C][/ROW]
[ROW][C]5[/C][C]0.50682[/C][C]3.9258[/C][C]0.000113[/C][/ROW]
[ROW][C]6[/C][C]0.465185[/C][C]3.6033[/C][C]0.00032[/C][/ROW]
[ROW][C]7[/C][C]0.458129[/C][C]3.5487[/C][C]0.00038[/C][/ROW]
[ROW][C]8[/C][C]0.449806[/C][C]3.4842[/C][C]0.000464[/C][/ROW]
[ROW][C]9[/C][C]0.44426[/C][C]3.4412[/C][C]0.00053[/C][/ROW]
[ROW][C]10[/C][C]0.360095[/C][C]2.7893[/C][C]0.003534[/C][/ROW]
[ROW][C]11[/C][C]0.335324[/C][C]2.5974[/C][C]0.005899[/C][/ROW]
[ROW][C]12[/C][C]0.203632[/C][C]1.5773[/C][C]0.059989[/C][/ROW]
[ROW][C]13[/C][C]0.215965[/C][C]1.6729[/C][C]0.049781[/C][/ROW]
[ROW][C]14[/C][C]0.140453[/C][C]1.0879[/C][C]0.140485[/C][/ROW]
[ROW][C]15[/C][C]0.177946[/C][C]1.3784[/C][C]0.086604[/C][/ROW]
[ROW][C]16[/C][C]0.171333[/C][C]1.3271[/C][C]0.094746[/C][/ROW]
[ROW][C]17[/C][C]0.09243[/C][C]0.716[/C][C]0.238397[/C][/ROW]
[ROW][C]18[/C][C]0.113228[/C][C]0.8771[/C][C]0.191976[/C][/ROW]
[ROW][C]19[/C][C]-0.010321[/C][C]-0.0799[/C][C]0.468272[/C][/ROW]
[ROW][C]20[/C][C]-0.002615[/C][C]-0.0203[/C][C]0.491953[/C][/ROW]
[ROW][C]21[/C][C]-0.062579[/C][C]-0.4847[/C][C]0.314815[/C][/ROW]
[ROW][C]22[/C][C]-0.05862[/C][C]-0.4541[/C][C]0.325709[/C][/ROW]
[ROW][C]23[/C][C]-0.059967[/C][C]-0.4645[/C][C]0.321983[/C][/ROW]
[ROW][C]24[/C][C]-0.061391[/C][C]-0.4755[/C][C]0.318067[/C][/ROW]
[ROW][C]25[/C][C]-0.029952[/C][C]-0.232[/C][C]0.40866[/C][/ROW]
[ROW][C]26[/C][C]-0.065299[/C][C]-0.5058[/C][C]0.307425[/C][/ROW]
[ROW][C]27[/C][C]-0.082818[/C][C]-0.6415[/C][C]0.26182[/C][/ROW]
[ROW][C]28[/C][C]-0.144011[/C][C]-1.1155[/C][C]0.134541[/C][/ROW]
[ROW][C]29[/C][C]-0.18053[/C][C]-1.3984[/C][C]0.083573[/C][/ROW]
[ROW][C]30[/C][C]-0.180121[/C][C]-1.3952[/C][C]0.084048[/C][/ROW]
[ROW][C]31[/C][C]-0.173213[/C][C]-1.3417[/C][C]0.092375[/C][/ROW]
[ROW][C]32[/C][C]-0.214891[/C][C]-1.6645[/C][C]0.05061[/C][/ROW]
[ROW][C]33[/C][C]-0.19303[/C][C]-1.4952[/C][C]0.070051[/C][/ROW]
[ROW][C]34[/C][C]-0.222623[/C][C]-1.7244[/C][C]0.04489[/C][/ROW]
[ROW][C]35[/C][C]-0.275273[/C][C]-2.1323[/C][C]0.018544[/C][/ROW]
[ROW][C]36[/C][C]-0.251755[/C][C]-1.9501[/C][C]0.027921[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60896&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.6325684.89994e-06
20.7291625.64810
30.5457614.22744.1e-05
40.5422264.20014.5e-05
50.506823.92580.000113
60.4651853.60330.00032
70.4581293.54870.00038
80.4498063.48420.000464
90.444263.44120.00053
100.3600952.78930.003534
110.3353242.59740.005899
120.2036321.57730.059989
130.2159651.67290.049781
140.1404531.08790.140485
150.1779461.37840.086604
160.1713331.32710.094746
170.092430.7160.238397
180.1132280.87710.191976
19-0.010321-0.07990.468272
20-0.002615-0.02030.491953
21-0.062579-0.48470.314815
22-0.05862-0.45410.325709
23-0.059967-0.46450.321983
24-0.061391-0.47550.318067
25-0.029952-0.2320.40866
26-0.065299-0.50580.307425
27-0.082818-0.64150.26182
28-0.144011-1.11550.134541
29-0.18053-1.39840.083573
30-0.180121-1.39520.084048
31-0.173213-1.34170.092375
32-0.214891-1.66450.05061
33-0.19303-1.49520.070051
34-0.222623-1.72440.04489
35-0.275273-2.13230.018544
36-0.251755-1.95010.027921







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6325684.89994e-06
