Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 22 Nov 2010 14:55:56 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/22/t1290437813qxmydcu2egtgc5k.htm/, Retrieved Fri, 03 May 2024 18:36:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98563, Retrieved Fri, 03 May 2024 18:36:46 +0000
QR Codes:

Original text written by user:Bij de eerste blog had ik getypt: opdracht 6 bis oefening 2 stap 2. Maar dit moest stap 1 zijn. Deze blog is dus de juiste blog. De unieke link staat in de paper. MVG Nicolas Norga
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean versus Median] [opdracht 5 oefeni...] [2010-10-19 09:27:19] [544c47be79b2f5f4be445678c64cc68d]
- RMPD    [(Partial) Autocorrelation Function] [opdracht 6 bis oe...] [2010-11-22 14:55:56] [72a344459e5b13eacf7bf474aa92c893] [Current]
Feedback Forum

Post a new message
Dataseries X:
132.1
125
127.1
101.5
85.7
79.3
70.9
77.1
83.9
96.2
111.7
127.2
143.6
134.9
135.6
105.3
86.4
74.6
67.6
73.4
78.5
98.2
118.6
136.9
137.9
115.6
119.3
98.5
84.3
73.5
60.7
69.5
77.9
113.9
126.3
135.1
130.5
113.1
110
90.8
85.4
72.5
64.7
67.2
77.9
105.2
107.2
120.7
121.3
107.9
105.6
81.3
71.7
64.8
57.3
61.9
70.1
88.8
106.8
110.7
114.1
108
111.5
86.8
78.4
68
57.3
65.3
73.3
88.6
101.3
122.9
126.6
114.1
124.7
93.3
77.2
66.5
57.9
63.7
65.8
85
101
105.3
121
117.9
106
86.6
79.9
65.2
61.2
67.6
78.9
95.5
113.1
124.4
122
110.3
114
93.3
75.5
65.4
59.2
63.8
74.2
91.7
107
120.7
127.4
119.7
112.7
84.4
75.6
66.5
59.9
64.8
74.3
100.4
105.9
131.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98563&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]3 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=98563&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98563&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8138318.91510
20.4802615.2610
30.0180670.19790.421724
4-0.418669-4.58636e-06
5-0.707115-7.74610
6-0.816313-8.94230
7-0.670003-7.33950
8-0.366876-4.01895.1e-05
90.0696990.76350.223327
100.483835.30010
110.7556898.27820
120.8523839.33740
130.6893617.55160
140.3895334.26712e-05
15-0.025969-0.28450.388268
16-0.402845-4.41291.1e-05
17-0.646967-7.08720
18-0.730378-8.00090
19-0.586189-6.42140
20-0.305141-3.34270.000554
210.0773250.84710.199324
220.4191814.59195e-06
230.6441367.05620
240.7188637.87470
250.5688156.23110
260.3143863.44390.000395
27-0.034566-0.37860.352808
28-0.364922-3.99755.5e-05
29-0.576562-6.31590
30-0.646917-7.08660
31-0.513585-5.6260
32-0.272524-2.98540.001717
330.0573690.62840.265453
340.3499833.83390.000101
350.5363675.87560
360.5958986.52770

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.813831 & 8.9151 & 0 \tabularnewline
2 & 0.480261 & 5.261 & 0 \tabularnewline
3 & 0.018067 & 0.1979 & 0.421724 \tabularnewline
4 & -0.418669 & -4.5863 & 6e-06 \tabularnewline
5 & -0.707115 & -7.7461 & 0 \tabularnewline
6 & -0.816313 & -8.9423 & 0 \tabularnewline
7 & -0.670003 & -7.3395 & 0 \tabularnewline
8 & -0.366876 & -4.0189 & 5.1e-05 \tabularnewline
9 & 0.069699 & 0.7635 & 0.223327 \tabularnewline
10 & 0.48383 & 5.3001 & 0 \tabularnewline
11 & 0.755689 & 8.2782 & 0 \tabularnewline
12 & 0.852383 & 9.3374 & 0 \tabularnewline
13 & 0.689361 & 7.5516 & 0 \tabularnewline
14 & 0.389533 & 4.2671 & 2e-05 \tabularnewline
15 & -0.025969 & -0.2845 & 0.388268 \tabularnewline
16 & -0.402845 & -4.4129 & 1.1e-05 \tabularnewline
17 & -0.646967 & -7.0872 & 0 \tabularnewline
18 & -0.730378 & -8.0009 & 0 \tabularnewline
19 & -0.586189 & -6.4214 & 0 \tabularnewline
20 & -0.305141 & -3.3427 & 0.000554 \tabularnewline
