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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationMon, 16 Apr 2012 07:30:37 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/16/t1334575957sfcatww3hbv6xvi.htm/, Retrieved Sun, 28 Apr 2024 20:36:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164382, Retrieved Sun, 28 Apr 2024 20:36:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [] [2012-04-16 11:30:37] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106
88
NA
157
111
98
150
78
93
99
56
NA
NA
218
142
93
97
141
146
85
NA
170
92
NA
44
91
125
124
132
148
124
179
128
134
140
120
192
112
165
164
163
39
99
130
110
154
133
146
146
154
105
102
127
NA
100
229
159
161
205
59
157
154
184
95
165
121
137
209
108
139
119
106
94
148
118
107
145
131
151
117
123
93
166
NA
96
127
121
103
134
82
NA
93
74
134
NA
74
47
114
NA
NA
NA
135
81
157
154
123
60
NA
133
170
125
122
NA
77
117
132
116
88
NA
82
127
84
64
129
104
167
89
131
NA
67
NA
87
102
70
NA
NA
77
195
175
NA
103
91
105
121
127
54
25
124
NA
NA
NA
22
65
124
68
140
NA
82
63
94
17
NA
NA
30
79
0
43
18
6
44
136
81
54
NA
45
NA
57
NA
52
48
47
52
100
113
53
60
NA
29
85
68
80
76
96
101
49
53
63
42
69
0
60
89
52
86
NA
58
55
62
32
NA
NA
NA
NA
44
77
91
57
NA
31
77
NA
NA
81
82
43
NA
79
84
56
119
67
47
56
77
69
67
8
51
76
4
102
54
116
53
21
71
80
48
NA
78
60
64
78
94
NA
52
NA
77
67
61
50
67
NA
54
67
55
65
91
92
106
68
28
62
86
84
57
74
90
49
61
46
NA
81
31
57
76
61
53
39
NA
47
93
9
116
83
54
105
32
88
88
86
44
63
84
61
85
NA
51
56
NA
96
51
103
64
64
66
64
67
58
70
64
107
NA
45
95
111
102
84
58
52
69
NA
44
67
77
NA
NA
24
66
83
NA
NA
67
77
0
48
54
NA
84
101
NA
54
5
69
86
0
52
50
127
NA
0
0
NA
0
24
NA
NA
97
136
88
36
134
43
99
39
NA
84
62
164
NA
59
71
123
5
110
128
70
72
NA
115
123
NA
22
150
88
NA
97
NA
118
67
121
126
67
100
164
74
41
112
129
89
50
58
93
80
37
173
19
86
53
73
21
54
NA
12
6
94
45
115
76
17
18
34
106
NA
3
29
NA
64
97
NA
32
11
62
129
NA
61
96
152
NA
99
NA
102
7
94
82
145
126
90
NA
85
77
123
15
9
94
23
177
133
NA
15
41
NA
116
92
54
23
NA
154
NA
22
126
97
110
135
75
101
112
NA
24
61
126
134
95
148
44
47
3
77
NA
140
124
138
96
48
147
112
95
NA
18
78
105
33
90
132
NA
71
NA
90
127
67
177
50
104
161
95
51
107
157
178
108
162
35
NA
40
0
113
80
NA
54
85
121
102
43
70
108
73
126
10
125
NA
81
27
69
5
77
84
0
76
40
61
46
39
43
48
55
35
50
64
37
58
74
45
13
53
76
39
58
33
13
61
78
61
47
5
118
47
71
44
49
19
53
97
63
46
0
43
59
25
69
NA
35
58
64
77
0
20
54
55
44
31
47
NA
14
56
46
NA
96
37
57
56
53
63
76
74
53
30
67
21
NA
62
43
30
36
70
44
14
108
37
19
52
109
NA
58
19
129
22
28
0
25
63
44
42
NA
65
40
13
58
26
NA
48
49
53
24
19
86
66
39
90
28
4
51
NA
NA
32
45
54
66
61
36
0
84
89
54
54
85
NA
55
48
5
42
50
45
58
58
1
57
55
56
80
137
0
94
74
0
71
122
157
2
139
103
132
75
37
NA
0
64
128
NA
153
NA
77
0
130
134
NA
65
134
116
NA
128
38
69
NA
0
71
57
139
NA
88
97
42
187
15
60
94
NA
95
NA
36
109
0
94
123
180
65
132
61
115
78
162
103
172
147
114
54
74
117
145
120
95
NA
68
NA
25
157
17
147
6
108
262
NA
NA
153
135
137
55
138
NA
86
14
95
76
31
114
56
53
174
NA
144
0
27
84
112
9
0
122
232
0
38
NA
112
87
169
1
77
