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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_density.wasp
Title produced by softwareKernel Density Estimation
Date of computationFri, 26 Sep 2014 18:23:42 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Sep/26/t1411752280rnpgvcl9evm2dvv.htm/, Retrieved Sun, 12 May 2024 20:57:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=236391, Retrieved Sun, 12 May 2024 20:57:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kernel Density Estimation] [] [2014-09-26 17:23:42] [1dcac4846cc473f11733ed24aca460fa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
42.06
41.85
42
41.85
41.98
41.75
41.77
41.29
41.45
41.9
41.68
41.9
41.77
41.67
41.86
41.8
41.69
41.52
41.6
41.51
41.53
41.41
41.32
41.29
41.29
41.15
41.35
40.79
40.85
39.93
39.7
39.56
39.52
39.34
39.96
39.13
39.34
39.41
39.13
39.53
40.45
40.75
40.99
40.92
40.97
40.98
41.1
42.12
42.14
41.93
42.26
42.41
41.99
42.12
41.56
41.93
41.97
41.96
42.26
42.31
42.39
41.98
41.99
41.91
41.6
41.52
41.46
41.87
41.54
40.79
41.18
40.19
40.39
40.41
40.98
40.84
40.85
40.94
40.73
40.91
40.72
40.75
40.54
40.68
40.7
40.56
40.63
40.77
40.55
40.8
40.6
40.52
40.62
41.02
40.83
40.88
40.78
40.85
40.7
40.52
40.65
40.79
40.79
40.69
40.97
40.82
40.46
40.7
40.7
40.58
40.47
40.43
40.12
39.83
38.71
38.83
38.98
38.84
38.67
38.27
38.24
38.39
38.49
38.53
38.99
38.89
38.51
38.69
38.49
38.48
38.78
38.11
38.36
38.27
38.17
37.95
38.45
38.27
38.84
38.55
38.56
38.4
38.42
38.34
37.88
38.08
37.84
37.9
37.63
37.3
37.59
37.06
37.5
37.98
38.6
38.13
38.85
38.67
38.07
38.17
38.76
37.49
37.44
38.02
37.95
38
38.57
38.77
38.82
39.08
39.61
39.99
39.64
39.72
39.78
39.83
39.64
40
39.96
39.95
40.44
40.48
40.48
40.68
41.12
41.13
40.77
40.69
40.22
40.17
40.1
39.92
39.97
39.26
39.12
39.46
39.47
39.99
39.95
40.26
40.4
40.05
40.28
40.2
40.05
40.1
40.27
40.09
40.49
40.48
40.34
40.2
40.05
40.14
40.24
40.16
40.09
39.82
39.91
40.01
39.74
40.08
39.62
39.36
39.71
39.57
39.51
39.88
39.57
39.02
38.84
39.15
39.08
38.86
38.95
38.58
38.06
38.01
38.18
37.56
37.92
37.77
37.38
37.1
37.08
37.25
37.46
37.81
38
38.19
38.57
38.49
38.65
38.72
39.16
39.33
39.64
38.81
38.81
39.03
38.56
38.59
38.68
38.77
38.52
38.38
38.63
37.88
38.27
38.16
38.47
38.06
37.98
38.6
38.61
38.32
38.63
38.85
39.05
39.03
39.3
39.59
39.93
40.04
40.25
40.3
40.31
40.23
40.18
40.03
40.4
40.41
40.42
40.61
40.65
40.81
41.12
40.95
41.08
40.88
40.86
40.55
39.78
41.05
41.03
41
40.92
40.86
40.65
40.72
40.24
40.47
40.5
40.25
40.65
40.08
39.82
39.45
39.63
40.27
41.01
40.7
40.54
40.38
40.31
40.79
40.88
41.5
41.2
40.55
41.4
41.59
39.95
40.65
41.49
42.34
42.6
41.54
41.93
42.28
42.48
42.95
43.05
42.91
42.5
42.18
42.14
42.11
42.51
42.54
42.21
42.29
42.17
41.66
42.15
42.15
42.24
42.18
42.26
42.64
42.78
42.52
42.28
42.48
42.14
41.4
40.85
40.91
41.13
40.78
40.81
40.06
40.21
40.27
40.78
40.43
40.39
40.38
40.45
40.13
40.11
39.98
39.85
39.4
38.92
38.61
38.82
38.82
38.82
39.28
39.2
39.17
39.04
38.8
38.98
38.6
38.49
38.47
38.03
37.95
38.56
37.76
37.62
37.7
37.51
36.94
37.24
37.67
38.11
38.71
38.85
38.42
38.13
37.56
37.48
37.54
37.53
37.4
36.88
37.07
37.18
37.2
37.08
37.74
37.49
37.43
37.21
36.99
36.95
36.84
37.12
37.2
37.19
37.52
37.65
37.45
36.99
35.88
36.22
36.35
36.7
36.72
37
36.69
37.25
37.53
37.79
37.52
37.7
37.89
37.63
37.7
37.44
37.34
37.2
37.31
37.9
37.94
37.68
37.06
37.44
37.58
37.55
37.33
37.23
36.85
36.49
35.9
36.19
36.03
36.29
36.05
36.65
37.28
36.92
36.95
37.58
37.15
37.16
37.12
37
36.6
36.96
37.37
37.93