21 & 0.077325 & 0.8471 & 0.199324 \tabularnewline
22 & 0.419181 & 4.5919 & 5e-06 \tabularnewline
23 & 0.644136 & 7.0562 & 0 \tabularnewline
24 & 0.718863 & 7.8747 & 0 \tabularnewline
25 & 0.568815 & 6.2311 & 0 \tabularnewline
26 & 0.314386 & 3.4439 & 0.000395 \tabularnewline
27 & -0.034566 & -0.3786 & 0.352808 \tabularnewline
28 & -0.364922 & -3.9975 & 5.5e-05 \tabularnewline
29 & -0.576562 & -6.3159 & 0 \tabularnewline
30 & -0.646917 & -7.0866 & 0 \tabularnewline
31 & -0.513585 & -5.626 & 0 \tabularnewline
32 & -0.272524 & -2.9854 & 0.001717 \tabularnewline
33 & 0.057369 & 0.6284 & 0.265453 \tabularnewline
34 & 0.349983 & 3.8339 & 0.000101 \tabularnewline
35 & 0.536367 & 5.8756 & 0 \tabularnewline
36 & 0.595898 & 6.5277 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98563&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]0.813831[/C][C]8.9151[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.480261[/C][C]5.261[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.018067[/C][C]0.1979[/C][C]0.421724[/C][/ROW]
[ROW][C]4[/C][C]-0.418669[/C][C]-4.5863[/C][C]6e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.707115[/C][C]-7.7461[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]-0.816313[/C][C]-8.9423[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.670003[/C][C]-7.3395[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]-0.366876[/C][C]-4.0189[/C][C]5.1e-05[/C][/ROW]
[ROW][C]9[/C][C]0.069699[/C][C]0.7635[/C][C]0.223327[/C][/ROW]
[ROW][C]10[/C][C]0.48383[/C][C]5.3001[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.755689[/C][C]8.2782[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.852383[/C][C]9.3374[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.689361[/C][C]7.5516[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.389533[/C][C]4.2671[/C][C]2e-05[/C][/ROW]
[ROW][C]15[/C][C]-0.025969[/C][C]-0.2845[/C][C]0.388268[/C][/ROW]
[ROW][C]16[/C][C]-0.402845[/C][C]-4.4129[/C][C]1.1e-05[/C][/ROW]
[ROW][C]17[/C][C]-0.646967[/C][C]-7.0872[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]-0.730378[/C][C]-8.0009[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.586189[/C][C]-6.4214[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]-0.305141[/C][C]-3.3427[/C][C]0.000554[/C][/ROW]
[ROW][C]21[/C][C]0.077325[/C][C]0.8471[/C][C]0.199324[/C][/ROW]
[ROW][C]22[/C][C]0.419181[/C][C]4.5919[/C][C]5e-06[/C][/ROW]
[ROW][C]23[/C][C]0.644136[/C][C]7.0562[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.718863[/C][C]7.8747[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.568815[/C][C]6.2311[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.314386[/C][C]3.4439[/C][C]0.000395[/C][/ROW]
[ROW][C]27[/C][C]-0.034566[/C][C]-0.3786[/C][C]0.352808[/C][/ROW]
[ROW][C]28[/C][C]-0.364922[/C][C]-3.9975[/C][C]5.5e-05[/C][/ROW]
[ROW][C]29[/C][C]-0.576562[/C][C]-6.3159[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]-0.646917[/C][C]-7.0866[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]-0.513585[/C][C]-5.626[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]-0.272524[/C][C]-2.9854[/C][C]0.001717[/C][/ROW]
[ROW][C]33[/C][C]0.057369[/C][C]0.6284[/C][C]0.265453[/C][/ROW]
[ROW][C]34[/C][C]0.349983[/C][C]3.8339[/C][C]0.000101[/C][/ROW]
[ROW][C]35[/C][C]0.536367[/C][C]5.8756[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.595898[/C][C]6.5277[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98563&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98563&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
10.8138318.91510
20.4802615.2610