155
72
107
158
84
61
107
81
90
56
42
50
144
43
116
110
94
124
55
115
21
94
NA
NA
72
NA
73
22
48
50
102
7
NA
68
20
NA
2
41
32
NA
52
20
40
0
44
23
157
57
43
17
NA
23
44
158
74
37
33
1
30
NA
100
NA
75
24
29
42
NA
97
NA
NA
4
NA
29
93
NA
19
43
0
NA
30
NA
55
1
NA
20
33
79
NA
NA
25
101
94
NA
1
22
NA
16
NA
30
23
NA
83
40
NA
28
NA
2
26
55
58
52
41
32
NA
0
17
14
136
22
119
NA
NA
NA
80
33
34
NA
59
13
49
57
22
46
0
14
77
77
40
81
83
6
4
5
7
49
30
23
21
13
0
0
29
15
34
15
0
80
30
59
62
9
0
10
11
12
23
18
1
13
15
7
33
62
26
21
33
30
47
103
38
35
91
15
22
24
80
44
32
110
32
43
39
13
0
0
23
66
0
25
40
2
15
20
54
25
0
14
32
51
23
84
74
16
19
4
0
122
36
96
93
62
28
112
36
38
40
19
29
57
32
0
0
63
71
92
33
51
13
62
32
66
14
20
36
74
44
69
91
5
0
17
19
0
2
16
73
93
10
3
37
56
43
58
4
50
6
65
8
62
59
49
37
31
56
48
7
11
4
30
16
72
5
56
43
8
21
40
7
6
13
35
3
19
0
53
20
2
52
0
16
4
2
7
8
15
14
33
8
0
49
58
7
65
2
0
38
34
15
6
1
0
5
15
38
0
15
0
32
0
0
36
40
6
26
0
43
22
43
0
0
10
35
20
0
0
0
27
0
5
1
2
0
0
0
1
17
56
0
0
6
23
12
8
0
0
1
0
3
0
0
0
0
3
60
Dataseries Y:
Download CSV
Histogram 
350.57
495.67
NA
898.74
632.6
357.47
846.12
915.46
282.29
445.94
1019.06
NA
NA
969.71
290.01
505.13
370.07
414.84
220.89
662.7
NA
421.97
657.68
NA
771.58
221.39
352.67
251
565.87
480.75
485.73
536.59
496.76
654.44
544.34
612.15
548.96
414.47
626.68
215.55
664.91
241.9
329.12
548.96
243.87
3094.14
1010.35
583.64
507.83
560.93
551.14
1374.3
303.86
NA
435.17
628.42
475.44
1053.39
514.85
382.54
278.7
392.2
946.88
666.5
636.27
497.77
853.31
809.45
401.06
307.39
647.95
469.32
NA
463.23
573.77
243.78
412.96
663.18
1443.38
256.99
596.32
405.88
295.79
NA
278.28
227.09
855.67
443.12
723.1
405.07
NA
519.06
752.91
1190.79
NA
287.77
646.35
1501.45
NA
NA
NA
480.18
956.67
1094.16
861.84
424.05
1103.03
NA
581.09
295.17
301.48
332.35
NA
596.73
238.65
332.85
1117.69
332.82
NA
564.37
576.13
572.06
608.63
981.31
270.66
198.14
497.08
904.05
NA
158.91
NA
317.27
442.61
374.54
NA
NA
575.74
500.51
404.5
NA
318.54
696.64
357.43
294.23
612.52
109.52
178.17
320.26
NA
NA
NA
136.13
2285.09
703.61
188.64
472
NA
164.19
318.79
1560.17
530.08
NA
NA
338.73
783.26
226.62
366.91
935.57
426.09
427.27
526.15
352.71
346.05
NA
336.43
NA
269
NA
251.63
179.49
78.61
268.11
891.14
404.38
301.32
250.69
NA
204.82
193.18
598.93
247.5
193.25
687.81
326.87
345.16
316.75
660.17
95.53
291.34
NA
659.79
519.32
359.63
1421.92
NA
142.45
268.34
138.47
132.84
NA
NA
256.02
NA
140.7
1666.06
355.44
358.27
NA
458.16
605.64
NA
NA
152
172.49
172.97
NA
307.96
312.87
208
211.91
655.96
135.28
668.59
245.67
317.16
249.53
85.16
124.04
376.61
180.8
493.38
351.27
322.79
317.27
411.31
264.7
431.46
329.42
NA
277.26
322.13
135.43
620.68
238.45
NA
229.22
NA
274.68
175.48
562.18
241.88
194.43
NA
89.73
568
247.65
267.65
149.45
702
277.82
143.03
337.66
418.97
399.73
201.66
217.29
282.51
384.49
9
191
200.76
NA
177.69
359.66
181.98
311.28
204.44
156.21
207.95
NA
381.01
364.7
384.43
283.9
998.93
408.34
167.98
136.82
1011.99
212.84
434.09
273.03
474.26
311.86
1284.88
183.9
NA
402.63
630.05
NA
224.23
683.11
312.13
322.55
260.78
195.51
434.36
381.4
416.04
495.47
