search for: nlls

...r me, as a novice functioneer, to figure out what's going wrong. Here's my example for deltaMethod(): t <- c(0.00000, 26.24551, 61.78180, 86.88254, 221.75480) m <- c(48.591707, 15.655895, 12.284635, 5.758547, 0.000000) dat <- data.frame(t = t, m = m) m0 <- m[1] t0 <- t[5] nlls <- nls(m ~ (m0^(1/lambda) - (t * m0/t0)^(1/lambda))^lambda, start = list(lambda = 1), data = dat) xVal <- seq(0, t0, length = 10) mod.SE <- list() for(i in 1:length(xVal)){ z <- xVal[i] mod.SE[[i]] <- deltaMethod(nlls, "(m0^(1/lambda) - (z * m0/t0)^(1/lambda))^lambda&quot...

Hey, So I have a scatter plot and I am trying to plot a curve to fit the data based on a Holling Type III functional response. My function is this: nll2<-function(a,b) { conefun<-(a*DBH^2)/(b^2+DBH^2) nlls2<-dnbinom(x=cones ,size=DBH, mu=conefun,log=TRUE) -sum(nlls) } and my plot is this: plot (DBH,cones) DBH is on the x-axis and cones is on the y-axis. How do I get the curve for my function onto the scatterplot? -- View this message in context: http://r.789695.n4.nabble.com/Plotting-a-cu...

...e complex model with 7 parameters (two of these parameters are equal in the 6-parameter model) by minimizing the corresponding NLL with "optim". In theory the 7-parameter model should fit the data either equally or better than the 6-parameter model. Therefore the difference of the minimal NLLs should be 0 or larger. For 500 data sets I use the following code: require(odesolve) res=matrix(nrow=500,ncol=18) colnames(res)=c("a_23","beta_23","mu_23","d_23","I_23","M_23","NLL_23", "a_21","...

Hi, We are preparing to make the release of OpenSSH 4.8 soon, so we would greatly appreciate testing of snapshot releases in as many environments and on as many operating systems as possible. The highlights of this release are: * Added chroot(2) support for sshd(8), controlled by a new option "ChrootDirectory". Please refer to sshd_config(5) for details, and please use this

Hello, I'm new to this and am trying to teach myself some R by plotting biological data. The growth curve in question is supposed to be fitted to the Verhulst equation, which may be transcribed as follows: f(x)=a/(1+((a-0.008)/0.008)*exp(-(b*x))) - for a known population density (0.008) at t(0). I am trying to rework the example from "An Introduction to R" (p. 72) for my case and