30.0180670.19790.421724
4-0.418669-4.58636e-06
5-0.707115-7.74610
6-0.816313-8.94230
7-0.670003-7.33950
8-0.366876-4.01895.1e-05
90.0696990.76350.223327
100.483835.30010
110.7556898.27820
120.8523839.33740
130.6893617.55160
140.3895334.26712e-05
15-0.025969-0.28450.388268
16-0.402845-4.41291.1e-05
17-0.646967-7.08720
18-0.730378-8.00090
19-0.586189-6.42140
20-0.305141-3.34270.000554
210.0773250.84710.199324
220.4191814.59195e-06
230.6441367.05620
240.7188637.87470
250.5688156.23110
260.3143863.44390.000395
27-0.034566-0.37860.352808
28-0.364922-3.99755.5e-05
29-0.576562-6.31590
30-0.646917-7.08660
31-0.513585-5.6260
32-0.272524-2.98540.001717
330.0573690.62840.265453
340.3499833.83390.000101
350.5363675.87560
360.5958986.52770







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8138318.91510
2-0.539151-5.90610
3-0.604265-6.61940
4-0.31713-3.4740.000357
50.0192970.21140.41647
6-0.149321-1.63570.052258
70.1634171.79010.037976
80.0447360.49010.312493
90.3144413.44450.000394
100.2232372.44540.00796
11-0.006382-0.06990.472192
120.1903272.08490.019598
13-0.045884-0.50260.308073
140.1625421.78060.038758
150.0041450.04540.48193
160.0560430.61390.270214
170.1331461.45850.073652
18-0.081778-0.89580.186068
19-0.035019-0.38360.35097
200.0076420.08370.46671
21-0.009641-0.10560.458034
22-0.093796-1.02750.153131
23-0.059742-0.65440.25704
240.1172141.2840.100806
25-0.107875-1.18170.119829
260.0445620.48810.313167
270.0476230.52170.301427
28-0.158477-1.7360.042562
290.0421530.46180.322543
30-0.037474-0.41050.341084
310.024870.27240.392876
32-0.011358-0.12440.450595
33-0.046581-0.51030.3054
34-0.029799-0.32640.372333
35-0.071853-0.78710.216383
360.0033670.03690.485317

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.813831 & 8.9151 & 0 \tabularnewline
2 & -0.539151 & -5.9061 & 0 \tabularnewline
3 & -0.604265 & -6.6194 & 0 \tabularnewline
4 & -0.31713 & -3.474 & 0.000357 \tabularnewline
5 & 0.019297 & 0.2114 & 0.41647 \tabularnewline
6 & -0.149321 & -1.6357 & 0.052258 \tabularnewline
7 & 0.163417 & 1.7901 & 0.037976 \tabularnewline
8 & 0.044736 & 0.4901 & 0.312493 \tabularnewline
9 & 0.314441 & 3.4445 & 0.000394 \tabularnewline
10 & 0.223237 & 2.4454 & 0.00796 \tabularnewline
11 & -0.006382 & -0.0699 & 0.472192 \tabularnewline
12 & 0.190327 & 2.0849 & 0.019598 \tabularnewline
13 & -0.045884 & -0.5026 & 0.308073 \tabularnewline
14 & 0.162542 & 1.7806 & 0.038758 \tabularnewline
15 & 0.004145 & 0.0454 & 0.48193 \tabularnewline
16 & 0.056043 & 0.6139 & 0.270214 \tabularnewline
17 & 0.133146 & 1.4585 & 0.073652 \tabularnewline
18 & -0.081778 & -0.8958 & 0.186068 \tabularnewline
19 & -0.035019 & -0.3836 & 0.35097 \tabularnewline
20 & 0.007642 & 0.0837 & 0.46671 \tabularnewline
21 & -0.009641 & -0.1056 & 0.458034 \tabularnewline
22 & -0.093796 & -1.0275 & 0.153131 \tabularnewline
23 & -0.059742 & -0.6544 & 0.25704 \tabularnewline
24 & 0.117214 & 1.284 & 0.100806 \tabularnewline
25 & -0.107875 & -1.1817 & 0.119829 \tabularnewline
26 & 0.044562 & 0.4881 & 0.313167 \tabularnewline
27 & 0.047623 & 0.5217 & 0.301427 \tabularnewline
28 & -0.158477 & -1.736 & 0.042562 \tabularnewline
29 & 0.042153 & 0.4618 & 0.322543 \tabularnewline
30 & -0.037474 & -0.4105 & 0.341084 \tabularnewline
31 & 0.02487 & 0.2724 & 0.392876 \tabularnewline
32 & -0.011358 & -0.1244 & 0.450595 \tabularnewline
33 & -0.046581 & -0.5103 & 0.3054 \tabularnewline
34 & -0.029799 & -0.3264 & 0.372333 \tabularnewline
35 & -0.071853 & -0.7871 & 0.216383 \tabularnewline
