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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, 07 Dec 2010 09:46:30 +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/Dec/07/t12917150745agi24603k4dme8.htm/, Retrieved Sat, 04 May 2024 02:34:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106086, Retrieved Sat, 04 May 2024 02:34:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R  D    [(Partial) Autocorrelation Function] [Workshop 9; Coffe...] [2010-12-07 09:31:16] [8ffb4cfa64b4677df0d2c448735a40bb]
-   PD        [(Partial) Autocorrelation Function] [Workshop 9; Coffe...] [2010-12-07 09:46:30] [50e0b5177c9c80b42996aa89930b928a] [Current]
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Dataseries X:
168.67
164.83
184.38
180.81
190.54
181.41
155.67
135.99
125.88
126.09
114.86
127.98
127.98
125.11
125.93
128.2
125.93
111.94
120.01
124.09
126.02
136.41
143.79
141.67
143.9
155
144.83
141.4
137
141.02
131.11
132.83
136.73
141.18
137.86
133.79
128.53
125.87
124.27
123.96
128.15
126.4
127.86
129.31
132.56
141.28
145.55
146.54
143.14
145.72
148.21
150.4
149.94
146.66
143.37
145.29
140.24
136.12
140.25
140.64
145.58
143.73
141.27
140.66
141.94
141.16
134.31
132.93
133.07
140.48
154.85
196.77
235.3
226.52
237.62
224.07
208.74
174.54
170.63
172.23
198.36
175.91
154.63
134.31
121.75
119.6
102.04
106.3
116.38
103.72
98.56
100.9
110
118.26
124.77
125.22
126.38
137.14
134.74
134.3
136.39
141.83
139.24
128.89
134.83
130.43
132.09
144.95
149.5
137.57
139.38
143.06
138.65
123.21
85.91
77.4
77.84
67.76
70.72
72.55
75.83
84.01
93.96
93.73
92.02
88.26
86.48
94.42
94.92
91.41
84.84
89.89
86.32
89.57
93.72
92.27
87.59
85.5
82.81
81.62
87.45
79.86
78.52
75.1
72.99
67.88
70.14
65.43
60.26
58.38
57.68
52.42
52.73
61.4
67.13
77.46
68.66
67.46
62.77
56.88
61.48
61.99
71.56
76.56
79.82
75.05
77.07
80
77.21
82.16
85.57
89.23
121.98
142.56
217.67
198.07
220.1
198.68
181.64
167.47
172.33
168.71
178.22
172.81
168.83
152.25
143.83
151.41
131.87
125.38
123.23
103.99
109.38
123.79
119.05
122.01
128.56
127.91
120.47
122.49
114.05
120.62
119.61
115.01
131.83
167.2
193.82
204.43
264.5
212.55
186.52
185.17
184.38
161.45
154.15
174.25
175.04
175.87
154.82
147.08
134.35
121.56
113.86
119.89
108.07
107.07
115.14
116.03
111.48
103.24
103.23
99.69
108.91
104.21
90.85
87.64
81.06
92.2
114.02
123.56
109.17
101.65
97.95
92.56
91.76
84.1
84.67
74.52
73.83
75.37
70.47
64.5
64.98
66.94
65.93
65.51
68.94
63.67
58.47
59.68
57.71
56.53
58.96
55.6
57.34
60.51
66.38
65.78
58.43
55.16
53.09
52.02
57.58
64.05
70.18
63.86
65.22
67.6
61.66
65.32
66.18
61.34
62.29
63.6
65.51
62.58
62.36
64.88
73.73
77.51
77.47
74.34
75.81
82.16
73.96
73.17
80.99
79.81
89.51
102.57
107.11
122.23
134.69
128.79
126.16
119.98
108.45
108.43
98.17
106.09
108.81
103.03
124.36
118.52
112.2
114.71
107.96
101.21
102.77
112.13
109.36
110.91
123.57
129.95
124.46
122.34
116.61
114.59
112.52
118.67
116.8
123.63
128.04
134.57
130.33
136.47
139.05
158.21
148.07
137.74
139.74
144.08
145.35
145.77
140.56
121.41
120.44
116.97
128.03
128.51
127.76
134.58
147.64
144.46
137.6
146.87
145.67
151.95