37.76
38.06
38.18
38.09
38.26
38.2
38.65
38.5
38.54
38.49
38.46
38.32
38.56
38.16
38.17
38.06
37.78
38.21
37.81
38.73
38.39
38.66
38.38
38.16
38.55
37.73
37.79
37.63
37.96
38.38
37.78
37.355
37.52
37.41
37.38
38.05
38.14
38.56
38.07
38.81
39.14
39.41
39.54
39.66
39.4
39.42
39.6
39.31
39.58
39.735
39.855
40.42
40.505
40.095
40.365
40.485
40.35
39.885
39.525
38.85
38.475
38.45
38.275
38.635
38.76
38.82
39.03
38.55
38.315
38.515
38.95
39.265
39.03
39.01
39.51
39.445
39.05
38.565
38.05
37.62
37.495
37.23
37.475
37.895
37.845
38.125
37.98
38.06
37.395
37.305
37.49
37.86
37.08
37.495
36.695
36.665
36.515
36.995
37.48
37.535
37.865
37.81
37.395
37
37.29
37.105
37.625
38.085
38.33
38.28
38.56
38.6
38.605
38.295
38.505
38.485
38.655
38.68
38.37
38.27
38.21
37.98
37.475
37.27
36.96
36.99
36.98
37.145
36.91
36.59
36.11
36.11
36.075
36.215
36.29
36.48
36.64
36.645
36.835
36.915
36.81
36.175
35.98
35.91
35.87
35.7
35.505
35.24
35.015
35.105
35.19
35.135
35.13
34.755
34.74
34.715
34.59
34.375
34.41
34.51
34.705
34.935
34.45
34.475
34.345
34.675
34.545
34.3
34.44
34.535
34.305
34.615
34.235
34.21
33.765
34.18
34.42
34.045
33.92
34.13
34.035
33.94
33.99
33.645
33.955
34.31
33.955
34.08
34
33.77
33.825
33.73
33.87
33.67
34.21
34.185
34.735
34.5
34.735
34.88
34.955
35.075
35
34.8
34.91
34.905
34.615
34.67
34.26
33.94
33.73
33.735
33.455
33.125
33.545
33.63
33.555
33.35
33.275
33.245
33.47
33.73
33.5
33.67
32.585
32.63
32.575
32.73
32.805
33.345
33.605
33.47
33.835
33.89
33.895
33.985
33.805
33.925
34.145
33.83
33.98
34.05
33.71
33.565
34.325
34.26
34.465
33.645
33.955
34.2
33.97
33.745
33.495
33.62
33.91
34.1
33.655
33.625
33.365
33.28
33.255
32.985
32.735
32.42
33.295
34.225
34.455
34.91
35.06
34.005
33.68
33.685
35.425
35.395
35.035
35.69
34.955
34.67
34.48
34.225
35.305
35.33
35.005
33.715
34.86
35.045
34.935
34.89
34.48
33.965
34.8
34.415
33.735
34.005
33.765
34.125
34.23
33.845
33.735
33.38
32
33.12
32.91
33.09
33.135
33.885
33.5
33.7
34.25
34.18
34.325
34.385
34.675
34.56
34.775
34.41
34.625
33.85
33.63
33.925
33.985
34.085
33.985
33.875
34.175
34.41
34.155
34.04
33.51
33.49
33.095
32.76
32.425
32.535
32.965
33.145
33.055
32.685
32.94
32.485
32.705
32.7
32.55
32.84
32.72
32.615
32.76
32.755
32.635
33.325
33.3
33.47
33.435
33.37
33.64
33.83
33.795
34.16
34.205
34
33.865
34.05
34.135
33.68
33.645
33.5
33.43
33.72
33.85
33.93
33.86
33.88
33.78
33.47
33.685
33.32
33.975
33.945
33.945
33.605
33.785
34.165
33.67
33.616
33.49
33.63
33.695
33.715
33.775
33.75
33.61
33.445
32.98
32.86
32.6
32.6
32.435
32.29
31.645
31.84
31.565
31.485
31.215
31.345
31.475
32.17
32.46
32.625
32.765
32.7
32.66
32.695
32.395
32.295
32.14
32.085
31.885
32.1
31.89
31.68
32.3
31.69
31.54
31.455
31.835
31.615
31.58
32.05
31.215
31.335
31.325
31.35
31.575
31.44
31.16
31.425
31.595
31.585
31.61
31.435
31.59
31.81
31.84
31.605
31.685
31.625
31.605
31.67
31.35
31.39
31.81
31.895
32.51
32.94
32.68
32.715
32.695
32.56
32.775
32.76
32.705
32.675
32.73
32.51
32.425
31.95
32.415
32.195
32.435
32.305
32.035
32.195
32.185
32.4
32.325
31.97
31.475
31.775
32.06
31.92
31.965
32.03
31.8
31.44
31.07
31.455
31.445
31.36
31.245
31.28
31.245
31.25
31.21
30.97
30.915
30.9
30.685
30.575
30.64
30.51
30.395
30.645
30.745
30.505
30.185
29.98
29.905
29.98
29.97
29.86
29.67
29.78
29.74
29.835
29.815
29.575
29.465
29.52
29.43
29.5
29.295
29.375
29.16
29.01
29.075
28.905
28.81
28.825
28.7
28.685
28.925
29.24
29.14
29.115
28.865
28.76
28.68
28.71
28.19
27.6
28.1
27.72
27.715
27.71
