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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 computationMon, 30 Nov 2009 13:04:41 -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/30/t1259611702q00wklpiayzm774.htm/, Retrieved Wed, 01 May 2024 23:58:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61881, Retrieved Wed, 01 May 2024 23:58:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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]
F    D        [(Partial) Autocorrelation Function] [WS 8: ACF 3, D=1 ...] [2009-11-27 13:09:29] [b97b96148b0223bc16666763988dc147]
-                 [(Partial) Autocorrelation Function] [ws 8 review 3] [2009-11-30 20:04:41] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107

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=61881&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=61881&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61881&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
1-0.269146-1.59230.060156
20.2051291.21360.116521
3-0.148186-0.87670.193319
40.1484840.87840.192847
5-0.245426-1.4520.077709
60.0024360.01440.494292
70.2528061.49560.071858
8-0.109814-0.64970.260075
90.2555071.51160.069806
10-0.131679-0.7790.2206
110.3725062.20380.017105
12-0.49869-2.95030.002815
130.0550670.32580.373265
14-0.165635-0.97990.166929
150.0882970.52240.302352
16-0.093046-0.55050.292747
170.1226160.72540.236512
180.011160.0660.473867
19-0.11407-0.67480.252104
200.064560.38190.352407
21-0.150872-0.89260.189091
220.0227420.13450.446872
23-0.154894-0.91640.182874
240.0716350.42380.337153
25-0.020741-0.12270.451521
260.0525320.31080.378905
27-0.005719-0.03380.4866
28-0.035078-0.20750.418402
29-0.032746-0.19370.423755
30-0.024017-0.14210.443913
31-0.012163-0.0720.471522
32-0.018226-0.10780.457374
330.0049660.02940.488363
34-0.000297-0.00180.499304
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.269146 & -1.5923 & 0.060156 \tabularnewline
2 & 0.205129 & 1.2136 & 0.116521 \tabularnewline
3 & -0.148186 & -0.8767 & 0.193319 \tabularnewline
4 & 0.148484 & 0.8784 & 0.192847 \tabularnewline
5 & -0.245426 & -1.452 & 0.077709 \tabularnewline
6 & 0.002436 & 0.0144 & 0.494292 \tabularnewline
7 & 0.252806 & 1.4956 & 0.071858 \tabularnewline
8 & -0.109814 & -0.6497 & 0.260075 \tabularnewline
9 & 0.255507 & 1.5116 & 0.069806 \tabularnewline
10 & -0.131679 & -0.779 & 0.2206 \tabularnewline
11 & 0.372506 & 2.2038 & 0.017105 \tabularnewline
12 & -0.49869 & -2.9503 & 0.002815 \tabularnewline
13 & 0.055067 & 0.3258 & 0.373265 \tabularnewline
14 & -0.165635 & -0.9799 & 0.166929 \tabularnewline
15 & 0.088297 & 0.5224 & 0.302352 \tabularnewline
16 & -0.093046 & -0.5505 & 0.292747 \tabularnewline
17 & 0.122616 & 0.7254 & 0.236512 \tabularnewline
18 & 0.01116 & 0.066 & 0.473867 \tabularnewline
19 & -0.11407 & -0.6748 & 0.252104 \tabularnewline
20 & 0.06456 & 0.3819 & 0.352407 \tabularnewline
21 & -0.150872 & -0.8926 & 0.189091 \tabularnewline
22 & 0.022742 & 0.1345 & 0.446872 \tabularnewline
23 & -0.154894 & -0.9164 & 0.182874 \tabularnewline
24 & 0.071635 & 0.4238 & 0.337153 \tabularnewline
25 & -0.020741 & -0.1227 & 0.451521 \tabularnewline
26 & 0.052532 & 0.3108 & 0.378905 \tabularnewline
27 & -0.005719 & -0.0338 & 0.4866 \tabularnewline
