I am aware this has been asked before but I could not find a resolution. I am doing a logit lg <- glm(y[1:200] ~ x[1:200,1],family=binomial) Then I want to predict a new set pred <- predict(lg,x[201:250,1],type="response") But I get varying error messages or warnings about the different number of rows. I have tried data/newdata and also to wrap in data.frame() but cannot get to work. Help would be appreciated. Dirk. -- View this message in context: http://r.789695.n4.nabble.com/glm-predict-on-new-data-tp3431855p3431855.html Sent from the R help mailing list archive at Nabble.com.
Dear Dirk, You should avoid indexing in the glm call so that the name of the terms will not contain the indexing part. (Check str(lg) in your example.) A more preferred solution uses predefined data frames in the original calls: n <- 250 x <- rnorm(n) noise <- rnorm(n,0,0.3) y <- round(exp(x+noise)/(1+exp(x+noise)),digits=0) datfr <- data.frame(x=x,y=y) lg <- glm(y~x,data=datfr[1:200,],family="binomial") pred <- predict(lg,newdata=datfr[201:n,],type="response") HTH, Denes> I am aware this has been asked before but I could not find a resolution. > > I am doing a logit > > lg <- glm(y[1:200] ~ x[1:200,1],family=binomial) > > Then I want to predict a new set > > pred <- predict(lg,x[201:250,1],type="response") > > But I get varying error messages or warnings about the different number of > rows. I have tried data/newdata and also to wrap in data.frame() but > cannot > get to work. > > Help would be appreciated. > > Dirk. > > -- > View this message in context: > http://r.789695.n4.nabble.com/glm-predict-on-new-data-tp3431855p3431855.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
On 4/6/2011 2:17 PM, dirknbr wrote:> I am aware this has been asked before but I could not find a resolution. > > I am doing a logit > > lg<- glm(y[1:200] ~ x[1:200,1],family=binomial)glm (and most modeling functions) are designed to work with data frames, not raw vectors.> Then I want to predict a new set > > pred<- predict(lg,x[201:250,1],type="response") > > But I get varying error messages or warnings about the different number of > rows. I have tried data/newdata and also to wrap in data.frame() but cannot > get to work.I'll made up some data, show the way you approached it, show where it went wrong, and then how it works more easily. # data like what I think you had: y <- rbinom(200, 1, prob=.8) x <- data.frame(x=rnorm(250)) # your glm call: lg <- glm(y[1:200]~x[1:200,1],family=binomial) # take a look at print(lg). Notice that your independent variable # name is "x[1:200, 1]", which is what you would need to match in # a call to predict. # Make data.frames of the given and testing data. DF <- data.frame(y=y, x=x[1:200,1]) DF.new <- data.frame(x=x[200:250,1]) # Notice DF.new has the same name (x) as DF. lg <- glm(y~x, data=DF, family=binomial) pred <- predict(lg, newdata=DF.new, type="response") summary(pred)> Help would be appreciated. > > Dirk.-- Brian S. Diggs, PhD Senior Research Associate, Department of Surgery Oregon Health & Science University