similar to: Renaming names in R matrix

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

Dear R-helpers ? I have 7 data points that I want to fit a continuous curve to, that should look similar to a sine wave My data points would mark the local minima and maxima respectively. This is what I?ve got so far. And I would keep doing so, but sadly nls() then says that it has reached the maximum number of Iterations? ?

I would like to load ApoAI.RData. During the operation of reading this data an error occurs. There is also a problem with STF file. > library (limma) > load("ApoAI.RData") Warning message: 'RG' looks like a pre-2.4.0 S4 object: please recreate it > objects() [1] "RG" > names(RG) [1] "R" "G" "Rb"

Hi, I have a question about how to obtain the union of several data frame rows. I'm trying to create a common key for several tests composed of different items. Here is a small scale version of the problem. These are keys for 4 different tests, not all mutually exclusive: id q1 q2 q3 q4 q5 q6 1 A C 2 B D 3 A D B 4 C D B D I would like

Hi, I'm new to R and have a problem with a little test program (see below). Why doesn't <<- in function rk4 assign the new value to y so that it is seen in rktest. I thought that <<- does exactly this. But it seems that I didn't get it right. I would be very appreciative for an explanation of that behaviour of <<-. I know how to write the whole thing so that it

Hi, I am generating large Kac matrices (also known as Clement matrix). This a tridiagonal matrix. I was wondering whether there is a vectorized solution that avoids the `for' loops to the following code: n <- 1000 Kacmat <- matrix(0, n+1, n+1) for (i in 1:n) Kacmat[i, i+1] <- n - i + 1 for (i in 2:(n+1)) Kacmat[i, i-1] <- i-1 The above code is fast, but I am curious about

Hi, I would like to solve a system of coupled ordinary differential equations, where there is a delay (time lag) term. I would like to use the "lsoda" function "odesolve" package. However, I am not sure how to specify the delay term using the syntax allowed by odesolve. Here is an example of the kind of problem that I am trying to solve: > library(odesolve)

Dear R-gurus, Just supose I have a dara.frame that looks like myDF<-read.table(stdin(),head=T,sep=",") codID,namesp,k1,k2,k3,k4 1,spA,2,5,6,3 2,spB,4,5,4,6 3,spC,2,1,5,6 4,spC,5,4,3,2 5,spD,1,2,3,4 6,spE,2,4,3,1 I need to update the columns k1-k4 with the namesp, but considering the math between Kx and codID. My desired output must looks like: codID,namesp,k1,k2,k3,k4

I am using nls to fit a non linear function to some data. The non linear function is: y= 1- exp(-(k0+k1*p1+ .... + kn*pn)) I have chosen algorithm "port", with lower boundary is 0 for all of the ki parameters, and I have tried many start values for the parameters ki (including generating them at random). If I fit the non linear function to the same data using an external

Hi r-users, I would like to solve system of nonlinear equation using BBsolve function and below is my code.  I have 4 parameters and I have 4 eqns. mgf_gammasum <- function(p) { t  <- rep(NA, length(p)) mn <- 142.36 vr <- 9335.69 sk <- 0.8139635 kur <- 3.252591 rh  <- 0.896 # cumulants k1 <- p[1]*(p[2]+p[3]) k2 <- p[1]*(2*p[2]*p[3]*p[4] +p[2]^2+p[3]^2) k3 <-

Dear list, I am trying to create a three-way table with percent occurrence instead of raw frequencies. However, I cannot get the results I expected: I have the following table: > ftable(table( mannerDF$agem, mannerDF$target, mannerDF$manner )) <snip> 50 bak 0 0 0 0 1 0 pak 0 0 0 0 3 0 sak

Friends, I changed one line of a package at the source level and then rebuilt it. When I run R CMD check, I get an error: installing R.css in C:/polsplineRS.Rcheck ---------- Making package polsplineRS ------------ adding build stamp to DESCRIPTION making DLL ... making hareall.d from hareall.c making heftall.d from heftall.c making lsdall.d from lsdall.c making lspecall.d from lspecall.c

To whom it may concern, I am a student at Macaleste College, and next semester Macalester is going to offer a course for CellBio that is mainly statistically based. For the most part the students will be using R for analysis. The problem is there will be some simple differential equations for the students to solve. The committee that in charge of the classes corriculam would like only to

Dear members. I am having problems to understand the kmeans- results in R. I am applying kmeans-algorithms to my big data file, and it is producing the results of the clusters. Q1) Does anybody knows how to find out in which cluster (I have fixed numberofclusters = 5 ) which data have been used? COMMAND (kmeans.results <- kmeans(mydata,centers =5, iter.max= 1000, nstart =10000)) Q2) When I

Hello, I am Souradeep Chattopadhyay and I am a graduate student at Iowa State University Department of Statistics. Can anyone please explain the mathematical formulation behind the scaling matrix returned by the qda function in MASS package. I want to understand how this scaling matrix is derived from the inputs given to the qda function. Example Code The following example is using

I did this: nb <- naiveBayes(users, platform) pl <- predict(nb,users) nrow(users) ==> 314781 ncol(users) ==> 109 1. naiveBayes() was quite fast (~20 seconds), while predict() was slow (tens of minutes). why? 2. the predict results were completely off the mark (quite the opposite of the expected overfitting). suffice it to show the tables: pl: android blackberry ipad

Hi, Does anyone know if the D'agostino test is available with R ? Alex

Here is a drop-in replacement for the R incomplete beta function. src/math/pbeta.c It is a slightly modified version of the cephes library one from Netlib. In the few cases I tried it seems to give at least 14 digit agreement with the one in S-PLUS (its hard to get more). I'm not sure what performance is like. I'd like to know if it helps with some of the problems which have been

I have tried the following code to plot and save many box plots in files. The code works by itself, but does not run in a loop. The error indicates that there is no device. The error is printed below the code. Code: for(i in 1:len) { A = as.numeric(delta[Delta[i,1]]) B = as.numeric(delta[Delta[i,2]]) C = as.numeric(delta[Delta[i,3]]) D = as.numeric(delta[Delta[i,4]]) data

You need to learn how to access code for nonexported methods. See ? "::" > methods(qda) [1] qda.data.frame* qda.default* qda.formula* qda.matrix* see '?methods' for accessing help and source code Shows you that the methods are not exported from the namespace. Hence you need to use the triple colon operator to see their code: > MASS:::qda Once you have the code, I