27.575
27.755
27.46
27.865
28.055
28.01
27.755
27.82
27.765
28.12
28.32
28.185
28.05
28.205
28.26
28.135
27.91
27.355
27.54
27.525
27.455
27.415
27.1
27.005
26.75
25.985
26.27
26.385
26.36
26.28
26.37
26.08
26.18
25.84
25.27
25.295
25.11
25.15
25.19
25.29
25.365
25.895
26.055
26.28
26.23
26.41
26.195
26.25
25.915
25.915
25.97
25.855
25.93
25.78
25.395
25.615
26.07
26.335
25.77
25.56
25.59
25.305
25.415
25.185
25.605
25.42
26.25
26.5
26.85
26.74
26.68
26.975
26.9
26.81
26.925
26.095
26.835
26.715
26.695
26.855
26.81
26.81
26.505
26.83
27
27.23
27.07
27.285
27.61
27.49
27.115
27.38
27.515
27.34
27.325
26.955
26.89
27.15
27.42
27.78
27.68
27.395
27.45
27.4
27.395
27.455
27.61
27.355
27.245
27.07
26.95
26.91
26.9
26.865
26.845
26.89
27.13
27.17
27.36
27.345
27.35
26.65
26.69
26.61
26.545
26.57
27.5
27.705
27.9
27.9
27.575
27.405
27.255
26.96
26.8
27.3
26.845
26.635
26.62
27.275
27.46
27.265
27.255
27.22
27.355
27
27.035
27.245
27.175
27.775
28.08
28.11
28.475
28.52
28.43
28.045
27.575
27.73
28.165
28.175
28.425
28.58
28.79
28.87
28.725
28.705
28.745
28.6
28.575
28.51
28.63
29.13
29.475
29.575
29.555
29.3
28.99
28.725
28.765
28.48
28.8
29.045
28.915
28.795
28.645
28.49
29.185
29.215
28.855
28.345
28.12
28.465
28.32
28.325
28.03
28.055
28.03
27.675
27.295
26.985
26.755
26.71
26.825
26.755
27.03
26.76
26.625
26.62
26.54
26.955
26.79
26.91
26.795
27.57
27.46
27.365
27.46
27.385
27.415
27.335
27.505
27.43
26.905
26.905
26.53
26.7
26.66
26.7
26.515
26.165
26.29
26.47
26.655
26.74
26.84
26.25
26.22
26.04
25.54
25.065
25.265
25.195
24.97
24.65
24.815
24.275
24.36
24.42
24.81
24.59
24.41
24.56
24.9
24.8
24.695
24.16
24.375
24.22
24.025
24.215
24.48
24.71
24.63
24.83
24.705
24.755
24.78
25.015
24.82
24.91
24.71
24.715
24.68
24.705
24.565
25.16
25.415
25.305
25.155
25.175
24.735
24.51
24.19
24.25
24.36
24.275
24.365
24.34
24.385
24.24
24.105
24.07
23.86
23.71
24.06
24.095
24.26
24.865
23.995
23.94
24.095
24.305
24.34
24.06
24.65
24.755
24.615
24.955
24.57
24.67
24.505
24.625
23.505
23.325
23.565
23.5
23.335
23.32
23.405
23.07
22.57
22.415
21.96
22.015
21.48
21.365
21.475
21.66
21.75
21.66
21.3
21.57
21.565
21.185
21.055
21.21
21.475
21.535
21.6
22.08
22.425
22.625
22.685
22.1
22.3
22.475
22.855
22.345
22.42
22.35
22.685
22.65
21.88
22.135
22.25
22.215
22.475
22.2
21.8
21.58
21.16
20.925
20.65
20.67
20.73
20.54
19.79
19.58
19.815
19.74
19.075
19.58
19.625
19.905
20.225
20.48
21.385
21.47
21.36
21.51
21.485
21.555
21.39
21.5
22.1
21.325
20.48
21.005
21.66
21.365
21.11
21.675
21.25
21.105
21.72
21.85
22
21.64
21.15
21.325
21.32
21.7
21.89
21.95
21.285
21.75
21.9
22.23
22.615
22.42
22.11
22.85
22.785
22.7
22.585
22.31
22.43
22.205
22.025
22.365
22.365
22.725
23.035
23.04
22.635
22.44
21.875
22.59
22.235
22.765
23.245
22.165
22.785
21.835
22.51
23.095
22.6
22.13
22.915
22.245
20.82
21
21.825
21.66
22.31
22.795
21.925
21.845
22.795
23.435
22.42
22.375
22.86
23.35
22.255
22.57
22.47
22.3
20.78
20.575
20.5
22.8
22.8
23.18
22.545
22.48
22.4
23.415
23.55
21.715
21.025
23.785
24.325
25.65
25.67
26.89
26.525
26.31
25.905
26.04
25.47
25.2

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236391&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236391&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236391&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Properties of Density Trace
Bandwidth1.32527786295681
#Observations1511

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 1.32527786295681 \tabularnewline
