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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, 08 Dec 2009 11:32:58 -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/Dec/08/t1260297221whf3lvf6n4h16q9.htm/, Retrieved Sat, 27 Apr 2024 15:09:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64772, Retrieved Sat, 27 Apr 2024 15:09:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

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]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-26 18:26:04] [94b62ad0aa784646217b93aa983cee13]
-   PD            [(Partial) Autocorrelation Function] [] [2009-12-08 18:32:58] [873be88d67c17ca20f1ec7e5d8eb10d1] [Current]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-08 18:38:48] [94b62ad0aa784646217b93aa983cee13]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-08 18:42:25] [94b62ad0aa784646217b93aa983cee13]
-   P                 [(Partial) Autocorrelation Function] [] [2009-12-08 18:44:27] [94b62ad0aa784646217b93aa983cee13]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
87.28
87.28
87.09
86.92
87.59
90.72
90.69
90.3
89.55
88.94
88.41
87.82
87.07
86.82
86.4
86.02
85.66
85.32
85
84.67
83.94
82.83
81.95
81.19
80.48
78.86
69.47
68.77
70.06
73.95
75.8
77.79
81.57
83.07
84.34
85.1
85.25
84.26
83.63
86.44
85.3
84.1
83.36
82.48
81.58
80.47
79.34
82.13
81.69
80.7
79.88
79.16
78.38
77.42
76.47
75.46
74.48
78.27
80.7
79.91
78.75
77.78
81.14
81.08
80.03
78.91
78.01
76.9
75.97
81.93
80.27
78.67
77.42
76.16
74.7
76.39
76.04
74.65
73.29
71.79
74.39
74.91
74.54
73.08
72.75
71.32
70.38
70.35
70.01
69.36
67.77
69.26
69.8
68.38
67.62
68.39
66.95
65.21
66.64
63.45
60.66
62.34
60.32
58.64
60.46
58.59
61.87
61.85
67.44
77.06
91.74
93.15
94.15
93.11
91.51
89.96
88.16
86.98
88.03
86.24
84.65
83.23
81.7
80.25
78.8
77.51
76.2
75.04
74
75.49
77.14
76.15
76.27
78.19
76.49
77.31
76.65
74.99
73.51
72.07
70.59
71.96
76.29
74.86
74.93
71.9
71.01
77.47
75.78
76.6
76.07
74.57
73.02
72.65
73.16
71.53
69.78
67.98
69.96
72.16
70.47
68.86
67.37
65.87
72.16
71.34
69.93
68.44
67.16
66.01
67.25
70.91
69.75
68.59
67.48
66.31
64.81
66.58
65.97
64.7
64.7
60.94
59.08
58.42
57.77
57.11
53.31
49.96
49.4
48.84
48.3
47.74
47.24
46.76
46.29
48.9
49.23
48.53
48.03
54.34
53.79
53.24
52.96
52.17
51.7
58.55
78.2
77.03
76.19
77.15
75.87
95.47
109.67
112.28
112.01
107.93
105.96
105.06
102.98
102.2
105.23
101.85
99.89
96.23
94.76
91.51
91.63
91.54
85.23
87.83
87.38
84.44
85.19
84.03
86.73
102.52
104.45
106.98
107.02
99.26
94.45
113.44
157.33
147.38
171.89
171.95
132.71
126.02
121.18
115.45
110.48
117.85
117.63
124.65
109.59
111.27
99.78
98.21
99.2
97.97
89.55
87.91
93.34
94.42
93.2
90.29
91.46
89.98
88.35
88.41
82.44
79.89
75.69
75.66
84.5
96.73
87.48
82.39
83.48
79.31
78.16
72.77
72.45
68.46
67.62
68.76
70.07
68.55
65.3
58.96
59.17
62.37
66.28
55.62
55.23
55.85
56.75
50.89
53.88
52.95
55.08
53.61
58.78
61.85
55.91
53.32
46.41
44.57
50
50
53.36
46.23
50.45
49.07
45.85
48.45
49.96
46.53
50.51
47.58
48.05
46.84
47.67
49.16
55.54
55.82
58.22
56.19
57.77
63.19
54.76
55.74
62.54
61.39
69.6
79.23
80
93.68
107.63
100.18
97.3
90.45
80.64
80.58
75.82
85.59
89.35
89.42
104.73
95.32
89.27
90.44
86.97
79.98
81.22
87.35
83.64
82.22
94.4

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=64772&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=64772&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64772&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
10.95711118.13470
20.90658717.17740
30.85667416.23170
40.80001915.15820
50.76239614.44530
60.73811913.98540
70.70886113.4310
80.67253612.74270
90.63491412.02990
100.5930811.23730
110.54552710.33630
120.4979629.4350
130.4575378.66910
140.4182317.92430
150.3850177.2950
160.3580366.78380
170.3335096.31910
180.3082265.840
190.2857375.41390
200.2730655.17390
210.2596344.91941e-06
220.2482554.70382e-06
230.234634.44566e-06
240.2170894.11322.4e-05
250.1947533.690.000129