272.91
169.21
216.22
108.35
230.05
461.21
311.6
262.62
138.97
401.43
414.85
NA
294.14
359.75
160.53
NA
NA
147.88
311.07
224.73
NA
NA
172.94
216.02
42.57
125.23
273.09
NA
124.49
180.6
NA
731.33
52.13
310.01
554.46
309.05
89.39
232.27
235.3
NA
NA
NA
NA
NA
NA
NA
NA
261.43
359.13
261.8
215.55
347.17
282.64
353.12
292.71
NA
244.95
341.65
815.72
NA
232.22
313.92
255.74
827.76
390.65
288.18
139.79
271.03
NA
921.4
969.48
NA
163.04
826.36
346.38
NA
173.34
NA
NA
NA
434.44
316.55
179.59
345.63
763.06
600.75
NA
468.21
588.22
251.1
113.29
204.69
438.75
231.98
NA
337.5
NA
184.58
260.23
247.3
307.56
416.39
NA
197.6
NA
827.12
717.4
464.33
263.81
NA
181.11
147.4
387.57
NA
NA
0
381
127.86
210.05
NA
233.34
0
1272.54
239.49
NA
NA
255.64
285.53
NA
474.91
NA
400.58
215.02
480.75
426.58
344.55
349.65
313.85
NA
241.6
416.54
447.73
NA
NA
458.61
NA
895.46
265.72
NA
151.61
868.69
NA
464.77
607.24
694.98
NA
NA
811.54
NA
265.56
318.85
386.94
411.86
727.35
247.3
422.1
364.49
NA
237.35
147.23
385.35
474.04
573.73
403.25
55.21
228.69
NA
200.78
NA
267.72
284.48
562.62
332.23
NA
358.44
339.61
417.37
NA
NA
398.78
589.57
NA
381.93
575.72
NA
276.88
NA
446.87
980.06
343.88
610.94
477.66
178.15
456.62
242.4
398.44
543.42
263.26
788.88
414.81
516.89
265.23
NA
263.66
0
328.71
405.12
NA
234.05
132.48
418.49
437.2
769.06
252.02
571.26
210.7
395.04
229.21
431.52
NA
167.04
207.4
349.3
103
279.25
334.67
0
263.97
276.59
257.3
219.13
278.74
239.58
225.58
366.69
280.35
313.07
132.74
382.58
309.17
436.67
203.42
237.89
80.86
180.98
230.56
183.87
NA
NA
478.99
585.25
209.65
297.01
NA
223.98
318.08
170.76
271.68
221.15
120.63
272.69
161.98
456.31
477.94
NA
200.7
221.31
517.22
326.79
NA
455.67
885.61
179.8
268.05
155.4
113.46
327.71
556.33
200.24
114.35
244.32
NA
NA
360.2
321.09
NA
178.24
197.06
308.14
202.11
272.41
352.71
431.28
227.72
508.32
209.44
307.36
386.05
NA
274.52
323.04
198.71
105.15
442.48
225.65
63.33
222.97
0
172.95
301.47
219.21
NA
235.14
135.03
262.27
133.37
119.37
422.93
272.24
116.76
86.96
240.33
NA
211.37
218.21
158.91
327.3
194.76
NA
180.14
286.16
179.36
159.7
285.49
155.16
431.64
451.86
189.59
89.4
NA
358.95
NA
NA
344.94
732.55
273.9
342.73
255.12
139.92
0
186.72
379.14
242.02
373.91
273.79
NA
158.92
358.29
170.69
305.5
99.96
263.81
364.42
209.72
0
243.77
219.32
241.08
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
41.34
198.86
51.92
111.17
89.79
47
62.09
75.43
35.94
143.58
122.18
104.97
104.62
96.04
58.13
30.9
0
94.97
68.48
142.39
37.04
90.37
141.62
0
91.87
82.62
100.1
94.34
114.38
68.17
83.25
45.35
59.06
63.64
25.71
62.6
38.67
58.65
61.65
109.87
66.88
78.15
0
157.52
88.91
69.35
43.33
221.93
104.13
186.52
101.12
128.92
80.95
82.59
93.84
97.14
82.03
142.91
104.65
53.56
68.79
71.05
286.33
58.17
199.3
61.9
14.97
61.76
466.23
56.18
84.15
38.45
144.15
112.28
52.24
89.67
191.89
97.77
40.92
28.87
48.29
41.58
93.44
112.55
186.15
253
67.42
83.1
104.49
81.71
363.25
129.68
66.98
71.66
132.33
67.03
39.59
0
102.52
51.02
23.77
182.55
85.25
50.25
99.61
95.21
44
112.28
56.22
56.47
59.64
130.23
117.31
79.34
79.5
18.38
121.4
131.88
29.86
87.5
141.91
71.78
92.99
47.57
60.21
72.25
105.67
136.51