#Observations & 1511 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236391&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]1.32527786295681[/C][/ROW]
[ROW][C]#Observations[/C][C]1511[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236391&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236391&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:

Properties of Density Trace
Bandwidth1.32527786295681
#Observations1511






Maximum Density Values
Kernelx-valuemax. density
Gaussian38.84111069203270.0731148190204465
Epanechnikov39.09102589498960.0736174570824588
Rectangular38.9035894927720.0753952174934754
Triangular38.84111069203270.0727405853496776
Biweight39.09102589498960.0733733898404655
Cosine39.09102589498960.0732573231819759
Optcosine39.09102589498960.0734810106407052

\begin{tabular}{lllllllll}
\hline
Maximum Density Values \tabularnewline
Kernel & x-value & max. density \tabularnewline
Gaussian & 38.8411106920327 & 0.0731148190204465 \tabularnewline
Epanechnikov & 39.0910258949896 & 0.0736174570824588 \tabularnewline
Rectangular & 38.903589492772 & 0.0753952174934754 \tabularnewline
Triangular & 38.8411106920327 & 0.0727405853496776 \tabularnewline
Biweight & 39.0910258949896 & 0.0733733898404655 \tabularnewline
Cosine & 39.0910258949896 & 0.0732573231819759 \tabularnewline
Optcosine & 39.0910258949896 & 0.0734810106407052 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236391&T=2

[TABLE]
[ROW][C]Maximum Density Values[/C][/ROW]
[ROW][C]Kernel[/C][C]x-value[/C][C]max. density[/C][/ROW]
[ROW][C]Gaussian[/C][C]38.8411106920327[/C][C]0.0731148190204465[/C][/ROW]
[ROW][C]Epanechnikov[/C][C]39.0910258949896[/C][C]0.0736174570824588[/C][/ROW]
[ROW][C]Rectangular[/C][C]38.903589492772[/C][C]0.0753952174934754[/C][/ROW]
[ROW][C]Triangular[/C][C]38.8411106920327[/C][C]0.0727405853496776[/C][/ROW]
[ROW][C]Biweight[/C][C]39.0910258949896[/C][C]0.0733733898404655[/C][/ROW]
[ROW][C]Cosine[/C][C]39.0910258949896[/C][C]0.0732573231819759[/C][/ROW]
[ROW][C]Optcosine[/C][C]39.0910258949896[/C][C]0.0734810106407052[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236391&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236391&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:

Maximum Density Values
Kernelx-valuemax. density
Gaussian38.84111069203270.0731148190204465
Epanechnikov39.09102589498960.0736174570824588
Rectangular38.9035894927720.0753952174934754
Triangular38.84111069203270.0727405853496776
Biweight39.09102589498960.0733733898404655
Cosine39.09102589498960.0732573231819759
Optcosine39.09102589498960.0734810106407052


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = no ; par3 = 512 ;
Parameters (R input):
par1 = 0 ; par2 = no ; par3 = 512 ;
R code (references can be found in the software module):
if (par1 == '0') bw <- 'nrd0'
if (par1 != '0') bw <- as.numeric(par1)
par3 <- as.numeric(par3)
mydensity <- array(NA, dim=c(par3,8))
bitmap(file='density1.png')
mydensity1<-density(x,bw=bw,kernel='gaussian',na.rm=TRUE)
mydensity[,8] = signif(mydensity1$x,3)
mydensity[,1] = signif(mydensity1$y,3)
plot(mydensity1,main='Gaussian Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
mydensity1
bitmap(file='density2.png')
mydensity2<-density(x,bw=bw,kernel='epanechnikov',na.rm=TRUE)
mydensity[,2] = signif(mydensity2$y,3)
plot(mydensity2,main='Epanechnikov Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density3.png')
mydensity3<-density(x,bw=bw,kernel='rectangular',na.rm=TRUE)