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.957111 & 18.1347 & 0 \tabularnewline
2 & 0.906587 & 17.1774 & 0 \tabularnewline
3 & 0.856674 & 16.2317 & 0 \tabularnewline
4 & 0.800019 & 15.1582 & 0 \tabularnewline
5 & 0.762396 & 14.4453 & 0 \tabularnewline
6 & 0.738119 & 13.9854 & 0 \tabularnewline
7 & 0.708861 & 13.431 & 0 \tabularnewline
8 & 0.672536 & 12.7427 & 0 \tabularnewline
9 & 0.634914 & 12.0299 & 0 \tabularnewline
10 & 0.59308 & 11.2373 & 0 \tabularnewline
11 & 0.545527 & 10.3363 & 0 \tabularnewline
12 & 0.497962 & 9.435 & 0 \tabularnewline
13 & 0.457537 & 8.6691 & 0 \tabularnewline
14 & 0.418231 & 7.9243 & 0 \tabularnewline
15 & 0.385017 & 7.295 & 0 \tabularnewline
16 & 0.358036 & 6.7838 & 0 \tabularnewline
17 & 0.333509 & 6.3191 & 0 \tabularnewline
18 & 0.308226 & 5.84 & 0 \tabularnewline
19 & 0.285737 & 5.4139 & 0 \tabularnewline
20 & 0.273065 & 5.1739 & 0 \tabularnewline
21 & 0.259634 & 4.9194 & 1e-06 \tabularnewline
22 & 0.248255 & 4.7038 & 2e-06 \tabularnewline
23 & 0.23463 & 4.4456 & 6e-06 \tabularnewline
24 & 0.217089 & 4.1132 & 2.4e-05 \tabularnewline
25 & 0.194753 & 3.69 & 0.000129 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64772&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]0.957111[/C][C]18.1347[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.906587[/C][C]17.1774[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.856674[/C][C]16.2317[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.800019[/C][C]15.1582[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.762396[/C][C]14.4453[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.738119[/C][C]13.9854[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.708861[/C][C]13.431[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.672536[/C][C]12.7427[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.634914[/C][C]12.0299[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.59308[/C][C]11.2373[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.545527[/C][C]10.3363[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.497962[/C][C]9.435[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.457537[/C][C]8.6691[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.418231[/C][C]7.9243[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.385017[/C][C]7.295[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.358036[/C][C]6.7838[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.333509[/C][C]6.3191[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.308226[/C][C]5.84[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.285737[/C][C]5.4139[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.273065[/C][C]5.1739[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.259634[/C][C]4.9194[/C][C]1e-06[/C][/ROW]
[ROW][C]22[/C][C]0.248255[/C][C]4.7038[/C][C]2e-06[/C][/ROW]
[ROW][C]23[/C][C]0.23463[/C][C]4.4456[/C][C]6e-06[/C][/ROW]
[ROW][C]24[/C][C]0.217089[/C][C]4.1132[/C][C]2.4e-05[/C][/ROW]
[ROW][C]25[/C][C]0.194753[/C][C]3.69[/C][C]0.000129[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64772&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64772&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
10.95711118.13470
20.90658717.17740
30.85667416.23170
40.80001915.15820
50.76239614.44530
60.73811913.98540
70.70886113.4310
80.67253612.74270
90.63491412.02990
100.5930811.23730
110.54552710.33630
120.4979629.4350
130.4575378.66910
140.4182317.92430
150.3850177.2950
160.3580366.78380
170.3335096.31910
180.3082265.840
190.2857375.41390
200.2730655.17390
210.2596344.91941e-06
220.2482554.70382e-06
230.234634.44566e-06
240.2170894.11322.4e-05
250.1947533.690.000129






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95711118.13470
2-0.112876-2.13870.016567
3-0.011324-0.21460.41512
4-0.110231-2.08860.018725
50.2152494.07842.8e-05
60.0968221.83450.033703
7-0.092136-1.74570.040857
8-0.140257-2.65750.004112
90.0057340.10860.456771
100.0051560.09770.461115
11-0.086599-1.64080.050856
12-0.089272-1.69150.045809
130.0510480.96720.167041
140.0010510.01990.492061
150.0281130.53270.297298
16-0.00788-0.14930.440698
170.0389850.73870.230298
18-0.007162-0.13570.446068
190.0292340.55390.289992
200.1177522.23110.013147
21-0.017723-0.33580.36861
22-0.0084-0.15920.436816
23-0.083622-1.58440.056989
240.0036050.06830.472788
25-0.055437-1.05040.147123