150.23
155.86
154.4
156.36
162.13
171.06
174.01
193.52
205.26
212.8
222.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106086&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106086&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106086&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1735273.32880.00048
20.1421382.72670.003352
30.0009390.0180.49282
4-0.049733-0.9540.170346
5-0.181931-3.490.000271
6-0.076237-1.46250.072232
70.0058650.11250.45524
8-0.005803-0.11130.455711
90.0524081.00540.157691
100.0034050.06530.47398
110.0351110.67350.250513
12-0.039576-0.75920.224111
13-0.043688-0.83810.201267
14-0.101693-1.95080.025919
15-0.087408-1.67680.047218
16-0.095376-1.82960.034057
17-0.154479-2.96340.00162
18-0.056297-1.080.140433
190.0182260.34960.363403
200.003470.06660.473482
210.0645081.23750.10835
220.0309140.5930.27676
23-0.006661-0.12780.449199
240.0095770.18370.427164
250.0095440.18310.427412

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.173527 & 3.3288 & 0.00048 \tabularnewline
2 & 0.142138 & 2.7267 & 0.003352 \tabularnewline
3 & 0.000939 & 0.018 & 0.49282 \tabularnewline
4 & -0.049733 & -0.954 & 0.170346 \tabularnewline
5 & -0.181931 & -3.49 & 0.000271 \tabularnewline
6 & -0.076237 & -1.4625 & 0.072232 \tabularnewline
7 & 0.005865 & 0.1125 & 0.45524 \tabularnewline
8 & -0.005803 & -0.1113 & 0.455711 \tabularnewline
9 & 0.052408 & 1.0054 & 0.157691 \tabularnewline
10 & 0.003405 & 0.0653 & 0.47398 \tabularnewline
11 & 0.035111 & 0.6735 & 0.250513 \tabularnewline
12 & -0.039576 & -0.7592 & 0.224111 \tabularnewline
13 & -0.043688 & -0.8381 & 0.201267 \tabularnewline
14 & -0.101693 & -1.9508 & 0.025919 \tabularnewline
15 & -0.087408 & -1.6768 & 0.047218 \tabularnewline
16 & -0.095376 & -1.8296 & 0.034057 \tabularnewline
17 & -0.154479 & -2.9634 & 0.00162 \tabularnewline
18 & -0.056297 & -1.08 & 0.140433 \tabularnewline
19 & 0.018226 & 0.3496 & 0.363403 \tabularnewline
20 & 0.00347 & 0.0666 & 0.473482 \tabularnewline
21 & 0.064508 & 1.2375 & 0.10835 \tabularnewline
22 & 0.030914 & 0.593 & 0.27676 \tabularnewline
23 & -0.006661 & -0.1278 & 0.449199 \tabularnewline
24 & 0.009577 & 0.1837 & 0.427164 \tabularnewline
25 & 0.009544 & 0.1831 & 0.427412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106086&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]0.173527[/C][C]3.3288[/C][C]0.00048[/C][/ROW]
[ROW][C]2[/C][C]0.142138[/C][C]2.7267[/C][C]0.003352[/C][/ROW]
[ROW][C]3[/C][C]0.000939[/C][C]0.018[/C][C]0.49282[/C][/ROW]
[ROW][C]4[/C][C]-0.049733[/C][C]-0.954[/C][C]0.170346[/C][/ROW]
[ROW][C]5[/C][C]-0.181931[/C][C]-3.49[/C][C]0.000271[/C][/ROW]
[ROW][C]6[/C][C]-0.076237[/C][C]-1.4625[/C][C]0.072232[/C][/ROW]
[ROW][C]7[/C][C]0.005865[/C][C]0.1125[/C][C]0.45524[/C][/ROW]
[ROW][C]8[/C][C]-0.005803[/C][C]-0.1113[/C][C]0.455711[/C][/ROW]
[ROW][C]9[/C][C]0.052408[/C][C]1.0054[/C][C]0.157691[/C][/ROW]
[ROW][C]10[/C][C]0.003405[/C][C]0.0653[/C][C]0.47398[/C][/ROW]
[ROW][C]11[/C][C]0.035111[/C][C]0.6735[/C][C]0.250513[/C][/ROW]
[ROW][C]12[/C][C]-0.039576[/C][C]-0.7592[/C][C]0.224111[/C][/ROW]