20.5484974.24863.8e-05
3-0.022542-0.17460.430988
4-0.0257-0.19910.421439
50.1480811.1470.127961
60.0341860.26480.396035
70.0198670.15390.439108
80.1018020.78860.216739
90.0668870.51810.303146
10-0.172472-1.3360.093304
11-0.087596-0.67850.250027
12-0.168299-1.30360.098669
13-0.015599-0.12080.452115
140.0133750.10360.458916
150.0865290.67030.252634
160.1003050.7770.220118
17-0.203607-1.57710.060011
18-0.043999-0.34080.367216
19-0.094288-0.73040.234008
20-0.04253-0.32940.371487
210.0722720.55980.288843
220.0742780.57540.283602
230.0375980.29120.385938
24-0.070511-0.54620.293486
250.0581950.45080.326886
26-0.031515-0.24410.403986
27-0.074107-0.5740.284046
28-0.016719-0.12950.448696
29-0.092039-0.71290.239326
300.0356150.27590.391798
31-0.00328-0.02540.489906
32-0.153671-1.19030.119302
33-0.054296-0.42060.337784
34-0.015644-0.12120.451976
35-0.132669-1.02760.15412
360.0315610.24450.403852

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.632568 & 4.8999 & 4e-06 \tabularnewline
2 & 0.548497 & 4.2486 & 3.8e-05 \tabularnewline
3 & -0.022542 & -0.1746 & 0.430988 \tabularnewline
4 & -0.0257 & -0.1991 & 0.421439 \tabularnewline
5 & 0.148081 & 1.147 & 0.127961 \tabularnewline
6 & 0.034186 & 0.2648 & 0.396035 \tabularnewline
7 & 0.019867 & 0.1539 & 0.439108 \tabularnewline
8 & 0.101802 & 0.7886 & 0.216739 \tabularnewline
9 & 0.066887 & 0.5181 & 0.303146 \tabularnewline
10 & -0.172472 & -1.336 & 0.093304 \tabularnewline
11 & -0.087596 & -0.6785 & 0.250027 \tabularnewline
12 & -0.168299 & -1.3036 & 0.098669 \tabularnewline
13 & -0.015599 & -0.1208 & 0.452115 \tabularnewline
14 & 0.013375 & 0.1036 & 0.458916 \tabularnewline
15 & 0.086529 & 0.6703 & 0.252634 \tabularnewline
16 & 0.100305 & 0.777 & 0.220118 \tabularnewline
17 & -0.203607 & -1.5771 & 0.060011 \tabularnewline
18 & -0.043999 & -0.3408 & 0.367216 \tabularnewline
19 & -0.094288 & -0.7304 & 0.234008 \tabularnewline
20 & -0.04253 & -0.3294 & 0.371487 \tabularnewline
21 & 0.072272 & 0.5598 & 0.288843 \tabularnewline
22 & 0.074278 & 0.5754 & 0.283602 \tabularnewline
23 & 0.037598 & 0.2912 & 0.385938 \tabularnewline
24 & -0.070511 & -0.5462 & 0.293486 \tabularnewline
25 & 0.058195 & 0.4508 & 0.326886 \tabularnewline
26 & -0.031515 & -0.2441 & 0.403986 \tabularnewline
27 & -0.074107 & -0.574 & 0.284046 \tabularnewline
28 & -0.016719 & -0.1295 & 0.448696 \tabularnewline
29 & -0.092039 & -0.7129 & 0.239326 \tabularnewline
30 & 0.035615 & 0.2759 & 0.391798 \tabularnewline
31 & -0.00328 & -0.0254 & 0.489906 \tabularnewline
32 & -0.153671 & -1.1903 & 0.119302 \tabularnewline
33 & -0.054296 & -0.4206 & 0.337784 \tabularnewline
34 & -0.015644 & -0.1212 & 0.451976 \tabularnewline
35 & -0.132669 & -1.0276 & 0.15412 \tabularnewline
36 & 0.031561 & 0.2445 & 0.403852 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60896&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]0.632568[/C][C]4.8999[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]0.548497[/C][C]4.2486[/C][C]3.8e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.022542[/C][C]-0.1746[/C][C]0.430988[/C][/ROW]
[ROW][C]4[/C][C]-0.0257[/C][C]-0.1991[/C][C]0.421439[/C][/ROW]
[ROW][C]5[/C][C]0.148081[/C][C]1.147[/C][C]0.127961[/C][/ROW]