28 & -0.035078 & -0.2075 & 0.418402 \tabularnewline
29 & -0.032746 & -0.1937 & 0.423755 \tabularnewline
30 & -0.024017 & -0.1421 & 0.443913 \tabularnewline
31 & -0.012163 & -0.072 & 0.471522 \tabularnewline
32 & -0.018226 & -0.1078 & 0.457374 \tabularnewline
33 & 0.004966 & 0.0294 & 0.488363 \tabularnewline
34 & -0.000297 & -0.0018 & 0.499304 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61881&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]-0.269146[/C][C]-1.5923[/C][C]0.060156[/C][/ROW]
[ROW][C]2[/C][C]0.205129[/C][C]1.2136[/C][C]0.116521[/C][/ROW]
[ROW][C]3[/C][C]-0.148186[/C][C]-0.8767[/C][C]0.193319[/C][/ROW]
[ROW][C]4[/C][C]0.148484[/C][C]0.8784[/C][C]0.192847[/C][/ROW]
[ROW][C]5[/C][C]-0.245426[/C][C]-1.452[/C][C]0.077709[/C][/ROW]
[ROW][C]6[/C][C]0.002436[/C][C]0.0144[/C][C]0.494292[/C][/ROW]
[ROW][C]7[/C][C]0.252806[/C][C]1.4956[/C][C]0.071858[/C][/ROW]
[ROW][C]8[/C][C]-0.109814[/C][C]-0.6497[/C][C]0.260075[/C][/ROW]
[ROW][C]9[/C][C]0.255507[/C][C]1.5116[/C][C]0.069806[/C][/ROW]
[ROW][C]10[/C][C]-0.131679[/C][C]-0.779[/C][C]0.2206[/C][/ROW]
[ROW][C]11[/C][C]0.372506[/C][C]2.2038[/C][C]0.017105[/C][/ROW]
[ROW][C]12[/C][C]-0.49869[/C][C]-2.9503[/C][C]0.002815[/C][/ROW]
[ROW][C]13[/C][C]0.055067[/C][C]0.3258[/C][C]0.373265[/C][/ROW]
[ROW][C]14[/C][C]-0.165635[/C][C]-0.9799[/C][C]0.166929[/C][/ROW]
[ROW][C]15[/C][C]0.088297[/C][C]0.5224[/C][C]0.302352[/C][/ROW]
[ROW][C]16[/C][C]-0.093046[/C][C]-0.5505[/C][C]0.292747[/C][/ROW]
[ROW][C]17[/C][C]0.122616[/C][C]0.7254[/C][C]0.236512[/C][/ROW]
[ROW][C]18[/C][C]0.01116[/C][C]0.066[/C][C]0.473867[/C][/ROW]
[ROW][C]19[/C][C]-0.11407[/C][C]-0.6748[/C][C]0.252104[/C][/ROW]
[ROW][C]20[/C][C]0.06456[/C][C]0.3819[/C][C]0.352407[/C][/ROW]
[ROW][C]21[/C][C]-0.150872[/C][C]-0.8926[/C][C]0.189091[/C][/ROW]
[ROW][C]22[/C][C]0.022742[/C][C]0.1345[/C][C]0.446872[/C][/ROW]
[ROW][C]23[/C][C]-0.154894[/C][C]-0.9164[/C][C]0.182874[/C][/ROW]
[ROW][C]24[/C][C]0.071635[/C][C]0.4238[/C][C]0.337153[/C][/ROW]
[ROW][C]25[/C][C]-0.020741[/C][C]-0.1227[/C][C]0.451521[/C][/ROW]
[ROW][C]26[/C][C]0.052532[/C][C]0.3108[/C][C]0.378905[/C][/ROW]
[ROW][C]27[/C][C]-0.005719[/C][C]-0.0338[/C][C]0.4866[/C][/ROW]
[ROW][C]28[/C][C]-0.035078[/C][C]-0.2075[/C][C]0.418402[/C][/ROW]
[ROW][C]29[/C][C]-0.032746[/C][C]-0.1937[/C][C]0.423755[/C][/ROW]
[ROW][C]30[/C][C]-0.024017[/C][C]-0.1421[/C][C]0.443913[/C][/ROW]
[ROW][C]31[/C][C]-0.012163[/C][C]-0.072[/C][C]0.471522[/C][/ROW]
[ROW][C]32[/C][C]-0.018226[/C][C]-0.1078[/C][C]0.457374[/C][/ROW]
[ROW][C]33[/C][C]0.004966[/C][C]0.0294[/C][C]0.488363[/C][/ROW]
[ROW][C]34[/C][C]-0.000297[/C][C]-0.0018[/C][C]0.499304[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61881&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61881&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
1-0.269146-1.59230.060156
20.2051291.21360.116521
3-0.148186-0.87670.193319
40.1484840.87840.192847
5-0.245426-1.4520.077709
60.0024360.01440.494292
70.2528061.49560.071858
8-0.109814-0.64970.260075
90.2555071.51160.069806
10-0.131679-0.7790.2206
110.3725062.20380.017105
12-0.49869-2.95030.002815
130.0550670.32580.373265
14-0.165635-0.97990.166929
150.0882970.52240.302352
16-0.093046-0.55050.292747
170.1226160.72540.236512
180.011160.0660.473867
19-0.11407-0.67480.252104
200.064560.38190.352407