[ROW][C]13[/C][C]-0.043688[/C][C]-0.8381[/C][C]0.201267[/C][/ROW]
[ROW][C]14[/C][C]-0.101693[/C][C]-1.9508[/C][C]0.025919[/C][/ROW]
[ROW][C]15[/C][C]-0.087408[/C][C]-1.6768[/C][C]0.047218[/C][/ROW]
[ROW][C]16[/C][C]-0.095376[/C][C]-1.8296[/C][C]0.034057[/C][/ROW]
[ROW][C]17[/C][C]-0.154479[/C][C]-2.9634[/C][C]0.00162[/C][/ROW]
[ROW][C]18[/C][C]-0.056297[/C][C]-1.08[/C][C]0.140433[/C][/ROW]
[ROW][C]19[/C][C]0.018226[/C][C]0.3496[/C][C]0.363403[/C][/ROW]
[ROW][C]20[/C][C]0.00347[/C][C]0.0666[/C][C]0.473482[/C][/ROW]
[ROW][C]21[/C][C]0.064508[/C][C]1.2375[/C][C]0.10835[/C][/ROW]
[ROW][C]22[/C][C]0.030914[/C][C]0.593[/C][C]0.27676[/C][/ROW]
[ROW][C]23[/C][C]-0.006661[/C][C]-0.1278[/C][C]0.449199[/C][/ROW]
[ROW][C]24[/C][C]0.009577[/C][C]0.1837[/C][C]0.427164[/C][/ROW]
[ROW][C]25[/C][C]0.009544[/C][C]0.1831[/C][C]0.427412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106086&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106086&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
10.1735273.32880.00048
20.1421382.72670.003352
30.0009390.0180.49282
4-0.049733-0.9540.170346
5-0.181931-3.490.000271
6-0.076237-1.46250.072232
70.0058650.11250.45524
8-0.005803-0.11130.455711
90.0524081.00540.157691
100.0034050.06530.47398
110.0351110.67350.250513
12-0.039576-0.75920.224111
13-0.043688-0.83810.201267
14-0.101693-1.95080.025919
15-0.087408-1.67680.047218
16-0.095376-1.82960.034057
17-0.154479-2.96340.00162
18-0.056297-1.080.140433
190.0182260.34960.363403
200.003470.06660.473482
210.0645081.23750.10835
220.0309140.5930.27676
23-0.006661-0.12780.449199
240.0095770.18370.427164
250.0095440.18310.427412







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1735273.32880.00048
20.1155042.21580.01366
3-0.042761-0.82030.206289
4-0.062617-1.20120.115224
5-0.166874-3.20120.000744
6-0.010218-0.1960.422355
70.0693041.32950.092255
8-0.009409-0.18050.42843
90.0307040.5890.27811
10-0.045076-0.86470.193882
110.0176880.33930.367283
12-0.032528-0.6240.266512
13-0.037537-0.72010.235964
14-0.074038-1.42030.078183
15-0.058289-1.11820.132109
16-0.055256-1.060.144923
17-0.13801-2.64750.004229
18-0.026702-0.51220.3044
190.0378720.72650.233993
20-0.031693-0.6080.271788
210.0345320.66240.254052
22-0.038527-0.73910.230164
23-0.038503-0.73860.230307
240.0340130.65250.25725
250.0145350.27880.390266

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.173527 & 3.3288 & 0.00048 \tabularnewline
2 & 0.115504 & 2.2158 & 0.01366 \tabularnewline
3 & -0.042761 & -0.8203 & 0.206289 \tabularnewline
4 & -0.062617 & -1.2012 & 0.115224 \tabularnewline
5 & -0.166874 & -3.2012 & 0.000744 \tabularnewline
6 & -0.010218 & -0.196 & 0.422355 \tabularnewline
7 & 0.069304 & 1.3295 & 0.092255 \tabularnewline
8 & -0.009409 & -0.1805 & 0.42843 \tabularnewline
9 & 0.030704 & 0.589 & 0.27811 \tabularnewline
10 & -0.045076 & -0.8647 & 0.193882 \tabularnewline
11 & 0.017688 & 0.3393 & 0.367283 \tabularnewline
12 & -0.032528 & -0.624 & 0.266512 \tabularnewline
13 & -0.037537 & -0.7201 & 0.235964 \tabularnewline
14 & -0.074038 & -1.4203 & 0.078183 \tabularnewline
