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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 computationWed, 25 Nov 2009 12:08:54 -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/25/t1259176231tkq4ae0i2jlsh3d.htm/, Retrieved Wed, 08 May 2024 02:21:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59572, Retrieved Wed, 08 May 2024 02:21:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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 12:26:39] [b98453cac15ba1066b407e146608df68]
- R  D          [(Partial) Autocorrelation Function] [ACF Link 3] [2009-11-25 19:08:54] [026d431dc78a3ce53a040b5408fc0322] [Current]
-   PD            [(Partial) Autocorrelation Function] [review WS 8 autoc...] [2009-11-30 18:40:52] [12f02da0296cb21dc23d82ae014a8b71]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5250,0
3937,0
4004,0
5560,0
3922,0
3759,0
4138,0
4634,0
3996,0
4308,0
4143,0
4429,0
5219,0
4929,0
5755,0
5592,0
4163,0
4962,0
5208,0
4755,0
4491,0
5732,0
5731,0
5040,0
6102,0
4904,0
5369,0
5578,0
4619,0
4731,0
5011,0
5299,0
4146,0
4625,0
4736,0
4219,0
5116,0
4205,0
4121,0
5103,0
4300,0
4578,0
3809,0
5526,0
4247,0
3830,0
4394,0
4826,0
4409,0
4569,0
4106,0
4794,0
3914,0
3793,0
4405,0
4022,0
4100,0
4788,0
3163,0
3585,0
3903,0

Tables (Output of Computation)





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=59572&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=59572&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59572&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.372967-2.5840.006433
2-0.340915-2.36190.011142
30.2911812.01740.024634
40.0787740.54580.293878
5-0.164526-1.13990.129999
6-0.07345-0.50890.306586
70.1681381.16490.124909
80.0120160.08320.467001
9-0.168575-1.16790.124304
100.2496641.72970.045053
11-0.072002-0.49880.310084
12-0.255633-1.77110.041449
130.2153071.49170.071162
14-0.009583-0.06640.47367
15-0.086835-0.60160.275133
16-0.034596-0.23970.405795
170.0925660.64130.262184
18-0.033412-0.23150.408961
190.0365680.25330.400541
20-0.050074-0.34690.365084
21-0.067705-0.46910.32057
220.0639620.44310.329828
230.1303330.9030.185524
24-0.252941-1.75240.043043
250.0427950.29650.384068
260.205391.4230.080604
27-0.048944-0.33910.368009
28-0.164978-1.1430.129353
290.1139420.78940.216876
300.116790.80910.211212
31-0.207994-1.4410.078035
320.0345770.23960.405847
330.1497431.03740.152363
34-0.137109-0.94990.173455
350.023160.16050.436596
360.1132490.78460.218268

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.372967 & -2.584 & 0.006433 \tabularnewline
2 & -0.340915 & -2.3619 & 0.011142 \tabularnewline
3 & 0.291181 & 2.0174 & 0.024634 \tabularnewline
4 & 0.078774 & 0.5458 & 0.293878 \tabularnewline
5 & -0.164526 & -1.1399 & 0.129999 \tabularnewline
6 & -0.07345 & -0.5089 & 0.306586 \tabularnewline
7 & 0.168138 & 1.1649 & 0.124909 \tabularnewline