[ROW][C]6[/C][C]0.034186[/C][C]0.2648[/C][C]0.396035[/C][/ROW]
[ROW][C]7[/C][C]0.019867[/C][C]0.1539[/C][C]0.439108[/C][/ROW]
[ROW][C]8[/C][C]0.101802[/C][C]0.7886[/C][C]0.216739[/C][/ROW]
[ROW][C]9[/C][C]0.066887[/C][C]0.5181[/C][C]0.303146[/C][/ROW]
[ROW][C]10[/C][C]-0.172472[/C][C]-1.336[/C][C]0.093304[/C][/ROW]
[ROW][C]11[/C][C]-0.087596[/C][C]-0.6785[/C][C]0.250027[/C][/ROW]
[ROW][C]12[/C][C]-0.168299[/C][C]-1.3036[/C][C]0.098669[/C][/ROW]
[ROW][C]13[/C][C]-0.015599[/C][C]-0.1208[/C][C]0.452115[/C][/ROW]
[ROW][C]14[/C][C]0.013375[/C][C]0.1036[/C][C]0.458916[/C][/ROW]
[ROW][C]15[/C][C]0.086529[/C][C]0.6703[/C][C]0.252634[/C][/ROW]
[ROW][C]16[/C][C]0.100305[/C][C]0.777[/C][C]0.220118[/C][/ROW]
[ROW][C]17[/C][C]-0.203607[/C][C]-1.5771[/C][C]0.060011[/C][/ROW]
[ROW][C]18[/C][C]-0.043999[/C][C]-0.3408[/C][C]0.367216[/C][/ROW]
[ROW][C]19[/C][C]-0.094288[/C][C]-0.7304[/C][C]0.234008[/C][/ROW]
[ROW][C]20[/C][C]-0.04253[/C][C]-0.3294[/C][C]0.371487[/C][/ROW]
[ROW][C]21[/C][C]0.072272[/C][C]0.5598[/C][C]0.288843[/C][/ROW]
[ROW][C]22[/C][C]0.074278[/C][C]0.5754[/C][C]0.283602[/C][/ROW]
[ROW][C]23[/C][C]0.037598[/C][C]0.2912[/C][C]0.385938[/C][/ROW]
[ROW][C]24[/C][C]-0.070511[/C][C]-0.5462[/C][C]0.293486[/C][/ROW]
[ROW][C]25[/C][C]0.058195[/C][C]0.4508[/C][C]0.326886[/C][/ROW]
[ROW][C]26[/C][C]-0.031515[/C][C]-0.2441[/C][C]0.403986[/C][/ROW]
[ROW][C]27[/C][C]-0.074107[/C][C]-0.574[/C][C]0.284046[/C][/ROW]
[ROW][C]28[/C][C]-0.016719[/C][C]-0.1295[/C][C]0.448696[/C][/ROW]
[ROW][C]29[/C][C]-0.092039[/C][C]-0.7129[/C][C]0.239326[/C][/ROW]
[ROW][C]30[/C][C]0.035615[/C][C]0.2759[/C][C]0.391798[/C][/ROW]
[ROW][C]31[/C][C]-0.00328[/C][C]-0.0254[/C][C]0.489906[/C][/ROW]
[ROW][C]32[/C][C]-0.153671[/C][C]-1.1903[/C][C]0.119302[/C][/ROW]
[ROW][C]33[/C][C]-0.054296[/C][C]-0.4206[/C][C]0.337784[/C][/ROW]
[ROW][C]34[/C][C]-0.015644[/C][C]-0.1212[/C][C]0.451976[/C][/ROW]
[ROW][C]35[/C][C]-0.132669[/C][C]-1.0276[/C][C]0.15412[/C][/ROW]
[ROW][C]36[/C][C]0.031561[/C][C]0.2445[/C][C]0.403852[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60896&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60896&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6325684.89994e-06
20.5484974.24863.8e-05
3-0.022542-0.17460.430988
4-0.0257-0.19910.421439
50.1480811.1470.127961
60.0341860.26480.396035
70.0198670.15390.439108
80.1018020.78860.216739
90.0668870.51810.303146
10-0.172472-1.3360.093304
11-0.087596-0.67850.250027
12-0.168299-1.30360.098669
13-0.015599-0.12080.452115
140.0133750.10360.458916
150.0865290.67030.252634
160.1003050.7770.220118
17-0.203607-1.57710.060011
18-0.043999-0.34080.367216
19-0.094288-0.73040.234008
20-0.04253-0.32940.371487
210.0722720.55980.288843
220.0742780.57540.283602
230.0375980.29120.385938
24-0.070511-0.54620.293486
250.0581950.45080.326886
26-0.031515-0.24410.403986
27-0.074107-0.5740.284046
28-0.016719-0.12950.448696
29-0.092039-0.71290.239326
300.0356150.27590.391798
31-0.00328-0.02540.489906
32-0.153671-1.19030.119302
33-0.054296-0.42060.337784
34-0.015644-0.12120.451976
35-0.132669-1.02760.15412
360.0315610.24450.403852



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