Computing weighted average using lowess mthod in R - r

Question

I am trying to use the lowess method from R to compute the weighted average of a data set which is not uniformly distributed along x axis. For example, the first 5 data points are like this, where the first column is the x and the second is the y.
375.0 2040.0
472.0 5538.0
510.0 4488.0
573.0 2668.0
586.0 7664.0
I used the following command in R:
x<-read.table(add,header=FALSE,sep="\t")
y<-lowess(x[,1],x[,2],f=0.01)
write.table(y, file = results , sep = "\t", col.names =FALSE, row.names =FALSE)
The output looks like this:
The green line shows the average computed by the smooth function in matlab (tri-cubic kernel), and the red line is the average line computed by lowess method in R. The blue dots are the data points.
I can't find why the method in R does not work. Do you have any idea?
Here is a link to part of the data.
Thanks a lot for your help.

Answer 1

Th smooth function in matlab is like a filter ,
yy = smooth(y)
yy(1) = y(1)
yy(2) = (y(1) + y(2) + y(3))/3
yy(3) = (y(1) + y(2) + y(3) + y(4) + y(5))/5 ## convolution of size 5
yy(4) = (y(2) + y(3) + y(4) + y(5) + y(6))/5
I think it is better to do a simple smooth here.
Here some attempts using loess, lowesss with f = 0.2(1/5) and using smooth.spline
I am using ggplot2 to plot ( to use geom_jitter with some alpha )
library(ggplot2)
dat <- subset(data, V2 < 5000)
#dat <- data
xy <- lowess(dat$V1,dat$V2,f = 0.8)
xy <- as.data.frame(do.call(cbind,xy))
p1<- ggplot(data = dat, aes(x= V1, y = V2))+
geom_jitter(position = position_jitter(width = .2), alpha= 0.1)+
geom_smooth()
xy <- lowess(dat$V1,dat$V2,f = 0.2)
xy <- as.data.frame(do.call(cbind,xy))
xy.smooth <- smooth.spline(dat$V1,dat$V2)
xy.smooth <- data.frame(x= xy.smooth$x,y = xy.smooth$y)
p2 <- ggplot(data = dat, aes(x= V1, y = V2))+
geom_jitter(position = position_jitter(width = .2), alpha= 0.1)+
geom_line(data = xy, aes(x=x, y = y, group = 1 ), color = 'red')+
geom_line(data = xy.smooth, aes(x=x, y = y, group = 1 ), color = 'blue')
library(gridExtra)
grid.arrange(p1,p2)