8 & 0.012016 & 0.0832 & 0.467001 \tabularnewline
9 & -0.168575 & -1.1679 & 0.124304 \tabularnewline
10 & 0.249664 & 1.7297 & 0.045053 \tabularnewline
11 & -0.072002 & -0.4988 & 0.310084 \tabularnewline
12 & -0.255633 & -1.7711 & 0.041449 \tabularnewline
13 & 0.215307 & 1.4917 & 0.071162 \tabularnewline
14 & -0.009583 & -0.0664 & 0.47367 \tabularnewline
15 & -0.086835 & -0.6016 & 0.275133 \tabularnewline
16 & -0.034596 & -0.2397 & 0.405795 \tabularnewline
17 & 0.092566 & 0.6413 & 0.262184 \tabularnewline
18 & -0.033412 & -0.2315 & 0.408961 \tabularnewline
19 & 0.036568 & 0.2533 & 0.400541 \tabularnewline
20 & -0.050074 & -0.3469 & 0.365084 \tabularnewline
21 & -0.067705 & -0.4691 & 0.32057 \tabularnewline
22 & 0.063962 & 0.4431 & 0.329828 \tabularnewline
23 & 0.130333 & 0.903 & 0.185524 \tabularnewline
24 & -0.252941 & -1.7524 & 0.043043 \tabularnewline
25 & 0.042795 & 0.2965 & 0.384068 \tabularnewline
26 & 0.20539 & 1.423 & 0.080604 \tabularnewline
27 & -0.048944 & -0.3391 & 0.368009 \tabularnewline
28 & -0.164978 & -1.143 & 0.129353 \tabularnewline
29 & 0.113942 & 0.7894 & 0.216876 \tabularnewline
30 & 0.11679 & 0.8091 & 0.211212 \tabularnewline
31 & -0.207994 & -1.441 & 0.078035 \tabularnewline
32 & 0.034577 & 0.2396 & 0.405847 \tabularnewline
33 & 0.149743 & 1.0374 & 0.152363 \tabularnewline
34 & -0.137109 & -0.9499 & 0.173455 \tabularnewline
35 & 0.02316 & 0.1605 & 0.436596 \tabularnewline
36 & 0.113249 & 0.7846 & 0.218268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59572&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]-0.372967[/C][C]-2.584[/C][C]0.006433[/C][/ROW]
[ROW][C]2[/C][C]-0.340915[/C][C]-2.3619[/C][C]0.011142[/C][/ROW]
[ROW][C]3[/C][C]0.291181[/C][C]2.0174[/C][C]0.024634[/C][/ROW]
[ROW][C]4[/C][C]0.078774[/C][C]0.5458[/C][C]0.293878[/C][/ROW]
[ROW][C]5[/C][C]-0.164526[/C][C]-1.1399[/C][C]0.129999[/C][/ROW]
[ROW][C]6[/C][C]-0.07345[/C][C]-0.5089[/C][C]0.306586[/C][/ROW]
[ROW][C]7[/C][C]0.168138[/C][C]1.1649[/C][C]0.124909[/C][/ROW]
[ROW][C]8[/C][C]0.012016[/C][C]0.0832[/C][C]0.467001[/C][/ROW]
[ROW][C]9[/C][C]-0.168575[/C][C]-1.1679[/C][C]0.124304[/C][/ROW]
[ROW][C]10[/C][C]0.249664[/C][C]1.7297[/C][C]0.045053[/C][/ROW]
[ROW][C]11[/C][C]-0.072002[/C][C]-0.4988[/C][C]0.310084[/C][/ROW]
[ROW][C]12[/C][C]-0.255633[/C][C]-1.7711[/C][C]0.041449[/C][/ROW]
[ROW][C]13[/C][C]0.215307[/C][C]1.4917[/C][C]0.071162[/C][/ROW]
[ROW][C]14[/C][C]-0.009583[/C][C]-0.0664[/C][C]0.47367[/C][/ROW]
[ROW][C]15[/C][C]-0.086835[/C][C]-0.6016[/C][C]0.275133[/C][/ROW]
[ROW][C]16[/C][C]-0.034596[/C][C]-0.2397[/C][C]0.405795[/C][/ROW]
[ROW][C]17[/C][C]0.092566[/C][C]0.6413[/C][C]0.262184[/C][/ROW]
[ROW][C]18[/C][C]-0.033412[/C][C]-0.2315[/C][C]0.408961[/C][/ROW]
[ROW][C]19[/C][C]0.036568[/C][C]0.2533[/C][C]0.400541[/C][/ROW]
[ROW][C]20[/C][C]-0.050074[/C][C]-0.3469[/C][C]0.365084[/C][/ROW]
