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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_density.wasp
Title produced by softwareKernel Density Estimation
Date of computationTue, 18 Oct 2011 18:33:50 -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/2011/Oct/18/t1318977243lg5bcvvbcz03ovs.htm/, Retrieved Wed, 01 May 2024 00:14:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=132651, Retrieved Wed, 01 May 2024 00:14:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact365

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Maximum-likelihood Fitting - Normal Distribution] [Intrinsic Motivat...] [2010-10-12 11:57:21] [b98453cac15ba1066b407e146608df68]
- RMPD    [Kernel Density Estimation] [] [2011-10-18 22:33:50] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- R PD      [Kernel Density Estimation] [Oplossing I2] [2011-10-21 13:02:01] [9e469a83342941fcd5c6dffbf184cd3a]
-   PD      [Kernel Density Estimation] [Kernel Density: E...] [2011-11-29 19:31:34] [16760482ab7535714acc81f7eb88a6ca]
- RMPD      [Percentiles] [QQ-plot: EM - geÃ...] [2011-11-29 19:42:11] [16760482ab7535714acc81f7eb88a6ca]
- RMPD      [Random Number Generator - Log-Normal Distribution] [] [2011-12-15 14:27:32] [d49626b9c7bd91ce0b695b5077c2942f]
- R PD      [Kernel Density Estimation] [Paper-KDP-I1] [2012-12-16 14:02:59] [8a32126242ff0300e413cfb1e4cb76da]
- R PD      [Kernel Density Estimation] [Kernel density pl...] [2012-12-20 13:09:25] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RMPD      [Variability] [Variability voor ...] [2012-12-20 18:45:17] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RMPD      [Variability] [Variability voor ...] [2012-12-20 18:45:17] [f8950b13b9b6c1e097d81f3c7491f9a1]
- RMP       [Kernel Density Estimation] [grafiek I3] [2014-10-15 10:40:20] [15866c21ed6246d5efde5ff3ba421193]
- RMP       [Kernel Density Estimation] [] [2014-10-15 12:49:45] [9b99fe494671b75fb711c2dc543f4e3e]
- RMP       [Kernel Density Estimation] [WS3-task3-I2] [2014-10-15 12:55:58] [81f624c2f0b20a2549c93e7c3dccf981]
- RM        [Kernel Density Estimation] [] [2014-10-15 13:03:38] [7b576ab45e161dc8fb6fe50455a3800c]
-  MP         [Kernel Density Estimation] [] [2014-12-10 12:43:00] [7b576ab45e161dc8fb6fe50455a3800c]
- RMPD      [Kernel Density Estimation] [] [2014-10-15 13:04:27] [5d70ade31d892c55b68fa1af48da4bec]
- RM        [Kernel Density Estimation] [] [2014-10-15 13:31:58] [d253a55552bf9917a397def3be261e30]
- RMPD      [Kernel Density Estimation] [WS3 task3E1] [2014-10-15 13:54:26] [46c7ebd23dbdec306a09830d8b7528e7]
- RMPD      [Kernel Density Estimation] [WS3-task3-E1] [2014-10-15 13:55:52] [81f624c2f0b20a2549c93e7c3dccf981]
-    D        [Kernel Density Estimation] [WS3-task3-E2] [2014-10-15 13:57:37] [81f624c2f0b20a2549c93e7c3dccf981]
- RMPD      [Kernel Density Estimation] [WS3 task3A1] [2014-10-15 14:01:31] [46c7ebd23dbdec306a09830d8b7528e7]
- R PD        [Kernel Density Estimation] [P AM Kernel] [2014-12-14 10:00:02] [46c7ebd23dbdec306a09830d8b7528e7]
- RMP       [Kernel Density Estimation] [] [2014-10-15 14:04:01] [eee95947b6243a1febfcd5f41483d733]
- RMP       [Kernel Density Estimation] [Gauss] [2014-10-15 14:14:04] [36781f05c04c55e165b348994b753b95]
- RM        [Kernel Density Estimation] [11] [2014-10-15 14:20:00] [e3727f74ca0896859afbe865e40a3465]
- RMP       [Kernel Density Estimation] [Q3] [2014-10-15 14:20:15] [bcf5edf18529a33bd1494456d2c6cb9a]
- RM        [Kernel Density Estimation] [] [2014-10-15 14:23:43] [63554e339c9381d8e23ab848f4176daf]
- RMP       [Kernel Density Estimation] [] [2014-10-15 14:32:55] [ae96d02647dd9ad9c105f1fa6642e295]
- RMP       [Kernel Density Estimation] [WS3 Question 3.1] [2014-10-15 14:40:44] [ce9f16fa58bb2303d66047ab4343b505]
- RMP       [Kernel Density Estimation] [] [2014-10-15 14:42:25] [fda96889f4ef6d31c0c28fd64d281011]
- RM        [Kernel Density Estimation] [Gaussian Kernel] [2014-10-15 15:52:19] [80a885d02035c87be624c190e38c794d]
- RMP       [Kernel Density Estimation] [] [2014-10-15 16:08:37] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP       [Kernel Density Estimation] [] [2014-10-15 16:10:28] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP       [Kernel Density Estimation] [] [2014-10-15 16:16:25] [dacad244957cb51472792888970d4390]
- RM D      [Kernel Density Estimation] [E3] [2014-10-15 16:19:16] [18108d1ac0353540c4304edbd3652e0f]
- RM D      [Kernel Density Estimation] [gaussian] [2014-10-15 16:32:56] [18108d1ac0353540c4304edbd3652e0f]
- RM D      [Kernel Density Estimation] [gaussian] [2014-10-15 16:32:56] [18108d1ac0353540c4304edbd3652e0f]
- RM D      [Kernel Density Estimation] [gauss] [2014-10-15 16:43:32] [18108d1ac0353540c4304edbd3652e0f]
- RM D      [Kernel Density Estimation] [gauss] [2014-10-15 16:43:32] [18108d1ac0353540c4304edbd3652e0f]
- RMP       [Kernel Density Estimation] [WS3 SHW] [2014-10-15 16:46:36] [cac6c5fb035463be46c296b46e439cb5]
- RMP       [Kernel Density Estimation] [] [2014-10-15 16:49:40] [5efa6717cfe6505454df834acc87b53b]
-    D        [Kernel Density Estimation] [] [2014-12-15 12:50:56] [5efa6717cfe6505454df834acc87b53b]
-    D          [Kernel Density Estimation] [] [2014-12-15 15:37:36] [5efa6717cfe6505454df834acc87b53b]
-    D        [Kernel Density Estimation] [] [2014-12-15 13:30:25] [5efa6717cfe6505454df834acc87b53b]
- RMPD        [Skewness and Kurtosis Test] [] [2014-12-15 13:58:54] [5efa6717cfe6505454df834acc87b53b]
- RMPD        [Notched Boxplots] [] [2014-12-15 18:33:02] [5efa6717cfe6505454df834acc87b53b]
- RMPD        [Notched Boxplots] [] [2014-12-15 18:39:45] [5efa6717cfe6505454df834acc87b53b]
- RM D      [Kernel Density Estimation] [gauss] [2014-10-15 16:50:33] [18108d1ac0353540c4304edbd3652e0f]
- RM D      [Kernel Density Estimation] [gauss] [2014-10-15 16:50:33] [18108d1ac0353540c4304edbd3652e0f]
- RM        [Kernel Density Estimation] [] [2014-10-15 16:59:41] [bca3c6529212edfac3e771806c79a908]

