# [R] Predict with loess

From: Jouanin Celine <celine_jouanin_at_yahoo.fr>
Date: Tue 13 Jun 2006 - 18:37:31 EST

I want to do a nonparametric regression. I’m using the function loess.

```      The variable are  the year from 1968 to 1977 and the dependant variable is  a proportion P. The dependant variable have  missing value (NA).
The script is :

year <- 1969:2002
length(year)

 34

P <- c(NA,0.1,0.56,NA,NA,0.5,0.4,0.75,0.9,
0.98,0.2,0.56,0.7,0.89,0.3,0.1,0.45,0.46,0.49,0.78,
0.25,0.79,0.23,0.26,0.46,0.12,0.56,0.8,0.55,0.41,
0.36,0.9,0.22,0.1)
length(P)

 34

lo1 <- loess(P~year,span=0.3,degree=1)
summary(lo1)

yearCo <- 1969:2002
year_lo <- data.frame(year = yearCo )
length(year_lo)

 34

mlo <- predict(loess(P~year,span=0.3,degree=1),new.data=year_lo,se=T)
mlo\$fit
mlo\$se.fit

plot(year,P,type='o')
lines(year,predict(loess(P~year,span=0.15,degree=1),new.data=year_lo,
se=T,na.action=na.omit)\$fit,col='blue',type='l')

The message error  indicates that x and y don’t have the same length.

In fact in m\$fit  and m\$se.fit there are 3 values who don’t   have a fitted value.

There is no predicted value when the dependant variable have  a NA. The synthase na.action=na.omit don’t seem to ignore the missing value, generating  an error.
What is the source, the solution to my problem?
Thanks for the help
Céline    I want to do a  nonparametric regression. I’m using the function loess.
The variable are  the year from 1968 to 1977 and the dependant variable is  a proportion P. The dependant variable have  missing value (NA).
The script is :

year <- 1969:2002
length(year)

 34

P <- c(NA,0.1,0.56,NA,NA,0.5,0.4,0.75,0.9,
0.98,0.2,0.56,0.7,0.89,0.3,0.1,0.45,0.46,0.49,0.78,
0.25,0.79,0.23,0.26,0.46,0.12,0.56,0.8,0.55,0.41,
0.36,0.9,0.22,0.1)
length(P)

 34

lo1 <- loess(P~year,span=0.3,degree=1)
summary(lo1)

yearCo <- 1969:2002
year_lo <- data.frame(year = yearCo )
length(year_lo)

 34

mlo <- predict(loess(P~year,span=0.3,degree=1),new.data=year_lo,se=T)
mlo\$fit
mlo\$se.fit

plot(year,P,type='o')
lines(year,predict(loess(P~year,span=0.15,degree=1),new.data=year_lo,
se=T,na.action=na.omit)\$fit,col='blue',type='l')

The message error  indicates that x and y don’t have the same length.

In fact in m\$fit  and m\$se.fit there are 3 values who don’t   have a fitted value.

There is no predicted value when the dependant variable have  a NA. The synthase na.action=na.omit don’t seem to ignore the missing value, generating  an error.
What is the source, the solution to my problem?
Thanks for the help
Céline
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