185.87
503.28
256.09
199.26
205.05
212.83
154.42
443.07
137.95
378.41
378.66
222.8
143.18
690.25
370.29
563.38
388.46
106.18
169.87
233.8
252.18
110.64
142.01
127.97
217.22
159.89
193.52
53.35
329.02
553.85
213.88
60.83
185.09
211.81
188.46
253.92
69.52
69.04
172.92
194
209.47
114.54
127.6
94.43
577.93
318.15
299.98
154.59
103.56
212.17
216.93
207.61
97.51
148.16
138.09
319.53
107.44
103.03
140.54
135.65
241.15
66.62
0
200.87
284.35
84.29
223.36
27.39
348.53
382.2
165.96
227.13
291.58
56.31
145.4
296.42
130.31
49.21
179.92
200.06
221.94
1
176.91
48.08
245.7
149.35
238.81
0
300.91
0
104.46
48.33
55.43
151.15
315.18
106.39
60.31
82.57
316.33
0
75.89
108.48
101.22
109.21
0
106.69
0
0
72.46
0
0
0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 7 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164382&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164382&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164382&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 time7 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Bandwidth
x axis7.96009388229584
y axis40.3462300969478
Correlation
correlation used in KDE0.492616289784104
correlation(x,y)0.492616289784104

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 7.96009388229584 \tabularnewline
y axis & 40.3462300969478 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.492616289784104 \tabularnewline
correlation(x,y) & 0.492616289784104 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164382&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]7.96009388229584[/C][/ROW]
[ROW][C]y axis[/C][C]40.3462300969478[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.492616289784104[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.492616289784104[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164382&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164382&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:

Bandwidth
x axis7.96009388229584
y axis40.3462300969478
Correlation
correlation used in KDE0.492616289784104
correlation(x,y)0.492616289784104


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = N ; par8 = terrain.colors ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = N ; par8 = terrain.colors ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
if (par3==0) par3 <- dpik(x)
if (par4==0) par4 <- dpik(y)
if (par5==0) par5 <- cor(x,y)
if (par1 > 500) par1 <- 500
if (par2 > 500) par2 <- 500
if (par8 == 'terrain.colors') mycol <- terrain.colors(100)
if (par8 == 'rainbow') mycol <- rainbow(100)
if (par8 == 'heat.colors') mycol <- heat.colors(100)
if (par8 == 'topo.colors') mycol <- topo.colors(100)
if (par8 == 'cm.colors') mycol <- cm.colors(100)
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par7=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x axis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'y axis',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation used in KDE',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation(x,y)',header=TRUE)
a<-table.element(a,cor(x,y))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')