search for: ans1

...put it in my codes. Cheers, JN rm(list=ls()) start<-rep(3,6) lo<-rep(2,6) up<-rep(4,6) flb <- function(x) { p <- length(x); sum(c(1, rep(4, p-1)) * (x - c(1, x[-p])^2)^2) } ans<-optim(start, flb, lower=lo, upper=up) ans ans<-optim(start, flb, lower<-lo, upper=up) ans ans1<-optim(start, flb, lower<-lo, upper=up) ans1 require(optimx) ans1x<-optimx(start, flb, lower<-lo, upper=up) ans1x<-optimx(start, flb, gr="gfwd",lower<-lo, upper=up) ans1<-optim(start, flb, gr=NULL,lower<-lo, upper=up)

Hi, I need to write a function that would look something like this: S <- function(b=betas){ expression(b[1] * f(b[2] * x * f(b[3] * x * f(...b[n-1] * x * f(b[n] * x)))...) } Where n is the number of element in b. Further I need to be able to evaluate S at some x numerically of course and I need to use "deriv" and produce dS/dx such that I can evaluate it also at some x. I

...20 and gives me desired result. fun = function(X, Y)          {          X + Y              #( I am just giving an example of process. Actual process is quite different.)          } result = fun(variable_1[1], variable_2[1])   # Thus, i should be getting answer 30 which I am storing in say 'ans1.csv' # ____________________________________________________________________ # My problem Suppose instead of having above dataframe having single data for variable 1 and variable 2, I have following data as variable_1           variable_2        10                         20         40     ...

Hi: I have two matrices, A and B, where A is n x k, and B is m x k, where n >> m >> k. Is there a computationally fast way to count the number of times each row (a k-vector) of B occurs in A? Thanks for any suggestions. Best, Ravi. [[alternative HTML version deleted]]

Hi, Reading about a "Heads and Tails" game in http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/amsbook.mac.pdf Introduction to Probability (Example 1.4, pp. 5-8). You toss a coin 40 times. If heads, Peter wins $1, tails, he loses $1. I think I can do that ok with: winnings <- sum(sample(c(-1,1), 40, replace=TRUE)) But I have to do it 10,000 times

...actor, but how can I mix these methods? Also, I need to be able to do post-hoc comparisons in all dimensions. Any ideas or references? I'd be happy to share more details as needed. Here is a sample from the data. All together, there are 366 subjects. There are 4 levels of Test_no (1,2,3,4), Ans1 and Ans2 are the within subject measures, and there are 8 levels of Ans* (cor, SE, CP, CPSE, FoM, FoMSE, zero, other). Thanks, again! SID Test_No Ans1 Ans2 1 1 other other 2 1 CPSE CP 3 1 other other 4 1 SE SE 5 1 FoM CP 6 1 FoM CPSE 7 2 cor cor 8 2 cor cor 9 2 cor cor 10 2 CPSE CPSE 11 2 cor cor...

library(plyr) n<-100000 grp1<-sample(1:750, n, replace=T) grp2<-sample(1:750, n, replace=T) d<-data.frame(x=rnorm(n), y=rnorm(n), grp1=grp1, grp2=grp2) system.time({ d$avx1 <- ave(d$x, list(d$grp1, d$grp2)) d$avy1 <- ave(d$y, list(d$grp1, d$grp2)) }) # user system elapsed # 39.300 0.279 40.809 system.time({ d$avx2 <- ave(d$x, interaction(d$grp1, d$grp2, drop =

...### solution 1 using mapply # proper answer, no input transform, output transform, no parallelization, no progress update sol1 <- function() { res1 <- mapply( function(i,j,k,l) { fisher.test( matrix(c(i,j,k,l), ncol=2), conf.int=F)$p.value }, i=Ax, j=Ay, k=Bx, l=By, SIMPLIFY=TRUE) ans1 <- matrix(res1,ncol=4) return(ans1) } s1 <- sol1() ### solution 2 using lapply # proper answer, input transform, output transform, no parallelization, no progress update sol2 <- function() { tmp.list <- as.data.frame(rbind(as.numeric(Ax), as.numeric(Ay), as.numeric(Bx), as.numeric(By...