[ROW][C]21[/C][C]-0.067705[/C][C]-0.4691[/C][C]0.32057[/C][/ROW]
[ROW][C]22[/C][C]0.063962[/C][C]0.4431[/C][C]0.329828[/C][/ROW]
[ROW][C]23[/C][C]0.130333[/C][C]0.903[/C][C]0.185524[/C][/ROW]
[ROW][C]24[/C][C]-0.252941[/C][C]-1.7524[/C][C]0.043043[/C][/ROW]
[ROW][C]25[/C][C]0.042795[/C][C]0.2965[/C][C]0.384068[/C][/ROW]
[ROW][C]26[/C][C]0.20539[/C][C]1.423[/C][C]0.080604[/C][/ROW]
[ROW][C]27[/C][C]-0.048944[/C][C]-0.3391[/C][C]0.368009[/C][/ROW]
[ROW][C]28[/C][C]-0.164978[/C][C]-1.143[/C][C]0.129353[/C][/ROW]
[ROW][C]29[/C][C]0.113942[/C][C]0.7894[/C][C]0.216876[/C][/ROW]
[ROW][C]30[/C][C]0.11679[/C][C]0.8091[/C][C]0.211212[/C][/ROW]
[ROW][C]31[/C][C]-0.207994[/C][C]-1.441[/C][C]0.078035[/C][/ROW]
[ROW][C]32[/C][C]0.034577[/C][C]0.2396[/C][C]0.405847[/C][/ROW]
[ROW][C]33[/C][C]0.149743[/C][C]1.0374[/C][C]0.152363[/C][/ROW]
[ROW][C]34[/C][C]-0.137109[/C][C]-0.9499[/C][C]0.173455[/C][/ROW]
[ROW][C]35[/C][C]0.02316[/C][C]0.1605[/C][C]0.436596[/C][/ROW]
[ROW][C]36[/C][C]0.113249[/C][C]0.7846[/C][C]0.218268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59572&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59572&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
1-0.372967-2.5840.006433
2-0.340915-2.36190.011142
30.2911812.01740.024634
40.0787740.54580.293878
5-0.164526-1.13990.129999
6-0.07345-0.50890.306586
70.1681381.16490.124909
80.0120160.08320.467001
9-0.168575-1.16790.124304
100.2496641.72970.045053
11-0.072002-0.49880.310084
12-0.255633-1.77110.041449
130.2153071.49170.071162
14-0.009583-0.06640.47367
15-0.086835-0.60160.275133
16-0.034596-0.23970.405795
170.0925660.64130.262184
18-0.033412-0.23150.408961
190.0365680.25330.400541
20-0.050074-0.34690.365084
21-0.067705-0.46910.32057
220.0639620.44310.329828
230.1303330.9030.185524
24-0.252941-1.75240.043043
250.0427950.29650.384068
260.205391.4230.080604
27-0.048944-0.33910.368009
28-0.164978-1.1430.129353
290.1139420.78940.216876
300.116790.80910.211212
31-0.207994-1.4410.078035
320.0345770.23960.405847
330.1497431.03740.152363
34-0.137109-0.94990.173455
350.023160.16050.436596
360.1132490.78460.218268






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.372967-2.5840.006433
2-0.557581-3.8630.000168
3-0.193553-1.3410.09312
4-0.037224-0.25790.398796
50.0071120.04930.480453
6-0.139014-0.96310.170158
7-0.04189-0.29020.386448
80.0176520.12230.451587
9-0.058104-0.40260.34453
100.2823621.95630.028133
110.1448941.00390.160241
12-0.137826-0.95490.17221
13-0.090992-0.63040.265707
14-0.214195-1.4840.072175
15-0.085407-0.59170.278409
16-0.144535-1.00140.160835
17-0.130308-0.90280.18557
18-0.276307-1.91430.030776
190.027010.18710.426174
20-0.034101-0.23630.407119
21-0.093982-0.65110.259034
220.0017640.01220.49515
230.1761571.22040.114128
24-0.115226-0.79830.214312
25-0.090088-0.62410.267743
26-0.040581-0.28120.389901
270.0673490.46660.321447