36 & 0.003367 & 0.0369 & 0.485317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98563&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]0.813831[/C][C]8.9151[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.539151[/C][C]-5.9061[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]-0.604265[/C][C]-6.6194[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]-0.31713[/C][C]-3.474[/C][C]0.000357[/C][/ROW]
[ROW][C]5[/C][C]0.019297[/C][C]0.2114[/C][C]0.41647[/C][/ROW]
[ROW][C]6[/C][C]-0.149321[/C][C]-1.6357[/C][C]0.052258[/C][/ROW]
[ROW][C]7[/C][C]0.163417[/C][C]1.7901[/C][C]0.037976[/C][/ROW]
[ROW][C]8[/C][C]0.044736[/C][C]0.4901[/C][C]0.312493[/C][/ROW]
[ROW][C]9[/C][C]0.314441[/C][C]3.4445[/C][C]0.000394[/C][/ROW]
[ROW][C]10[/C][C]0.223237[/C][C]2.4454[/C][C]0.00796[/C][/ROW]
[ROW][C]11[/C][C]-0.006382[/C][C]-0.0699[/C][C]0.472192[/C][/ROW]
[ROW][C]12[/C][C]0.190327[/C][C]2.0849[/C][C]0.019598[/C][/ROW]
[ROW][C]13[/C][C]-0.045884[/C][C]-0.5026[/C][C]0.308073[/C][/ROW]
[ROW][C]14[/C][C]0.162542[/C][C]1.7806[/C][C]0.038758[/C][/ROW]
[ROW][C]15[/C][C]0.004145[/C][C]0.0454[/C][C]0.48193[/C][/ROW]
[ROW][C]16[/C][C]0.056043[/C][C]0.6139[/C][C]0.270214[/C][/ROW]
[ROW][C]17[/C][C]0.133146[/C][C]1.4585[/C][C]0.073652[/C][/ROW]
[ROW][C]18[/C][C]-0.081778[/C][C]-0.8958[/C][C]0.186068[/C][/ROW]
[ROW][C]19[/C][C]-0.035019[/C][C]-0.3836[/C][C]0.35097[/C][/ROW]
[ROW][C]20[/C][C]0.007642[/C][C]0.0837[/C][C]0.46671[/C][/ROW]
[ROW][C]21[/C][C]-0.009641[/C][C]-0.1056[/C][C]0.458034[/C][/ROW]
[ROW][C]22[/C][C]-0.093796[/C][C]-1.0275[/C][C]0.153131[/C][/ROW]
[ROW][C]23[/C][C]-0.059742[/C][C]-0.6544[/C][C]0.25704[/C][/ROW]
[ROW][C]24[/C][C]0.117214[/C][C]1.284[/C][C]0.100806[/C][/ROW]
[ROW][C]25[/C][C]-0.107875[/C][C]-1.1817[/C][C]0.119829[/C][/ROW]
[ROW][C]26[/C][C]0.044562[/C][C]0.4881[/C][C]0.313167[/C][/ROW]
[ROW][C]27[/C][C]0.047623[/C][C]0.5217[/C][C]0.301427[/C][/ROW]
[ROW][C]28[/C][C]-0.158477[/C][C]-1.736[/C][C]0.042562[/C][/ROW]
[ROW][C]29[/C][C]0.042153[/C][C]0.4618[/C][C]0.322543[/C][/ROW]
[ROW][C]30[/C][C]-0.037474[/C][C]-0.4105[/C][C]0.341084[/C][/ROW]
[ROW][C]31[/C][C]0.02487[/C][C]0.2724[/C][C]0.392876[/C][/ROW]
[ROW][C]32[/C][C]-0.011358[/C][C]-0.1244[/C][C]0.450595[/C][/ROW]
[ROW][C]33[/C][C]-0.046581[/C][C]-0.5103[/C][C]0.3054[/C][/ROW]
[ROW][C]34[/C][C]-0.029799[/C][C]-0.3264[/C][C]0.372333[/C][/ROW]
[ROW][C]35[/C][C]-0.071853[/C][C]-0.7871[/C][C]0.216383[/C][/ROW]
[ROW][C]36[/C][C]0.003367[/C][C]0.0369[/C][C]0.485317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98563&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98563&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
10.8138318.91510
2-0.539151-5.90610
3-0.604265-6.61940
4-0.31713-3.4740.000357
50.0192970.21140.41647
6-0.149321-1.63570.052258
70.1634171.79010.037976
80.0447360.49010.312493
90.3144413.44450.000394
100.2232372.44540.00796
11-0.006382-0.06990.472192
120.1903272.08490.019598
13-0.045884-0.50260.308073
140.1625421.78060.038758
150.0041450.04540.48193
160.0560430.61390.270214
170.1331461.45850.073652
18-0.081778-0.89580.186068
19-0.035019-0.38360.35097
200.0076420.08370.46671
21-0.009641-0.10560.458034
22-0.093796-1.02750.153131
23-0.059742-0.65440.25704
240.1172141.2840.100806
25-0.107875-1.18170.119829
260.0445620.48810.313167
270.0476230.52170.301427
28-0.158477-1.7360.042562
290.0421530.46180.322543
30-0.037474-0.41050.341084
310.024870.27240.392876
32-0.011358-0.12440.450595
33-0.046581-0.51030.3054
34-0.029799-0.32640.372333
35-0.071853-0.78710.216383
360.0033670.03690.485317



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