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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 computationWed, 20 Dec 2017 00:09:23 +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/2017/Dec/20/t1513724995al6jhmvjvagwjsz.htm/, Retrieved Tue, 14 May 2024 21:31:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310430, Retrieved Tue, 14 May 2024 21:31:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85

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] [bivariate kernel ...] [2017-12-19 23:09:23] [906db62ac77b324063fa7e908483789b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
696688.604651165
352705.439528025
319574.638709679
477423.742857145
367801.886792454
274864.902439025
268557.456896553
278133.333333334
295714.876033059
248817.238095239
269479.037037038
339098.412698414
282146.621621623
276913.437500001
299348.974576272
286877.061728396
294213.424657535
274111.111111112
273200
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241181.44329897
242297.647058824
231933.287234043
304091.452991454
227886.363636364
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202128.648648649
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184500
233863.636363637
247600
NA
NA
180545
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173002.344827587
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333012.196473553
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307309.390243904
307136.375000001
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298323.513513515
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NA
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NA
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275275
244401.111111112
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172008
177301.525000001
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405286.972602741
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332993.261904763
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317777
300930
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225083.265306123
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224169.047619048
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225812.44871795
230992.475609757
248674.016393443
180400
193260.066666667
188882.025316456
206357.160000001
Dataseries Y:
Download CSV
Histogram 
19676
164151.080000001
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24611
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13210
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57152
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15196.1400000001
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NA
NA
5311
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35135.9100000001
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310566.580000001
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313847.400000001
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295136.400000001
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32916
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108930.22
53242
30391
17562
NA
382938.910000001
127634
159348
269987
84950
91396.0500000003
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110574
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50223
41619
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128499
30024
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46000
79134
926816
954690
486980
NA
151282.550000001
194692
138780
157456
95761
51712
1432439
569078.110000002
596627
782722.410000003
187814.210000001
342290.540000001
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377481
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398362
134814
372334
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45190
132012
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153366
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39074.9300000001
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1983.55000000001
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12158.26
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17283
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16823
18173.0600000001
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33092.3100000001
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453387.280000002
292009.750000001
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249710.680000001
140008.84
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174172.760000001
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263320.810000001
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65331.1800000002
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131375.55
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263951.820000001
160047

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310430&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310430&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310430&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Bandwidth
x axis26984.5732058294
y axis16068.8164133148
Correlation
correlation used in KDE0.313912226411253
correlation(x,y)0.313912226411253

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 26984.5732058294 \tabularnewline
y axis & 16068.8164133148 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.313912226411253 \tabularnewline
correlation(x,y) & 0.313912226411253 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310430&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]26984.5732058294[/C][/ROW]
[ROW][C]y axis[/C][C]16068.8164133148[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.313912226411253[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.313912226411253[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310430&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310430&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 axis26984.5732058294
y axis16068.8164133148
Correlation
correlation used in KDE0.313912226411253
correlation(x,y)0.313912226411253


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; 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')