21-0.150872-0.89260.189091
220.0227420.13450.446872
23-0.154894-0.91640.182874
240.0716350.42380.337153
25-0.020741-0.12270.451521
260.0525320.31080.378905
27-0.005719-0.03380.4866
28-0.035078-0.20750.418402
29-0.032746-0.19370.423755
30-0.024017-0.14210.443913
31-0.012163-0.0720.471522
32-0.018226-0.10780.457374
330.0049660.02940.488363
34-0.000297-0.00180.499304
35NANANA
36NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.269146-1.59230.060156
20.1430520.84630.201565
3-0.068648-0.40610.343561
40.0787220.46570.322148
5-0.182897-1.0820.143319
6-0.143471-0.84880.200885
70.3517022.08070.022423
8-0.024397-0.14430.443032
90.2118541.25330.109194
10-0.034364-0.20330.420038
110.2590981.53280.067152
12-0.29499-1.74520.044864
13-0.297048-1.75740.043801
14-0.048076-0.28440.388882
15-0.019554-0.11570.454283
160.0510340.30190.382249
17-0.019848-0.11740.453599
18-0.258953-1.5320.067258
190.0683860.40460.344125
200.0100340.05940.476501
210.0790370.46760.321488
22-0.066387-0.39270.348444
230.1130980.66910.253912
24-0.05202-0.30780.380047
25-0.039702-0.23490.407835
26-0.109208-0.64610.261219
270.0212820.12590.450263
28-0.044158-0.26120.397719
290.0466420.27590.392109
30-0.063324-0.37460.355099
31-0.091459-0.54110.29594
320.0007010.00410.498357
330.0153030.09050.464189
34-0.090874-0.53760.297122
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.269146 & -1.5923 & 0.060156 \tabularnewline
2 & 0.143052 & 0.8463 & 0.201565 \tabularnewline
3 & -0.068648 & -0.4061 & 0.343561 \tabularnewline
4 & 0.078722 & 0.4657 & 0.322148 \tabularnewline
5 & -0.182897 & -1.082 & 0.143319 \tabularnewline
6 & -0.143471 & -0.8488 & 0.200885 \tabularnewline
7 & 0.351702 & 2.0807 & 0.022423 \tabularnewline
8 & -0.024397 & -0.1443 & 0.443032 \tabularnewline
9 & 0.211854 & 1.2533 & 0.109194 \tabularnewline
10 & -0.034364 & -0.2033 & 0.420038 \tabularnewline
11 & 0.259098 & 1.5328 & 0.067152 \tabularnewline
12 & -0.29499 & -1.7452 & 0.044864 \tabularnewline
13 & -0.297048 & -1.7574 & 0.043801 \tabularnewline
14 & -0.048076 & -0.2844 & 0.388882 \tabularnewline
15 & -0.019554 & -0.1157 & 0.454283 \tabularnewline
16 & 0.051034 & 0.3019 & 0.382249 \tabularnewline
17 & -0.019848 & -0.1174 & 0.453599 \tabularnewline
18 & -0.258953 & -1.532 & 0.067258 \tabularnewline
19 & 0.068386 & 0.4046 & 0.344125 \tabularnewline
20 & 0.010034 & 0.0594 & 0.476501 \tabularnewline
21 & 0.079037 & 0.4676 & 0.321488 \tabularnewline
22 & -0.066387 & -0.3927 & 0.348444 \tabularnewline
23 & 0.113098 & 0.6691 & 0.253912 \tabularnewline
24 & -0.05202 & -0.3078 & 0.380047 \tabularnewline
25 & -0.039702 & -0.2349 & 0.407835 \tabularnewline
26 & -0.109208 & -0.6461 & 0.261219 \tabularnewline
27 & 0.021282 & 0.1259 & 0.450263 \tabularnewline
28 & -0.044158 & -0.2612 & 0.397719 \tabularnewline
29 & 0.046642 & 0.2759 & 0.392109 \tabularnewline
30 & -0.063324 & -0.3746 & 0.355099 \tabularnewline
31 & -0.091459 & -0.5411 & 0.29594 \tabularnewline
32 & 0.000701 & 0.0041 & 0.498357 \tabularnewline
33 & 0.015303 & 0.0905 & 0.464189 \tabularnewline
34 & -0.090874 & -0.5376 & 0.297122 \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61881&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]-0.269146[/C][C]-1.5923[/C][C]0.060156[/C][/ROW]
[ROW][C]2[/C][C]0.143052[/C][C]0.8463[/C][C]0.201565[/C][/ROW]
