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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, 24 Nov 2009 11:28:26 -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/24/t125908745950nb5d6dgeuh1m5.htm/, Retrieved Sun, 03 Dec 2023 08:10:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59213, Retrieved Sun, 03 Dec 2023 08:10:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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]
- R PD          [(Partial) Autocorrelation Function] [autocorrelatie ; ...] [2009-11-24 18:28:26] [a931a0a30926b49d162330b43e89b999] [Current]
-                 [(Partial) Autocorrelation Function] [blog 9] [2009-12-07 21:18:11] [42ad1186d39724f834063794eac7cea3]
-                 [(Partial) Autocorrelation Function] [blog 10] [2009-12-07 21:23:48] [42ad1186d39724f834063794eac7cea3]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
310631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224

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=59213&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=59213&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59213&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
1-0.040762-0.28530.388295
2-0.023148-0.1620.435971
30.2267481.58720.059446
40.0691960.48440.315139
50.1014540.71020.24048
60.0245190.17160.432218
70.0124130.08690.465556
80.003580.02510.490054
90.0555620.38890.349505
10-0.046816-0.32770.372263
110.2933682.05360.022687
12-0.227324-1.59130.05899
130.0280540.19640.422563
140.2097741.46840.07419
15-0.051234-0.35860.360705
160.0572780.40090.345101
17-0.0344-0.24080.405357
18-0.005274-0.03690.485351
190.1002460.70170.243087
200.0958170.67070.252774
21-0.233688-1.63580.054143
22-0.006653-0.04660.481522
23-0.034444-0.24110.405239
24-0.0697-0.48790.313899
25-0.076954-0.53870.296275
26-0.147107-1.02970.154093
27-0.118322-0.82830.205772
28-0.101856-0.7130.239617
29-0.050066-0.35050.363746
30-0.052881-0.37020.356426
31-0.02535-0.17750.429942
32-0.112551-0.78790.217288
330.0342730.23990.4057
340.0219330.15350.439306
35-0.020688-0.14480.442724
36-0.015628-0.10940.456666

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.040762 & -0.2853 & 0.388295 \tabularnewline
2 & -0.023148 & -0.162 & 0.435971 \tabularnewline
3 & 0.226748 & 1.5872 & 0.059446 \tabularnewline
4 & 0.069196 & 0.4844 & 0.315139 \tabularnewline
5 & 0.101454 & 0.7102 & 0.24048 \tabularnewline
6 & 0.024519 & 0.1716 & 0.432218 \tabularnewline
7 & 0.012413 & 0.0869 & 0.465556 \tabularnewline
8 & 0.00358 & 0.0251 & 0.490054 \tabularnewline
9 & 0.055562 & 0.3889 & 0.349505 \tabularnewline
10 & -0.046816 & -0.3277 & 0.372263 \tabularnewline
11 & 0.293368 & 2.0536 & 0.022687 \tabularnewline
12 & -0.227324 & -1.5913 & 0.05899 \tabularnewline
13 & 0.028054 & 0.1964 & 0.422563 \tabularnewline
14 & 0.209774 & 1.4684 & 0.07419 \tabularnewline
15 & -0.051234 & -0.3586 & 0.360705 \tabularnewline
16 & 0.057278 & 0.4009 & 0.345101 \tabularnewline
17 & -0.0344 & -0.2408 & 0.405357 \tabularnewline
18 & -0.005274 & -0.0369 & 0.485351 \tabularnewline
19 & 0.100246 & 0.7017 & 0.243087 \tabularnewline
20 & 0.095817 & 0.6707 & 0.252774 \tabularnewline
21 & -0.233688 & -1.6358 & 0.054143 \tabularnewline
22 & -0.006653 & -0.0466 & 0.481522 \tabularnewline
23 & -0.034444 & -0.2411 & 0.405239 \tabularnewline
24 & -0.0697 & -0.4879 & 0.313899 \tabularnewline
25 & -0.076954 & -0.5387 & 0.296275 \tabularnewline
26 & -0.147107 & -1.0297 & 0.154093 \tabularnewline
27 & -0.118322 & -0.8283 & 0.205772 \tabularnewline
28 & -0.101856 & -0.713 & 0.239617 \tabularnewline
29 & -0.050066 & -0.3505 & 0.363746 \tabularnewline
30 & -0.052881 & -0.3702 & 0.356426 \tabularnewline
31 & -0.02535 & -0.1775 & 0.429942 \tabularnewline
32 & -0.112551 & -0.7879 & 0.217288 \tabularnewline
33 & 0.034273 & 0.2399 & 0.4057 \tabularnewline
34 & 0.021933 & 0.1535 & 0.439306 \tabularnewline
35 & -0.020688 & -0.1448 & 0.442724 \tabularnewline
36 & -0.015628 & -0.1094 & 0.456666 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59213&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]-0.040762[/C][C]-0.2853[/C][C]0.388295[/C][/ROW]
[ROW][C]2[/C][C]-0.023148[/C][C]-0.162[/C][C]0.435971[/C][/ROW]
[ROW][C]3[/C][C]0.226748[/C][C]1.5872[/C][C]0.059446[/C][/ROW]
[ROW][C]4[/C][C]0.069196[/C][C]0.4844[/C][C]0.315139[/C][/ROW]
[ROW][C]5[/C][C]0.101454[/C][C]0.7102[/C][C]0.24048[/C][/ROW]
[ROW][C]6[/C][C]0.024519[/C][C]0.1716[/C][C]0.432218[/C][/ROW]
[ROW][C]7[/C][C]0.012413[/C][C]0.0869[/C][C]0.465556[/C][/ROW]
[ROW][C]8[/C][C]0.00358[/C][C]0.0251[/C][C]0.490054[/C][/ROW]
[ROW][C]9[/C][C]0.055562[/C][C]0.3889[/C][C]0.349505[/C][/ROW]
[ROW][C]10[/C][C]-0.046816[/C][C]-0.3277[/C][C]0.372263[/C][/ROW]
[ROW][C]11[/C][C]0.293368[/C][C]2.0536[/C][C]0.022687[/C][/ROW]
[ROW][C]12[/C][C]-0.227324[/C][C]-1.5913[/C][C]0.05899[/C][/ROW]
[ROW][C]13[/C][C]0.028054[/C][C]0.1964[/C][C]0.422563[/C][/ROW]
[ROW][C]14[/C][C]0.209774[/C][C]1.4684[/C][C]0.07419[/C][/ROW]
[ROW][C]15[/C][C]-0.051234[/C][C]-0.3586[/C][C]0.360705[/C][/ROW]
[ROW][C]16[/C][C]0.057278[/C][C]0.4009[/C][C]0.345101[/C][/ROW]
[ROW][C]17[/C][C]-0.0344[/C][C]-0.2408[/C][C]0.405357[/C][/ROW]
[ROW][C]18[/C][C]-0.005274[/C][C]-0.0369[/C][C]0.485351[/C][/ROW]
[ROW][C]19[/C][C]0.100246[/C][C]0.7017[/C][C]0.243087[/C][/ROW]
[ROW][C]20[/C][C]0.095817[/C][C]0.6707[/C][C]0.252774[/C][/ROW]
[ROW][C]21[/C][C]-0.233688[/C][C]-1.6358[/C][C]0.054143[/C][/ROW]
[ROW][C]22[/C][C]-0.006653[/C][C]-0.0466[/C][C]0.481522[/C][/ROW]
[ROW][C]23[/C][C]-0.034444[/C][C]-0.2411[/C][C]0.405239[/C][/ROW]