28-0.015148-0.10490.458426
29-0.012495-0.08660.465688
300.0046060.03190.487337
31-0.049467-0.34270.366654
32-0.060424-0.41860.338678
33-0.065686-0.45510.32555
34-0.089496-0.620.269079
350.0574480.3980.346194
36-0.065273-0.45220.326573

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.372967 & -2.584 & 0.006433 \tabularnewline
2 & -0.557581 & -3.863 & 0.000168 \tabularnewline
3 & -0.193553 & -1.341 & 0.09312 \tabularnewline
4 & -0.037224 & -0.2579 & 0.398796 \tabularnewline
5 & 0.007112 & 0.0493 & 0.480453 \tabularnewline
6 & -0.139014 & -0.9631 & 0.170158 \tabularnewline
7 & -0.04189 & -0.2902 & 0.386448 \tabularnewline
8 & 0.017652 & 0.1223 & 0.451587 \tabularnewline
9 & -0.058104 & -0.4026 & 0.34453 \tabularnewline
10 & 0.282362 & 1.9563 & 0.028133 \tabularnewline
11 & 0.144894 & 1.0039 & 0.160241 \tabularnewline
12 & -0.137826 & -0.9549 & 0.17221 \tabularnewline
13 & -0.090992 & -0.6304 & 0.265707 \tabularnewline
14 & -0.214195 & -1.484 & 0.072175 \tabularnewline
15 & -0.085407 & -0.5917 & 0.278409 \tabularnewline
16 & -0.144535 & -1.0014 & 0.160835 \tabularnewline
17 & -0.130308 & -0.9028 & 0.18557 \tabularnewline
18 & -0.276307 & -1.9143 & 0.030776 \tabularnewline
19 & 0.02701 & 0.1871 & 0.426174 \tabularnewline
20 & -0.034101 & -0.2363 & 0.407119 \tabularnewline
21 & -0.093982 & -0.6511 & 0.259034 \tabularnewline
22 & 0.001764 & 0.0122 & 0.49515 \tabularnewline
23 & 0.176157 & 1.2204 & 0.114128 \tabularnewline
24 & -0.115226 & -0.7983 & 0.214312 \tabularnewline
25 & -0.090088 & -0.6241 & 0.267743 \tabularnewline
26 & -0.040581 & -0.2812 & 0.389901 \tabularnewline
27 & 0.067349 & 0.4666 & 0.321447 \tabularnewline
28 & -0.015148 & -0.1049 & 0.458426 \tabularnewline
29 & -0.012495 & -0.0866 & 0.465688 \tabularnewline
30 & 0.004606 & 0.0319 & 0.487337 \tabularnewline
31 & -0.049467 & -0.3427 & 0.366654 \tabularnewline
32 & -0.060424 & -0.4186 & 0.338678 \tabularnewline
33 & -0.065686 & -0.4551 & 0.32555 \tabularnewline
34 & -0.089496 & -0.62 & 0.269079 \tabularnewline
35 & 0.057448 & 0.398 & 0.346194 \tabularnewline
36 & -0.065273 & -0.4522 & 0.326573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59572&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]-0.372967[/C][C]-2.584[/C][C]0.006433[/C][/ROW]
[ROW][C]2[/C][C]-0.557581[/C][C]-3.863[/C][C]0.000168[/C][/ROW]
[ROW][C]3[/C][C]-0.193553[/C][C]-1.341[/C][C]0.09312[/C][/ROW]
[ROW][C]4[/C][C]-0.037224[/C][C]-0.2579[/C][C]0.398796[/C][/ROW]
[ROW][C]5[/C][C]0.007112[/C][C]0.0493[/C][C]0.480453[/C][/ROW]
[ROW][C]6[/C][C]-0.139014[/C][C]-0.9631[/C][C]0.170158[/C][/ROW]
[ROW][C]7[/C][C]-0.04189[/C][C]-0.2902[/C][C]0.386448[/C][/ROW]
[ROW][C]8[/C][C]0.017652[/C][C]0.1223[/C][C]0.451587[/C][/ROW]
[ROW][C]9[/C][C]-0.058104[/C][C]-0.4026[/C][C]0.34453[/C][/ROW]
[ROW][C]10[/C][C]0.282362[/C][C]1.9563[/C][C]0.028133[/C][/ROW]