Hi, I have a list in which element is a vector (all of the same length and all numeric). I want to find the mean of the first elements of the vectors, the mean of the second elements of the vectors and so on. Currently I convert the list to a data.frame and apply rowMeans(). But is there a way to to do this directly on the list? I seem to recall a post in which there was such a function (or

Hey fellas: I would like to integrate the following function: integrand <- function (x,t) { exp(-2*t)*(2*t)^x/(10*factorial(x)) } with respect to the t variable, from 0 to 10. The variable x here works as a parameter: I would like to integrate the said function for each value of x in 0,1,..,44. I have tried Vectorize to no avail. Thanks in advance, jose romero

Hi, I am just wondering if there is an easy way to count in a numeric vector how many numbers don't have replicates. For example, a=c(1,1,2,2,3,4,5), how can I know there are three numbers (3, 4 and 5) without replicates? Thank you! Jun =====

On 2/8/07, Albrecht, Dr. Stefan (AZ Private Equity Partner) <stefan.albrecht at apep.com> wrote: > Dear all, > > Thanks a lot for your comments. > > I very well agree with you that writing efficient code is about optimisation. The most important rules I know would be: > - vectorization > - pre-definition of vectors, etc. > - use matrix instead of data.frame > - do

Hi, I would have thought that these two constructions would produce the same result but they do not. Resp <- rbinom(10, 1, 0.5) Stim <- rep(0:1, 5) mm <- model.matrix(~ Stim) Xb <- mm %*% c(0, 1) ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) pnorm(as.vector(Xb), lower.tail = Resp, log.p = TRUE) > ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) [1] -0.6931472 -1.8410216

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

...manual: require(graphics) fr <- function(x) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] 100 * (x2 - x1 * x1)^2 + (1 - x1)^2 } grr <- function(x) { ## Gradient of 'fr' x1 <- x[1] x2 <- x[2] c(-400 * x1 * (x2 - x1 * x1) - 2 * (1 - x1), 200 * (x2 - x1 * x1)) } ans1<-optimx(c(-1.2,1), fr)

Hi, I apologize for the long message but the problem I encountered can't be stated in a few lines. I am having some problems with the function constrOptim. My goal is to maximize the likelihood of product of K multinomials, each with four catagories under linear constraints on the parameter values. I have found that the function does not work for many data configurations. #The likelihood

Dear R users, I have two nonlinear equations, f1(x1,x2)=0 and f2(x1,x2)=0. I try to use optim command by minimize f1^2+f2^2 to find x1 and x2. I found the optimal solution changes when I change initial values. How to solve this? BTW, I also try to use grid searching. But I have no information on ranges of x1 and x2, respectively. Any suggestion to solve this question? Thanks, Kate

Dear R-list members, I've had a hard time trying to solve a non-linear system (nls) of equations which structure for the equation i, i=1,...,4, is as follows: f_i(d_1,d_2,d_3,d_4)-k_i(l,m,s) = 0 (1) In the expression above, both f_i and k_i are known functions and l, m and s are known constants. I would like to estimate the vector d=(d_1,d_2,d_3,d_4) which is solution

...ls located in samba-3.0.0/examples/LDAP/smbldap-tools They can also be downloaded from http://www.idealx.org/prj/samba/dist/ Location of Perl Modules ################### http://www.cpan.org/modules/01modules.index.html ############################################## Install Perl LDAP and Convert ANS1 These are required for smbldap tools. Install in the following order. This can be copied and pasted in your terminal. Convert-ASN1-0.17.tar.gz tar -zxf Convert-ASN1-0.17.tar.gz cd Convert-ASN1-0.17 perl Makefile.PL make make test make install cd .. If you want to use TSL or SSL the following pac...

Hello Everyone,   Learning about R and its wonderful array of functions. If it's not obvious, I usually try to find out what a function stands for. I think this helps me remember better.   One function that has me stumped is "sink." Can anyone tell me if this stands for something?   Thanks,   Paul         __________________________________________________ [[alternative HTML