similar to: solve nonlinear equation using BBsolve

Hi I would like to solve a system of nonlinear equations below using dfsane function   mn <- 142.36; vr <- 9335.69 ; sk <- 0.81;  kur <- 0.25 test_fn <- function(p) {    f <- rep(NA, length(p))     f[1] <- p[1]*(p [2]+p[3])- mn   f[2] <- - vr + 2*p[1]*p[2]*p[3]*(p[4]-1)+p[1]*(p[2]+p[3])^2   f[3] <- - sk + (p[1]*(p [2]+p[3])^3*(p[1]+1)*(p[1]+2)-6*p[1]*p[2]*p[3]*(p[2]+

Dear Dr. Gilbert, Dr. Varadhan and all R-help list members, I'm using the function BBsolve( ) and I have some questions on the stopping criterion "maxit" and "noimp" specified in the option "control". Here are two such examples I'm having problem with. In these two examples, the function BBsolve( ) always stops at iteration 100, overlooking the values

Dear: I am having trouble solving simultaneous nonlinear equations by R. I have been using BBsolve (BB) to do so. Though the function is very strong, still the program doesn't converge. I have tried all (according to my small knowledge) the options described in the help file. Now I am trying to find something else than BBsolve for solving simultaneous nonlinear equations by R. Any idea or

Dear R-users, I'm running an MLE procedure where some ODEs are solved for each iteration in the maximization process. I use mle2 for the Maximum likelihood and deSolve for the ODEs. The problem is that somewhere along the way the ODE solver crashes and I get the following error message: DLSODA- Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next

Hi, I'm not a programmer, so I have a question about R functions, I run the Random Forest regression models, but I would like to run the random forest model 1000 times with different random sample set. to check the uncertainty of the regression model estimates. exemple of data: ################################# table= all Y: all$AGB X variables: Variables=as.matrix(all[, c( "min",

Hello! I need some help with the linear discriminant analysis in R. I have some plant samples (divided into several groups) on which I measured a few quantitative characteristics. Now, I need to infer some classification rules usable for identifying new samples. I have used the function lda from the MASS library in a usual fashion: lda.1 <- lda(groups~char1+char2+char3, data=xxx) I'd

Dear: I am having problem with simulation. Sometimes for 100 iteration, my program works but sometimes give error message regarding some "built-in function" which I never used in my code. I have no idea about the problem. Any suggestion, comments or idea regarding this would be highly appreciable. Thanks. I have used ---- "maxLik()" and "BBsolve()" in my code. Error

Hi there, I'm trying to solve 2 nonlinear equations in 2 unknowns using the BB package. The first part of my program solves 3 ODEs using the deSolve package. This part works. The output is used as parameter values in the functions I need to solve. The second part is to solve 2 equations in 2 unknowns. This does not work. I get the error message "unexpected end of input". So what

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)+

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

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

Hello, I haven't found errors in your code. I implemented the test in the paper (the first, fixed symetric mean) and it also gives me zero Type I errors, when alpha = 0.05. Try to see the value of min(pv) or to plot the histogram of 'pv', hist(pv) and you'll see that there are no significant p-values, at that level. Anyway I'll continue to look at it, but my first

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

Dear All, I need to find the (possible multiple) zeros of a function f within an interval. I gave uniroot a try, but it just returns one zero and I need to provide it with an interval [a,b] such that f(a)f(b)<0. Is there any function to find the multiple zeros of f in (a,b) without constraints on the sign of f(a) and f(b)? Many thanks Lorenzo

I have the following matrix: > dat [,1] [,2] [,3] [,4] foo 0.7574657 0.2104075 0.02922241 0.002705617 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 and given this:

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

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

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)

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

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? ?