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...rantee large differences in the results #================================CUT=========================== ln <- 100 x <- 1:ln y0 <- exp(-.02*x) y <- rnorm(y0, y0, .01) wts <- rep(1, ln) y[30] <- 1.2*y[30] wts[30] <- 1e3 model <- y ~ exp(-k*x) xydata <- list(x=x, y=y) #simple unweighted fit works as expected: r0 <- nls(model, start = c(k=.01), data = list(x=x, y=y)) #simple weighted fit works as expected: r1 <- nls(model, start = c(k=.01), data = xydata, weights = wts) #this actually performs an unweighted fit (issuing a warning):...

...rantee large differences in the results.) #================================CUT=========================== ln <- 100 x <- 1:ln y0 <- exp(-.02*x) y <- rnorm(y0, y0, .01) wts <- rep(1, ln) y[30] <- 1.2*y[30] wts[30] <- 1e3 model <- y ~ exp(-k*x) xydata <- list(x=x, y=y) #simple unweighted fit works as expected: r0 <- nls(model, start = c(k=.01), data = list(x=x, y=y)) #simple weighted fit works as expected: r1 <- nls(model, start = c(k=.01), data = xydata, weights = wts) #this actually performs an unweighted fit (issuing a warning):...

Hello, nls library provides 6 self-starting models, among them: SSfp, a four parameters logistic function. Its self-starting procedure involves several steps. One of these steps is: pars <- as.vector(coef(nls(y ~ cbind(1, 1/(1 + exp((xmid - x)/exp(lscal)))), data = xydata, start = list(lscal = 0), algorithm = "plinear"))) which assumes an initial value of lscal equal to 0. If lscal is very different to 0, the evaluation could fail (singular gradient,...), as it is the case with the dataset provided hereunder (see end of this message). As a workaround, I p...

...int(round(cbind(p, prior, post),2)) # Lattice Library PRIOR=data.frame("prior",p,prior) POST=data.frame("posterior",p,post) names(PRIOR)=c("Type","P","Probability") names(POST)=c("Type","P","Probability") xydata=rbind(PRIOR,POST) windows() xyplot(Probability~P|Type,data=xydata,layout=c(1,2),type="h",lwd=3,col="blac k") # Last command Although there is no warning or error msg after running the code (source("Chapter.2.3.R"), nothing shows up on the second window. Ho...

...gt; subj1 radius x1 x2 x3 1 436.61 1.00000 0.000000 0.000000 2 735.27 1.00000 0.000000 0.000000 3 901.73 0.96081 0.053223 -0.055439 co1 <- multinomRob(model=list(radius ~ x1 + x2 + x3), subj1, starting.values=NULL, equality=list(radius ~ x1 + x2 + x3 + 0)) Error in dimnames(XYdata$Y) <- list(NULL, XYdata$ynames) : length of 'dimnames' [2] not equal to array extent I'm coming from a background of several years with MATLAB so this particular message is all greek to me. I see an array where I have the same number of labels as columns so I have no idea what...

Hi. first things first ... thanks for ggplot2. Now my question. I'm using qplot to generate a plot as follows where X,Y,Z, A are columns in a dataframe. qplot(X, Y, data=XYDATA, color=Z, geom=c("point"), size=A) This works as expected. Factor A has three levels so there are three sizes of the point plot symbol. I understand that the factor levels are mapped to symbol sizes. However the sizes are too small for my liking. Is there any way I can specify the range...