[ROW][C]3[/C][C]-0.068648[/C][C]-0.4061[/C][C]0.343561[/C][/ROW]
[ROW][C]4[/C][C]0.078722[/C][C]0.4657[/C][C]0.322148[/C][/ROW]
[ROW][C]5[/C][C]-0.182897[/C][C]-1.082[/C][C]0.143319[/C][/ROW]
[ROW][C]6[/C][C]-0.143471[/C][C]-0.8488[/C][C]0.200885[/C][/ROW]
[ROW][C]7[/C][C]0.351702[/C][C]2.0807[/C][C]0.022423[/C][/ROW]
[ROW][C]8[/C][C]-0.024397[/C][C]-0.1443[/C][C]0.443032[/C][/ROW]
[ROW][C]9[/C][C]0.211854[/C][C]1.2533[/C][C]0.109194[/C][/ROW]
[ROW][C]10[/C][C]-0.034364[/C][C]-0.2033[/C][C]0.420038[/C][/ROW]
[ROW][C]11[/C][C]0.259098[/C][C]1.5328[/C][C]0.067152[/C][/ROW]
[ROW][C]12[/C][C]-0.29499[/C][C]-1.7452[/C][C]0.044864[/C][/ROW]
[ROW][C]13[/C][C]-0.297048[/C][C]-1.7574[/C][C]0.043801[/C][/ROW]
[ROW][C]14[/C][C]-0.048076[/C][C]-0.2844[/C][C]0.388882[/C][/ROW]
[ROW][C]15[/C][C]-0.019554[/C][C]-0.1157[/C][C]0.454283[/C][/ROW]
[ROW][C]16[/C][C]0.051034[/C][C]0.3019[/C][C]0.382249[/C][/ROW]
[ROW][C]17[/C][C]-0.019848[/C][C]-0.1174[/C][C]0.453599[/C][/ROW]
[ROW][C]18[/C][C]-0.258953[/C][C]-1.532[/C][C]0.067258[/C][/ROW]
[ROW][C]19[/C][C]0.068386[/C][C]0.4046[/C][C]0.344125[/C][/ROW]
[ROW][C]20[/C][C]0.010034[/C][C]0.0594[/C][C]0.476501[/C][/ROW]
[ROW][C]21[/C][C]0.079037[/C][C]0.4676[/C][C]0.321488[/C][/ROW]
[ROW][C]22[/C][C]-0.066387[/C][C]-0.3927[/C][C]0.348444[/C][/ROW]
[ROW][C]23[/C][C]0.113098[/C][C]0.6691[/C][C]0.253912[/C][/ROW]
[ROW][C]24[/C][C]-0.05202[/C][C]-0.3078[/C][C]0.380047[/C][/ROW]
[ROW][C]25[/C][C]-0.039702[/C][C]-0.2349[/C][C]0.407835[/C][/ROW]
[ROW][C]26[/C][C]-0.109208[/C][C]-0.6461[/C][C]0.261219[/C][/ROW]
[ROW][C]27[/C][C]0.021282[/C][C]0.1259[/C][C]0.450263[/C][/ROW]
[ROW][C]28[/C][C]-0.044158[/C][C]-0.2612[/C][C]0.397719[/C][/ROW]
[ROW][C]29[/C][C]0.046642[/C][C]0.2759[/C][C]0.392109[/C][/ROW]
[ROW][C]30[/C][C]-0.063324[/C][C]-0.3746[/C][C]0.355099[/C][/ROW]
[ROW][C]31[/C][C]-0.091459[/C][C]-0.5411[/C][C]0.29594[/C][/ROW]
[ROW][C]32[/C][C]0.000701[/C][C]0.0041[/C][C]0.498357[/C][/ROW]
[ROW][C]33[/C][C]0.015303[/C][C]0.0905[/C][C]0.464189[/C][/ROW]
[ROW][C]34[/C][C]-0.090874[/C][C]-0.5376[/C][C]0.297122[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61881&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61881&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
1-0.269146-1.59230.060156
20.1430520.84630.201565
3-0.068648-0.40610.343561
40.0787220.46570.322148
5-0.182897-1.0820.143319
6-0.143471-0.84880.200885
70.3517022.08070.022423
8-0.024397-0.14430.443032
90.2118541.25330.109194
10-0.034364-0.20330.420038
110.2590981.53280.067152
12-0.29499-1.74520.044864
13-0.297048-1.75740.043801
14-0.048076-0.28440.388882
15-0.019554-0.11570.454283
160.0510340.30190.382249
17-0.019848-0.11740.453599
18-0.258953-1.5320.067258
190.0683860.40460.344125
200.0100340.05940.476501
210.0790370.46760.321488
22-0.066387-0.39270.348444
230.1130980.66910.253912
24-0.05202-0.30780.380047
25-0.039702-0.23490.407835
26-0.109208-0.64610.261219
270.0212820.12590.450263
28-0.044158-0.26120.397719
290.0466420.27590.392109
30-0.063324-0.37460.355099
31-0.091459-0.54110.29594
320.0007010.00410.498357
330.0153030.09050.464189
34-0.090874-0.53760.297122
35NANANA
36NANANA


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 = 2 ; 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')