search for: yhat2

...v.glmnet(data.train,y) # predictions by using predict function yhat_enet <- predict(myglmnet,newx=data.test, s="lambda.min") # attempting to get predictions by using coefficients beta <- as.vector( t(coef(myglmnet,s="lambda.min"))) testX <- cbind(1,data.test.std) yhat2 <- testX %*% beta # does not match plot(yhat2,yhat_enet)

Hi, See below I reply your message for <https://stat.ethz.ch/pipermail/r-help/2008-April/160966.html>[R] predict.glm & newdata posted on Fri Apr 4 21:02:24 CEST 2008 You say it ##works fine but it does not: if you look at the length of yhat2, you will find 100 and not 200 as expected. In fact predict(reg1, data=x2) gives the same results as predict(reg1). So I am still looking for a solution of this problem. best regards Maurice =========== Hi, could it be the "newdata" argument? When I run predict with the newdata a...

...akes d more readable cat("Subset of insample points --\n"); print(d) # Estimate a linear regression using all points m1 = lm(y ~ x, D) # Estimate a linear regression using only the subset m2 = lm(y ~ x, D, subset=d) # Get to predictions -- yhat1 = predict.lm(m1, D); yhat2 = predict.lm(m2, D) # And standard deviations of errors -- full.s = sd(y - yhat1) insample.s = sd(y[d] - yhat2[d]) outsample.s = sd(y[-d] - yhat2[-d]) cat("Sigmas of prediction errors --\n") cat(" All points used in estimation, in sample : ", full.s, &q...

Hi all - I'm stumped by the following mdl <- glm(resp ~ . , data = df, family=binomial, offset = ofst) WORKS yhat <- predict(mdl) WORKS yhat <- predict(mdl,newdata = df) FAILS Error in drop(X[, piv, drop = FALSE] %*% beta[piv]) : subscript out of bounds I've tried without offset, quoting binomial. The offset variable ofst IS in df. Previous postings indicate possible