[ROW][C]24[/C][C]-0.0697[/C][C]-0.4879[/C][C]0.313899[/C][/ROW]
[ROW][C]25[/C][C]-0.076954[/C][C]-0.5387[/C][C]0.296275[/C][/ROW]
[ROW][C]26[/C][C]-0.147107[/C][C]-1.0297[/C][C]0.154093[/C][/ROW]
[ROW][C]27[/C][C]-0.118322[/C][C]-0.8283[/C][C]0.205772[/C][/ROW]
[ROW][C]28[/C][C]-0.101856[/C][C]-0.713[/C][C]0.239617[/C][/ROW]
[ROW][C]29[/C][C]-0.050066[/C][C]-0.3505[/C][C]0.363746[/C][/ROW]
[ROW][C]30[/C][C]-0.052881[/C][C]-0.3702[/C][C]0.356426[/C][/ROW]
[ROW][C]31[/C][C]-0.02535[/C][C]-0.1775[/C][C]0.429942[/C][/ROW]
[ROW][C]32[/C][C]-0.112551[/C][C]-0.7879[/C][C]0.217288[/C][/ROW]
[ROW][C]33[/C][C]0.034273[/C][C]0.2399[/C][C]0.4057[/C][/ROW]
[ROW][C]34[/C][C]0.021933[/C][C]0.1535[/C][C]0.439306[/C][/ROW]
[ROW][C]35[/C][C]-0.020688[/C][C]-0.1448[/C][C]0.442724[/C][/ROW]
[ROW][C]36[/C][C]-0.015628[/C][C]-0.1094[/C][C]0.456666[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59213&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59213&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
1-0.040762-0.28530.388295
2-0.023148-0.1620.435971
30.2267481.58720.059446
40.0691960.48440.315139
50.1014540.71020.24048
60.0245190.17160.432218
70.0124130.08690.465556
80.003580.02510.490054
90.0555620.38890.349505
10-0.046816-0.32770.372263
110.2933682.05360.022687
12-0.227324-1.59130.05899
130.0280540.19640.422563
140.2097741.46840.07419
15-0.051234-0.35860.360705
160.0572780.40090.345101
17-0.0344-0.24080.405357
18-0.005274-0.03690.485351
190.1002460.70170.243087
200.0958170.67070.252774
21-0.233688-1.63580.054143
22-0.006653-0.04660.481522
23-0.034444-0.24110.405239
24-0.0697-0.48790.313899
25-0.076954-0.53870.296275
26-0.147107-1.02970.154093
27-0.118322-0.82830.205772
28-0.101856-0.7130.239617
29-0.050066-0.35050.363746
30-0.052881-0.37020.356426
31-0.02535-0.17750.429942
32-0.112551-0.78790.217288
330.0342730.23990.4057
340.0219330.15350.439306
35-0.020688-0.14480.442724
36-0.015628-0.10940.456666






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.040762-0.28530.388295
2-0.024851-0.1740.431307
30.2252821.5770.060619
40.0910420.63730.263449
50.1251670.87620.192607
6-0.011332-0.07930.468548
7-0.019021-0.13310.447312
8-0.059096-0.41370.340459
90.032930.23050.409326
10-0.06047-0.42330.336969
110.3283492.29840.012921
12-0.263554-1.84490.035552
130.1020910.71460.239113
140.0295460.20680.418503
150.0547420.38320.351617
160.001730.01210.495194
17-0.037804-0.26460.396203
18-0.06641-0.46490.322042
190.1299090.90940.183806
200.041960.29370.385105
21-0.190882-1.33620.093833
22-0.164912-1.15440.126971
230.0410550.28740.387514
24-0.102185-0.71530.23891
25-0.114039-0.79830.214283
26-0.032382-0.22670.41081
27-0.172714-1.2090.116233
28-0.02281-0.15970.436898
29-0.049935-0.34950.36409
30-0.02948-0.20640.418683
310.0347670.24340.404369
