similar to: Error using constrOptim in constraint definition

Hello there, I am using nls the first time for a non-linear regression with a logistic growth function: startparam <- c(alpha=3e+07,beta=4000,gamma=2) fit <- nls(dataset$V2~(( alpha / ( 1 + exp( beta - gamma * dataset$V1 ) ) ) ),data=dataset,start=startparam) Everything works fine and i get good results. Now I would like to improve the results using my DUMMY Variable (dataset$V6) the

Hi, How can I partitioned an example vector like this > print(myvector) [1] 30.9 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 into the following pairwise partition: PAIR1 part1 = 30.9 part2 = 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 PAIR2 part1 = 30.9 60.1 part2 = 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 .... PAIR9 part1 = 30.9

Hi, With the following codes, I attempt to convert the data.frame into a matrix. However I notice that data.matrix function doesn't seem to work. __ BEGIN__ dat <- read.table("mydata", comment.char = "!" , na.strings = "null"); # Select n-genes by random sample # n = 1 nosamp <- 1 geneid <- sequence(nrow(dat)) geneid.samp <- sample(geneid,nosamp)

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

Hi, I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. Gamlss seems to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno

Hi, I have two figures where I stacked together as one PNG. Top -> scatter plot Bottom -> density plot. However these two figures are squeezed together as rectangle figures each. (i.e. the y axes are compressed) Is there a way I can resize the figure? So that it can show proportional and complete plots? The code I have is the following: (I can also provide the figure if needed).

Dear all, I am trying to fit a double gaussian to some data using the mixdist package: --- begin code --- ? library(mixdist) ? time <- seq(673,723) ??counts <- c(3,12,8,12,18,24,39,48,64,88,101,132,198,253,331,419,563,781,1134,1423,1842,2505,374,6099,9343,13009, ? ? ? ? ? ? ? ? ? ?15097,13712,9969,6785,4742,3626,3794,4737,5494,5656,4806,3474,2165,1290,799,431,213,137,66,57,41,35,27,27,27) ?