mydensity[,3] = signif(mydensity3$y,3)
plot(mydensity3,main='Rectangular Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density4.png')
mydensity4<-density(x,bw=bw,kernel='triangular',na.rm=TRUE)
mydensity[,4] = signif(mydensity4$y,3)
plot(mydensity4,main='Triangular Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density5.png')
mydensity5<-density(x,bw=bw,kernel='biweight',na.rm=TRUE)
mydensity[,5] = signif(mydensity5$y,3)
plot(mydensity5,main='Biweight Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density6.png')
mydensity6<-density(x,bw=bw,kernel='cosine',na.rm=TRUE)
mydensity[,6] = signif(mydensity6$y,3)
plot(mydensity6,main='Cosine Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density7.png')
mydensity7<-density(x,bw=bw,kernel='optcosine',na.rm=TRUE)
mydensity[,7] = signif(mydensity7$y,3)
plot(mydensity7,main='Optcosine Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Properties of Density Trace',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',header=TRUE)
a<-table.element(a,mydensity1$bw)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#Observations',header=TRUE)
a<-table.element(a,mydensity1$n)
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,'Maximum Density Values',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Kernel',1,TRUE)
a<-table.element(a,'x-value',1,TRUE)
a<-table.element(a,'max. density',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Gaussian',1,TRUE)
a<-table.element(a,mydensity1$x[mydensity1$y==max(mydensity1$y)],1)
a<-table.element(a,mydensity1$y[mydensity1$y==max(mydensity1$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Epanechnikov',1,TRUE)
a<-table.element(a,mydensity2$x[mydensity2$y==max(mydensity2$y)],1)
a<-table.element(a,mydensity2$y[mydensity2$y==max(mydensity2$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Rectangular',1,TRUE)
a<-table.element(a,mydensity3$x[mydensity3$y==max(mydensity3$y)],1)
a<-table.element(a,mydensity3$y[mydensity3$y==max(mydensity3$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Triangular',1,TRUE)
a<-table.element(a,mydensity4$x[mydensity4$y==max(mydensity4$y)],1)
a<-table.element(a,mydensity4$y[mydensity4$y==max(mydensity4$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Biweight',1,TRUE)
a<-table.element(a,mydensity5$x[mydensity5$y==max(mydensity5$y)],1)
a<-table.element(a,mydensity5$y[mydensity5$y==max(mydensity5$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Cosine',1,TRUE)
a<-table.element(a,mydensity6$x[mydensity6$y==max(mydensity6$y)],1)
a<-table.element(a,mydensity6$y[mydensity6$y==max(mydensity6$y)],1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Optcosine',1,TRUE)
a<-table.element(a,mydensity7$x[mydensity7$y==max(mydensity7$y)],1)
a<-table.element(a,mydensity7$y[mydensity7$y==max(mydensity7$y)],1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
if (par2=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kernel Density Values',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x-value',1,TRUE)
a<-table.element(a,'Gaussian',1,TRUE)
a<-table.element(a,'Epanechnikov',1,TRUE)
a<-table.element(a,'Rectangular',1,TRUE)
a<-table.element(a,'Triangular',1,TRUE)
a<-table.element(a,'Biweight',1,TRUE)
a<-table.element(a,'Cosine',1,TRUE)
a<-table.element(a,'Optcosine',1,TRUE)
a<-table.row.end(a)
for(i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,mydensity[i,8],1,TRUE)
for(j in 1:7) {
a<-table.element(a,mydensity[i,j],1)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}