320.1095130.76660.223501
33-0.056598-0.39620.346845
340.0146770.10270.459294
350.1096610.76760.223196
360.0554840.38840.349707

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.040762 & -0.2853 & 0.388295 \tabularnewline
2 & -0.024851 & -0.174 & 0.431307 \tabularnewline
3 & 0.225282 & 1.577 & 0.060619 \tabularnewline
4 & 0.091042 & 0.6373 & 0.263449 \tabularnewline
5 & 0.125167 & 0.8762 & 0.192607 \tabularnewline
6 & -0.011332 & -0.0793 & 0.468548 \tabularnewline
7 & -0.019021 & -0.1331 & 0.447312 \tabularnewline
8 & -0.059096 & -0.4137 & 0.340459 \tabularnewline
9 & 0.03293 & 0.2305 & 0.409326 \tabularnewline
10 & -0.06047 & -0.4233 & 0.336969 \tabularnewline
11 & 0.328349 & 2.2984 & 0.012921 \tabularnewline
12 & -0.263554 & -1.8449 & 0.035552 \tabularnewline
13 & 0.102091 & 0.7146 & 0.239113 \tabularnewline
14 & 0.029546 & 0.2068 & 0.418503 \tabularnewline
15 & 0.054742 & 0.3832 & 0.351617 \tabularnewline
16 & 0.00173 & 0.0121 & 0.495194 \tabularnewline
17 & -0.037804 & -0.2646 & 0.396203 \tabularnewline
18 & -0.06641 & -0.4649 & 0.322042 \tabularnewline
19 & 0.129909 & 0.9094 & 0.183806 \tabularnewline
20 & 0.04196 & 0.2937 & 0.385105 \tabularnewline
21 & -0.190882 & -1.3362 & 0.093833 \tabularnewline
22 & -0.164912 & -1.1544 & 0.126971 \tabularnewline
23 & 0.041055 & 0.2874 & 0.387514 \tabularnewline
24 & -0.102185 & -0.7153 & 0.23891 \tabularnewline
25 & -0.114039 & -0.7983 & 0.214283 \tabularnewline
26 & -0.032382 & -0.2267 & 0.41081 \tabularnewline
27 & -0.172714 & -1.209 & 0.116233 \tabularnewline
28 & -0.02281 & -0.1597 & 0.436898 \tabularnewline
29 & -0.049935 & -0.3495 & 0.36409 \tabularnewline
30 & -0.02948 & -0.2064 & 0.418683 \tabularnewline
31 & 0.034767 & 0.2434 & 0.404369 \tabularnewline
32 & 0.109513 & 0.7666 & 0.223501 \tabularnewline
33 & -0.056598 & -0.3962 & 0.346845 \tabularnewline
34 & 0.014677 & 0.1027 & 0.459294 \tabularnewline
35 & 0.109661 & 0.7676 & 0.223196 \tabularnewline
36 & 0.055484 & 0.3884 & 0.349707 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59213&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]-0.040762[/C][C]-0.2853[/C][C]0.388295[/C][/ROW]
[ROW][C]2[/C][C]-0.024851[/C][C]-0.174[/C][C]0.431307[/C][/ROW]
[ROW][C]3[/C][C]0.225282[/C][C]1.577[/C][C]0.060619[/C][/ROW]
[ROW][C]4[/C][C]0.091042[/C][C]0.6373[/C][C]0.263449[/C][/ROW]
[ROW][C]5[/C][C]0.125167[/C][C]0.8762[/C][C]0.192607[/C][/ROW]
[ROW][C]6[/C][C]-0.011332[/C][C]-0.0793[/C][C]0.468548[/C][/ROW]
[ROW][C]7[/C][C]-0.019021[/C][C]-0.1331[/C][C]0.447312[/C][/ROW]
[ROW][C]8[/C][C]-0.059096[/C][C]-0.4137[/C][C]0.340459[/C][/ROW]
[ROW][C]9[/C][C]0.03293[/C][C]0.2305[/C][C]0.409326[/C][/ROW]
[ROW][C]10[/C][C]-0.06047[/C][C]-0.4233[/C][C]0.336969[/C][/ROW]
[ROW][C]11[/C][C]0.328349[/C][C]2.2984[/C][C]0.012921[/C][/ROW]