15 & -0.058289 & -1.1182 & 0.132109 \tabularnewline
16 & -0.055256 & -1.06 & 0.144923 \tabularnewline
17 & -0.13801 & -2.6475 & 0.004229 \tabularnewline
18 & -0.026702 & -0.5122 & 0.3044 \tabularnewline
19 & 0.037872 & 0.7265 & 0.233993 \tabularnewline
20 & -0.031693 & -0.608 & 0.271788 \tabularnewline
21 & 0.034532 & 0.6624 & 0.254052 \tabularnewline
22 & -0.038527 & -0.7391 & 0.230164 \tabularnewline
23 & -0.038503 & -0.7386 & 0.230307 \tabularnewline
24 & 0.034013 & 0.6525 & 0.25725 \tabularnewline
25 & 0.014535 & 0.2788 & 0.390266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106086&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]0.173527[/C][C]3.3288[/C][C]0.00048[/C][/ROW]
[ROW][C]2[/C][C]0.115504[/C][C]2.2158[/C][C]0.01366[/C][/ROW]
[ROW][C]3[/C][C]-0.042761[/C][C]-0.8203[/C][C]0.206289[/C][/ROW]
[ROW][C]4[/C][C]-0.062617[/C][C]-1.2012[/C][C]0.115224[/C][/ROW]
[ROW][C]5[/C][C]-0.166874[/C][C]-3.2012[/C][C]0.000744[/C][/ROW]
[ROW][C]6[/C][C]-0.010218[/C][C]-0.196[/C][C]0.422355[/C][/ROW]
[ROW][C]7[/C][C]0.069304[/C][C]1.3295[/C][C]0.092255[/C][/ROW]
[ROW][C]8[/C][C]-0.009409[/C][C]-0.1805[/C][C]0.42843[/C][/ROW]
[ROW][C]9[/C][C]0.030704[/C][C]0.589[/C][C]0.27811[/C][/ROW]
[ROW][C]10[/C][C]-0.045076[/C][C]-0.8647[/C][C]0.193882[/C][/ROW]
[ROW][C]11[/C][C]0.017688[/C][C]0.3393[/C][C]0.367283[/C][/ROW]
[ROW][C]12[/C][C]-0.032528[/C][C]-0.624[/C][C]0.266512[/C][/ROW]
[ROW][C]13[/C][C]-0.037537[/C][C]-0.7201[/C][C]0.235964[/C][/ROW]
[ROW][C]14[/C][C]-0.074038[/C][C]-1.4203[/C][C]0.078183[/C][/ROW]
[ROW][C]15[/C][C]-0.058289[/C][C]-1.1182[/C][C]0.132109[/C][/ROW]
[ROW][C]16[/C][C]-0.055256[/C][C]-1.06[/C][C]0.144923[/C][/ROW]
[ROW][C]17[/C][C]-0.13801[/C][C]-2.6475[/C][C]0.004229[/C][/ROW]
[ROW][C]18[/C][C]-0.026702[/C][C]-0.5122[/C][C]0.3044[/C][/ROW]
[ROW][C]19[/C][C]0.037872[/C][C]0.7265[/C][C]0.233993[/C][/ROW]
[ROW][C]20[/C][C]-0.031693[/C][C]-0.608[/C][C]0.271788[/C][/ROW]
[ROW][C]21[/C][C]0.034532[/C][C]0.6624[/C][C]0.254052[/C][/ROW]
[ROW][C]22[/C][C]-0.038527[/C][C]-0.7391[/C][C]0.230164[/C][/ROW]
[ROW][C]23[/C][C]-0.038503[/C][C]-0.7386[/C][C]0.230307[/C][/ROW]
[ROW][C]24[/C][C]0.034013[/C][C]0.6525[/C][C]0.25725[/C][/ROW]
[ROW][C]25[/C][C]0.014535[/C][C]0.2788[/C][C]0.390266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106086&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106086&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
10.1735273.32880.00048
20.1155042.21580.01366
3-0.042761-0.82030.206289
4-0.062617-1.20120.115224
5-0.166874-3.20120.000744
6-0.010218-0.1960.422355
70.0693041.32950.092255
8-0.009409-0.18050.42843
90.0307040.5890.27811
10-0.045076-0.86470.193882
110.0176880.33930.367283
12-0.032528-0.6240.266512
13-0.037537-0.72010.235964
14-0.074038-1.42030.078183
15-0.058289-1.11820.132109
16-0.055256-1.060.144923
17-0.13801-2.64750.004229
18-0.026702-0.51220.3044
190.0378720.72650.233993
20-0.031693-0.6080.271788
210.0345320.66240.254052
22-0.038527-0.73910.230164
23-0.038503-0.73860.230307
240.0340130.65250.25725
250.0145350.27880.390266



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