[ROW][C]11[/C][C]0.144894[/C][C]1.0039[/C][C]0.160241[/C][/ROW]
[ROW][C]12[/C][C]-0.137826[/C][C]-0.9549[/C][C]0.17221[/C][/ROW]
[ROW][C]13[/C][C]-0.090992[/C][C]-0.6304[/C][C]0.265707[/C][/ROW]
[ROW][C]14[/C][C]-0.214195[/C][C]-1.484[/C][C]0.072175[/C][/ROW]
[ROW][C]15[/C][C]-0.085407[/C][C]-0.5917[/C][C]0.278409[/C][/ROW]
[ROW][C]16[/C][C]-0.144535[/C][C]-1.0014[/C][C]0.160835[/C][/ROW]
[ROW][C]17[/C][C]-0.130308[/C][C]-0.9028[/C][C]0.18557[/C][/ROW]
[ROW][C]18[/C][C]-0.276307[/C][C]-1.9143[/C][C]0.030776[/C][/ROW]
[ROW][C]19[/C][C]0.02701[/C][C]0.1871[/C][C]0.426174[/C][/ROW]
[ROW][C]20[/C][C]-0.034101[/C][C]-0.2363[/C][C]0.407119[/C][/ROW]
[ROW][C]21[/C][C]-0.093982[/C][C]-0.6511[/C][C]0.259034[/C][/ROW]
[ROW][C]22[/C][C]0.001764[/C][C]0.0122[/C][C]0.49515[/C][/ROW]
[ROW][C]23[/C][C]0.176157[/C][C]1.2204[/C][C]0.114128[/C][/ROW]
[ROW][C]24[/C][C]-0.115226[/C][C]-0.7983[/C][C]0.214312[/C][/ROW]
[ROW][C]25[/C][C]-0.090088[/C][C]-0.6241[/C][C]0.267743[/C][/ROW]
[ROW][C]26[/C][C]-0.040581[/C][C]-0.2812[/C][C]0.389901[/C][/ROW]
[ROW][C]27[/C][C]0.067349[/C][C]0.4666[/C][C]0.321447[/C][/ROW]
[ROW][C]28[/C][C]-0.015148[/C][C]-0.1049[/C][C]0.458426[/C][/ROW]
[ROW][C]29[/C][C]-0.012495[/C][C]-0.0866[/C][C]0.465688[/C][/ROW]
[ROW][C]30[/C][C]0.004606[/C][C]0.0319[/C][C]0.487337[/C][/ROW]
[ROW][C]31[/C][C]-0.049467[/C][C]-0.3427[/C][C]0.366654[/C][/ROW]
[ROW][C]32[/C][C]-0.060424[/C][C]-0.4186[/C][C]0.338678[/C][/ROW]
[ROW][C]33[/C][C]-0.065686[/C][C]-0.4551[/C][C]0.32555[/C][/ROW]
[ROW][C]34[/C][C]-0.089496[/C][C]-0.62[/C][C]0.269079[/C][/ROW]
[ROW][C]35[/C][C]0.057448[/C][C]0.398[/C][C]0.346194[/C][/ROW]
[ROW][C]36[/C][C]-0.065273[/C][C]-0.4522[/C][C]0.326573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59572&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59572&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
1-0.372967-2.5840.006433
2-0.557581-3.8630.000168
3-0.193553-1.3410.09312
4-0.037224-0.25790.398796
50.0071120.04930.480453
6-0.139014-0.96310.170158
7-0.04189-0.29020.386448
80.0176520.12230.451587
9-0.058104-0.40260.34453
100.2823621.95630.028133
110.1448941.00390.160241
12-0.137826-0.95490.17221
13-0.090992-0.63040.265707
14-0.214195-1.4840.072175
15-0.085407-0.59170.278409
16-0.144535-1.00140.160835
17-0.130308-0.90280.18557
18-0.276307-1.91430.030776
190.027010.18710.426174
20-0.034101-0.23630.407119
21-0.093982-0.65110.259034
220.0017640.01220.49515
230.1761571.22040.114128
24-0.115226-0.79830.214312
25-0.090088-0.62410.267743
26-0.040581-0.28120.389901
270.0673490.46660.321447
28-0.015148-0.10490.458426
29-0.012495-0.08660.465688
300.0046060.03190.487337
31-0.049467-0.34270.366654
32-0.060424-0.41860.338678
33-0.065686-0.45510.32555
34-0.089496-0.620.269079
350.0574480.3980.346194
36-0.065273-0.45220.326573


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')