[ROW][C]12[/C][C]-0.263554[/C][C]-1.8449[/C][C]0.035552[/C][/ROW]
[ROW][C]13[/C][C]0.102091[/C][C]0.7146[/C][C]0.239113[/C][/ROW]
[ROW][C]14[/C][C]0.029546[/C][C]0.2068[/C][C]0.418503[/C][/ROW]
[ROW][C]15[/C][C]0.054742[/C][C]0.3832[/C][C]0.351617[/C][/ROW]
[ROW][C]16[/C][C]0.00173[/C][C]0.0121[/C][C]0.495194[/C][/ROW]
[ROW][C]17[/C][C]-0.037804[/C][C]-0.2646[/C][C]0.396203[/C][/ROW]
[ROW][C]18[/C][C]-0.06641[/C][C]-0.4649[/C][C]0.322042[/C][/ROW]
[ROW][C]19[/C][C]0.129909[/C][C]0.9094[/C][C]0.183806[/C][/ROW]
[ROW][C]20[/C][C]0.04196[/C][C]0.2937[/C][C]0.385105[/C][/ROW]
[ROW][C]21[/C][C]-0.190882[/C][C]-1.3362[/C][C]0.093833[/C][/ROW]
[ROW][C]22[/C][C]-0.164912[/C][C]-1.1544[/C][C]0.126971[/C][/ROW]
[ROW][C]23[/C][C]0.041055[/C][C]0.2874[/C][C]0.387514[/C][/ROW]
[ROW][C]24[/C][C]-0.102185[/C][C]-0.7153[/C][C]0.23891[/C][/ROW]
[ROW][C]25[/C][C]-0.114039[/C][C]-0.7983[/C][C]0.214283[/C][/ROW]
[ROW][C]26[/C][C]-0.032382[/C][C]-0.2267[/C][C]0.41081[/C][/ROW]
[ROW][C]27[/C][C]-0.172714[/C][C]-1.209[/C][C]0.116233[/C][/ROW]
[ROW][C]28[/C][C]-0.02281[/C][C]-0.1597[/C][C]0.436898[/C][/ROW]
[ROW][C]29[/C][C]-0.049935[/C][C]-0.3495[/C][C]0.36409[/C][/ROW]
[ROW][C]30[/C][C]-0.02948[/C][C]-0.2064[/C][C]0.418683[/C][/ROW]
[ROW][C]31[/C][C]0.034767[/C][C]0.2434[/C][C]0.404369[/C][/ROW]
[ROW][C]32[/C][C]0.109513[/C][C]0.7666[/C][C]0.223501[/C][/ROW]
[ROW][C]33[/C][C]-0.056598[/C][C]-0.3962[/C][C]0.346845[/C][/ROW]
[ROW][C]34[/C][C]0.014677[/C][C]0.1027[/C][C]0.459294[/C][/ROW]
[ROW][C]35[/C][C]0.109661[/C][C]0.7676[/C][C]0.223196[/C][/ROW]
[ROW][C]36[/C][C]0.055484[/C][C]0.3884[/C][C]0.349707[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59213&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59213&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
1-0.040762-0.28530.388295
2-0.024851-0.1740.431307
30.2252821.5770.060619
40.0910420.63730.263449
50.1251670.87620.192607
6-0.011332-0.07930.468548
7-0.019021-0.13310.447312
8-0.059096-0.41370.340459
90.032930.23050.409326
10-0.06047-0.42330.336969
110.3283492.29840.012921
12-0.263554-1.84490.035552
130.1020910.71460.239113
140.0295460.20680.418503
150.0547420.38320.351617
160.001730.01210.495194
17-0.037804-0.26460.396203
18-0.06641-0.46490.322042
190.1299090.90940.183806
200.041960.29370.385105
21-0.190882-1.33620.093833
22-0.164912-1.15440.126971
230.0410550.28740.387514
24-0.102185-0.71530.23891
25-0.114039-0.79830.214283
26-0.032382-0.22670.41081
27-0.172714-1.2090.116233
28-0.02281-0.15970.436898
29-0.049935-0.34950.36409
30-0.02948-0.20640.418683
310.0347670.24340.404369
320.1095130.76660.223501
33-0.056598-0.39620.346845
340.0146770.10270.459294
350.1096610.76760.223196
360.0554840.38840.349707


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')