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.957111 & 18.1347 & 0 \tabularnewline
2 & -0.112876 & -2.1387 & 0.016567 \tabularnewline
3 & -0.011324 & -0.2146 & 0.41512 \tabularnewline
4 & -0.110231 & -2.0886 & 0.018725 \tabularnewline
5 & 0.215249 & 4.0784 & 2.8e-05 \tabularnewline
6 & 0.096822 & 1.8345 & 0.033703 \tabularnewline
7 & -0.092136 & -1.7457 & 0.040857 \tabularnewline
8 & -0.140257 & -2.6575 & 0.004112 \tabularnewline
9 & 0.005734 & 0.1086 & 0.456771 \tabularnewline
10 & 0.005156 & 0.0977 & 0.461115 \tabularnewline
11 & -0.086599 & -1.6408 & 0.050856 \tabularnewline
12 & -0.089272 & -1.6915 & 0.045809 \tabularnewline
13 & 0.051048 & 0.9672 & 0.167041 \tabularnewline
14 & 0.001051 & 0.0199 & 0.492061 \tabularnewline
15 & 0.028113 & 0.5327 & 0.297298 \tabularnewline
16 & -0.00788 & -0.1493 & 0.440698 \tabularnewline
17 & 0.038985 & 0.7387 & 0.230298 \tabularnewline
18 & -0.007162 & -0.1357 & 0.446068 \tabularnewline
19 & 0.029234 & 0.5539 & 0.289992 \tabularnewline
20 & 0.117752 & 2.2311 & 0.013147 \tabularnewline
21 & -0.017723 & -0.3358 & 0.36861 \tabularnewline
22 & -0.0084 & -0.1592 & 0.436816 \tabularnewline
23 & -0.083622 & -1.5844 & 0.056989 \tabularnewline
24 & 0.003605 & 0.0683 & 0.472788 \tabularnewline
25 & -0.055437 & -1.0504 & 0.147123 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64772&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]0.957111[/C][C]18.1347[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.112876[/C][C]-2.1387[/C][C]0.016567[/C][/ROW]
[ROW][C]3[/C][C]-0.011324[/C][C]-0.2146[/C][C]0.41512[/C][/ROW]
[ROW][C]4[/C][C]-0.110231[/C][C]-2.0886[/C][C]0.018725[/C][/ROW]
[ROW][C]5[/C][C]0.215249[/C][C]4.0784[/C][C]2.8e-05[/C][/ROW]
[ROW][C]6[/C][C]0.096822[/C][C]1.8345[/C][C]0.033703[/C][/ROW]
[ROW][C]7[/C][C]-0.092136[/C][C]-1.7457[/C][C]0.040857[/C][/ROW]
[ROW][C]8[/C][C]-0.140257[/C][C]-2.6575[/C][C]0.004112[/C][/ROW]
[ROW][C]9[/C][C]0.005734[/C][C]0.1086[/C][C]0.456771[/C][/ROW]
[ROW][C]10[/C][C]0.005156[/C][C]0.0977[/C][C]0.461115[/C][/ROW]
[ROW][C]11[/C][C]-0.086599[/C][C]-1.6408[/C][C]0.050856[/C][/ROW]
[ROW][C]12[/C][C]-0.089272[/C][C]-1.6915[/C][C]0.045809[/C][/ROW]
[ROW][C]13[/C][C]0.051048[/C][C]0.9672[/C][C]0.167041[/C][/ROW]
[ROW][C]14[/C][C]0.001051[/C][C]0.0199[/C][C]0.492061[/C][/ROW]
[ROW][C]15[/C][C]0.028113[/C][C]0.5327[/C][C]0.297298[/C][/ROW]
[ROW][C]16[/C][C]-0.00788[/C][C]-0.1493[/C][C]0.440698[/C][/ROW]
[ROW][C]17[/C][C]0.038985[/C][C]0.7387[/C][C]0.230298[/C][/ROW]
[ROW][C]18[/C][C]-0.007162[/C][C]-0.1357[/C][C]0.446068[/C][/ROW]
[ROW][C]19[/C][C]0.029234[/C][C]0.5539[/C][C]0.289992[/C][/ROW]
[ROW][C]20[/C][C]0.117752[/C][C]2.2311[/C][C]0.013147[/C][/ROW]
[ROW][C]21[/C][C]-0.017723[/C][C]-0.3358[/C][C]0.36861[/C][/ROW]
[ROW][C]22[/C][C]-0.0084[/C][C]-0.1592[/C][C]0.436816[/C][/ROW]
[ROW][C]23[/C][C]-0.083622[/C][C]-1.5844[/C][C]0.056989[/C][/ROW]
[ROW][C]24[/C][C]0.003605[/C][C]0.0683[/C][C]0.472788[/C][/ROW]
[ROW][C]25[/C][C]-0.055437[/C][C]-1.0504[/C][C]0.147123[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64772&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64772&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
10.95711118.13470
2-0.112876-2.13870.016567
3-0.011324-0.21460.41512
4-0.110231-2.08860.018725
50.2152494.07842.8e-05
60.0968221.83450.033703
7-0.092136-1.74570.040857
8-0.140257-2.65750.004112
90.0057340.10860.456771
100.0051560.09770.461115
11-0.086599-1.64080.050856
12-0.089272-1.69150.045809
130.0510480.96720.167041
140.0010510.01990.492061
150.0281130.53270.297298
16-0.00788-0.14930.440698
170.0389850.73870.230298
18-0.007162-0.13570.446068
190.0292340.55390.289992
200.1177522.23110.013147
21-0.017723-0.33580.36861
22-0.0084-0.15920.436816
23-0.083622-1.58440.056989
240.0036050.06830.472788
25-0.055437-1.05040.147123


Figures (Output of Computation)

Input Parameters & R Code

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