[R] lm predictions for rows with missing y values
ruipbarradas at sapo.pt
Tue Apr 15 23:22:25 CEST 2014
I believe you want na.action = na.exclude.
lmnew <- lm(newy ~ newx,newdata,na.action=na.exclude)
na.action can not be set to TRUE or FALSE. From the help page ?lm
a function which indicates what should happen when the data contain NAs.
The default is set by the na.action setting of options, and is na.fail
if that is unset. The ‘factory-fresh’ default is na.omit. Another
possible value is NULL, no action. Value na.exclude can be useful.
Hope this helps,
Em 15-04-2014 21:22, Mast, Brent D escreveu:
> I'm trying to produce lm fitted values and standard errors for cases with missing y values. I know how to compute these myself with matrix algebra, but I'm wondering if there is an appropriate na.action in the lm function to do this.
> Here is some simple code where I use na.action=NULL with a dataset with 2 missing y values, but the model won't estimate. It also won't run with na.action=TRUE or FALSE. Any suggestions would be appreciated.
> Thanks much,
> Brent Mast
> x <- rnorm(15)
> y <- x + rnorm(15)
> lm <- lm(y ~ x)
> fit <- fitted(lm)
> # 2 new x cases
> newx <- c(x,-3, 3)
> # set y to NA for new cases
> newy <- matrix(,17,1)
> newy[1:15,1] <- y
> newdata <- data.frame(newy,newx)
> lmnew <- lm(newy ~ newx,newdata,na.action=NULL)
> fitnew <- fitted(lmnew)
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