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I am having a problem with a gantt chart since moving to R2.4.0. from 2.3.1 I made some adaptations to the code from http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=74 and successful produced a simple gantt chart. However when I upgraded to 2.4.0 it no longer works as desired. See http://ca.geocities.com/jrkrideau/R/gantproblem.pdf for the two charts. The charts were produced

...that's not what I'm getting. Consider the following slight modification of the first example in help('predict.lm'): set.seed(1) x <- rnorm(15) y <- x + rnorm(15) predict(lm(y ~ x)) new <- data.frame(x = seq(-3, 3, 0.5)) predict(lm(y ~ x), new, se.fit = TRUE) pred.w.plim <- predict(lm(y ~ x), new, interval = "prediction", se.fit = TRUE) pred.w.clim <- predict(lm(y ~ x), new, interval = "confidence", se.fit = TRUE) (z.confInt <- with(pred.w.clim, (fit[,3]-fit[,2])/se.fit)) pnorm(-z.confInt...

...with the new "abs" data to predict "conc" with confidence limits would be appreciated. conc<-seq(100, 280, 20) # mg/l abs<-c(1.064, 1.177, 1.303, 1.414, 1.534, 1.642, 1.744, 1.852, 1.936, 2.046) # absorbance units lm.calibration<-lm(abs ~ conc) pred.w.plim <- predict(lm.calibration, interval="prediction") pred.w.clim <- predict(lm.calibration, interval="confidence") matplot(conc, cbind(pred.w.clim, pred.w.plim[,-1]), lty=c(1,2,2,3,3), type="l", ylab="abs", xlab= "conc mg/l&quot...

...34, 32.2, 36.4, 36, 23.8, 24.4, 24, 23, 23.25, 17.5, 18.37, 20.25, 21, 19.47, 14.37, 15, 13.42, 12, 13.2, 8, 8, 7.15, 7, 8.25) predict(lm(dev1hr ~ temp+I(temp^2)+I(temp^3))) new <- data.frame(temp = seq(16, 32, 0.5)) predict(lm(dev1hr ~ temp+I(temp^2)), new, se.fit = TRUE) pred.w.plim <- predict(lm(dev1hr ~ temp+I(temp^2)+I(temp^3)), new, interval="prediction") pred.w.clim <- predict(lm(dev1hr ~ temp+I(temp^2)+I(temp^3)), new, interval="confidence") plot.new() plot.window(xlim=range(temp),ylim = range(pred.w.plim[,-1])) axis(1,at=seq(16,32,by=4...

...indows 98 R : Copyright 2001, The R Development Core Team Version 1.2.1 (2001-01-15) Dear friends. How comes this works and produce a single prediction: x <- rnorm(15) y <- x + rnorm(15) predict(lm(y ~ x)) new <- data.frame(x = seq(-3, 3, 0.5)) predict(lm(y ~ x), new, se.fit = TRUE) pred.w.plim <- predict(lm(y ~ x), new, interval="confidence") new1 <- data.frame(x=3) predict(lm(y ~ x), new1, interval="confidence") while this refuses to take the "new" and predict ? lot <- c(30,20,60,80,40,50,60,30,70,60) hours <- c(73,50,128,170,87,108,135,69,148,...

...binary composite variable (comp) and a predictor (egfr). I am trying to plot a restricted cubic spline using: require (Hmisc) require (Design) rcspline.plot(x=egfr,y=comp,model="logistic",nk=5,knots=NULL, xlab="label1", ylab="Label2", plim=c(0,1), plotcl=TRUE, showknots=TRUE, add=FALSE, lty=1, noprint=FALSE, smooth=FALSE, main="Title goes here "); I get the following error message (exactly as cut/pated): Loading required package: package Error in requirePackage("Design") : This func...

Hello, although I searched for a solution related to my problem I didn?t find one, yet. My skills in R aren?t very large, however. For my Diploma thesis I need to run a GMM estimation on a dynamic panel model using the "pgmm" - function in the plm-Package. The model I want to estimate is: "Y(t) = Y(t-1) + X1(t) + X2(t) + X3(t)" . There are no "normal" instruments

...exit1 (td=0xfffffe000b0af000, rv=0) at /usr/home/julian/src/freebsd/sys/kern/kern_exit.c:301 id = <value optimized out> p = (struct proc *) 0xfffffe000b181950 nq = <value optimized out> q = (struct proc *) 0x4 vtmp = <value optimized out> ttyvp = <value optimized out> plim = <value optimized out> reason = <value optimized out> #14 0xffffffff805c5d0e in sys_sys_exit (td=<value optimized out>, uap=<value optimized out>) at /usr/home/julian/src/freebsd/sys/kern/kern_exit.c:122 No locals. #15 0xffffffff808a6b56 in amd64_syscall (td=0xfffffe00...