[Truncated]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21
16
19
18
16
23
17
12
19
16
19
20
13
20
27
17
8
25
26
13
19
15
5
16
14
24
24
9
19
19
25
19
18
15
12
21
12
15
28
25
19
20
24
26
25
12
12
15
17
14
16
11
20
11
22
20
19
17
21
23
18
17
27
25
19
22
24
20
19
11
22
22
16
20
24
16
16
22
24
16
27
11
21
20
20
27
20
12
8
21
18
24
16
18
20
20
19
17
16
26
15
22
17
23
21
19
14
17
12
24
18
20
16
20
22
12
16
17
22
12
14
23
15
17
28
20
23
13
18
23
19
23
12
16
23
13
22
18
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10
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15
23
17
17
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22
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18

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=132651&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=132651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=132651&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Properties of Density Trace
Bandwidth1.44414956238819
#Observations162

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 1.44414956238819 \tabularnewline
#Observations & 162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=132651&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]1.44414956238819[/C][/ROW]
[ROW][C]#Observations[/C][C]162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=132651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=132651&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
Bandwidth1.44414956238819
#Observations162


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ;
Parameters (R input):
par1 = 0 ;
R code (references can be found in the software module):
if (par1 == '0') bw <- 'nrd0'
if (par1 != '0') bw <- as.numeric(par1)
bitmap(file='density1.png')
mydensity1<-density(x,bw=bw,kernel='gaussian',na.rm=TRUE)
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)
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)
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)
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)
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)
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)
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')