[R] Predict with loess

[Jouanin Celine]

    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) 
      [1] 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)
      [1] 34
       
      lo1 <- loess(P~year,span=0.3,degree=1)
      summary(lo1)
       
      yearCo <- 1969:2002
      year_lo <- data.frame(year = yearCo )
      length(year_lo)
      [1] 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) 
      [1] 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)
      [1] 34
       
      lo1 <- loess(P~year,span=0.3,degree=1)
      summary(lo1)
       
      yearCo <- 1969:2002
      year_lo <- data.frame(year = yearCo )
      length(year_lo)
      [1] 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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