Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
7263.63 7135.88 7008.00 6752.38 9339.00 9211.13 7263.63 5970.38 6098.13 6098.13 6226.00 6495.50 5714.75 4932.75 4292.38 4292.38 6752.38 7008.00 5060.50 2857.38 4022.88 4022.88 4932.75 5457.88 5330.00 4022.88 4677.13 4420.25 6623.38 6098.13 4022.88 2472.75 3895.00 4292.38 4677.13 5188.38 4150.63 3254.75 3639.50 3767.25 7135.88 7135.88 5188.38 4932.75 5714.75 5330.00 6367.75 7661.00 7917.88 6098.13 5585.63 5060.50 8570.88 8827.75 8173.50 8827.75 8698.63 7661.00 8827.75 10121.00 10646.13 9083.38 8045.63 8827.75 12196.25 13234.00 12978.38 13489.50 13361.75 12068.50 14271.63 14796.75 15564.88 13234.00 12324.13 13361.75 15834.38 18037.50 17512.38 17512.38 17769.25 16872.00 19204.25 19204.25 18806.88 16602.50 16999.88 17256.75 18947.38 21150.50 19587.63 20369.75 19715.50 19332.00 22317.25 21663.00 20753.13 19459.88 20753.13 21407.38 22188.13 23225.75 22188.13 22828.50 22047.63 21919.88 25160.63 25430.13 24392.50 22572.88 24123.00 24776.00 25558.00 26723.50 25558.00 26467.88 26070.50 24648.13 27633.25 27633.25
Sample Range:
(leave blank to include all observations)
From:
To:
Smoothing Bandwidth (leave zero for default)
Display values
(?)
no
no
yes
Number of density points
(?)
Chart options
Label y-axis:
Label x-axis:
R Code
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') ab<-table.start() ab<-table.row.start(ab) ab<-table.element(ab,'Properties of Density Trace',2,TRUE) ab<-table.row.end(ab) ab<-table.row.start(ab) ab<-table.element(ab,'Bandwidth',header=TRUE) ab<-table.element(ab,mydensity1$bw) ab<-table.row.end(ab) ab<-table.row.start(ab) ab<-table.element(ab,'#Observations',header=TRUE) ab<-table.element(ab,mydensity1$n) ab<-table.row.end(ab) ab<-table.end(ab) a <- ab table.save(ab,file='mytable123.tab') b<-table.start() b<-table.row.start(b) b<-table.element(b,'Maximum Density Values',3,TRUE) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Kernel',1,TRUE) b<-table.element(b,'x-value',1,TRUE) b<-table.element(b,'max. density',1,TRUE) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Gaussian',1,TRUE) b<-table.element(b,mydensity1$x[mydensity1$y==max(mydensity1$y)],1) b<-table.element(b,mydensity1$y[mydensity1$y==max(mydensity1$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Epanechnikov',1,TRUE) b<-table.element(b,mydensity2$x[mydensity2$y==max(mydensity2$y)],1) b<-table.element(b,mydensity2$y[mydensity2$y==max(mydensity2$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Rectangular',1,TRUE) b<-table.element(b,mydensity3$x[mydensity3$y==max(mydensity3$y)],1) b<-table.element(b,mydensity3$y[mydensity3$y==max(mydensity3$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Triangular',1,TRUE) b<-table.element(b,mydensity4$x[mydensity4$y==max(mydensity4$y)],1) b<-table.element(b,mydensity4$y[mydensity4$y==max(mydensity4$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Biweight',1,TRUE) b<-table.element(b,mydensity5$x[mydensity5$y==max(mydensity5$y)],1) b<-table.element(b,mydensity5$y[mydensity5$y==max(mydensity5$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Cosine',1,TRUE) b<-table.element(b,mydensity6$x[mydensity6$y==max(mydensity6$y)],1) b<-table.element(b,mydensity6$y[mydensity6$y==max(mydensity6$y)],1) b<-table.row.end(b) b<-table.row.start(b) b<-table.element(b,'Optcosine',1,TRUE) b<-table.element(b,mydensity7$x[mydensity7$y==max(mydensity7$y)],1) b<-table.element(b,mydensity7$y[mydensity7$y==max(mydensity7$y)],1) b<-table.row.end(b) b<-table.end(b) a <- b[1] table.save(b,file='mytable2a.tab') 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) if (par2=='yes') { 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) } } else { a<-table.row.start(a) a<-table.element(a,'Kernel Density Values are not shown',8) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation