similar to: Integrate() error message, I am at a loss

Hello! I have a problem with integrate() in my function nctspa(). Integrate produces an error message "evaluation of function gave a result of wrong length". I don't know what that means. Could anyone suggest me what is wrong with my function? These are the examples of function calls that work OK: nctspa(a=1:10,n=5) nctspa(a=1:10, n=5, mu=2, theta=3, renorm=0) This does not work:

HI >i have a problem please help me to solve it: http://r.789695.n4.nabble.com/file/n4639434/aj.pdf aj.pdf >i want to calculate the vecteur a[j] where j: 1...8 >this is the code in R: >aj.fun <- function(j, i, X, z, E, beta0, beta1){ + n <- length(X) + iX <- order(X) + iz <- order(z) + e1 <- -(beta)*z[ iz[1:(i - 1)] ] + numer <- E[j] - sum( X[ iX[1:(i - 1)] ]

Hello, fellow Rdicts, I have the code for the program below. I need to integrate a function of "x" and "p". I use integrate to integrate over "x" and pass "p" as an additional argument. "p" is specified and given default value in the argument list. Still, integrate() cannot read "p", unless I explicitly insert a numeric value in the

I am having a problem with any terms which contain hyphens in them. Is there a particular reason why this wouldn''t work? i''m using aaf, and have tried with the the previous version (pre 0.10.0) and the newest versions of both ferret and aaf. Basically, the problem is that term1-term2 is something my users want to search for, and it appears in the titles of publications,

Hi all, I am trying to construct a pairwise coocurrence matrix for certain terms appearing in a number of documents. For example I have the following table with binary values showing the presence or absence of a certain term in a document: term1 term2 term3 term4 term5 doc1 1 1 0 0 1 doc2 1 1 0 1 1 doc3 1 0 0 0 1 And I want to have a matrix with the number of the pairwise coocurrencies. So,

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

The following plot is a first approximation to what I need: *********************************** mu1 <- 0 mu2 <- 5 s <- 1 x <- seq(-2.5, 7.5, length = 41) y <- seq(-2.5, 2.5, length = 41) f <- function(x,y){ term1 <- 1/(2*pi*sqrt(s*s)) term2 <- -1/2 term3 <- (x - mu1)^2/s term4 <- (y - mu1)^2/s term5 <- (x - mu2)^2/s term1*(.5 * exp(term2*(term3 + term4)) + .5 *

Hello, I am interested in fitting a segmented model with unknown joint points in nls and perhaps eventually in nlme. I can fit this model in sas (see below, joint points to be estimated are a41 and a41), but am unsure how to specify this in the nlm function. I would really appreciate any suggestions or example code. Thanks a lot. -andy proc nlin data=Stems.Trees; params b41=-3 b42=1.5

Greetings all, I'm trying to figure out how to calculate the inverse CDF (i.e. a quantile) for a non-central F distribution. I could put together a quick numerical solver routine using the CDF, but I wonder if there's a function that I've missed that would be more efficient? Thank-you, Andrew Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885

Hi R-users,   I have this code below and I understand the error message but do not know how to correct it.  My question is how do I get rid of “with absolute error < 7.5e-06” attach to value of cdf so that I can carry out the calculation.   integrand <- function(z) { alp  <- 2.0165   rho  <- 0.868   # simplified expressions   a      <- alp-0.5   c1     <-

Hi, I'm running into a wall when trying to use the integrate function. I have the following setting: powerLaw2 <- function(x,l1,l2,c0,t0) { idx <- which(x <= 0); if (length(idx) > 0) { x[idx] <- 0; } xl <- (-l1+l2)*log(x/t0); L <- log(c0)-l1*log(x)-log(1+exp(xl)); L <- exp(L); return(L); } plCDF2 <- function(x,l1,l2,c0,t0) {

My machine has 8GB memory. I had quit all other programs that might take a lot of memory when I try the script (before I post the first message in this thread). The cdf file is of only 741 MB. It is strange to me to see the error. On Mon, Dec 28, 2009 at 2:38 AM, Wolfgang Huber <whuber at embl.de> wrote: > Dear Peng Yu > > how big is the RAM of your computer? You could try with

Hello R-Users, I'm new to R so I apologize in advance for any big mistake I might be doing. I'm trying to fit a set of samples with some probabilistic curve, and I have an important question to ask; in particular I have some data, from which I calculate manually the CDF, and then I import them into R and try to fit: I have the x values (my original samples) and the y values

Please give me some help, many thanks. I graphed a expected CDF line of a binomial distribution on a graph, And I have some observed points (observed CDF) from 4 groups fall on the smooth CDF line. I cannot really get the legend I want legend ('topleft', c('a, 'b', 'c', 'd', 'expected CDF'), col=c(1,2,3,4), pch=c(0,1,2, 3, '' ),

Dear list members, I want to draw surfaces of Dirichlet distributions with different parameter settings. My code is the following: #<begin code> a1 <- a2 <- a3 <- 2 #a2 <- .5 #a3 <- .5 x1 <- x2 <- seq(0.01, .99, by=.01) f <- function(x1, x2){ term1 <- gamma(a1+a2+a3)/(gamma(a1)*gamma(a2)*gamma(a3)) term2 <- x1^(a1-1)*x2^(a2-1)*(1-x1-x2)^(a3-1)

Hi, I need to write two inequalities depend on cumulative distribution (CDF) of beta binomial distribution where alpha and beta are unknown and need to find them. CDF of betabinomial(2,10,alpha,beta) <0.3<=CDF of betabinomial(3,10,alpha,beta) and CDF of betabinomial(5,10,alpha,beta) <0.8<=CDF of betabinomial(6,10,alpha,beta) How I can do that using r studio package? I tried to do

Hello R Helpers, Business - 64 bit windows 7, R 2.11.1 I am trying to match the character contents of one list, called 'exclude', to those of a second list, called 'dataset' dataset is a list of file names with folder locations, and looks like this when called: > dataset [1] "A/10-10-29a-13.cdf" "A/10-10-29a-14.cdf" "A/10-10-29a-15.cdf"

Hi r-users,   I hope somebody can help me to understand the error message.  Here is my code; ## Newton iteration newton_gam <- function(z) { n   <- length(z)   r   <- runif(n)   tol <- 1E-6   cdf <- vector(length=n, mode="numeric")   fprime <- vector(length=n, mode="numeric")   f   <- vector(length=n, mode="numeric")     for (i in 1:1000)   {

Hi R-users,   I have this code here: library(numDeriv)   fprime <- function(z) { alp  <- 2.0165;   rho  <- 0.868;   # simplified expressions   a      <- alp-0.5   c1     <- sqrt(pi)/(gamma(alp)*(1-rho)^alp)   c2     <- sqrt(rho)/(1-rho)   t1     <- exp(-z/(1-rho))   t2     <- (z/(2*c2))^a   bes1   <- besselI(z*c2,a)   t1bes1 <- t1*bes1   c1*t1bes1*t2 }   ## Newton

Folks, Normally, in a data frame, one observation counts as one observation of the distribution. Thus one can easily produce a CDF and (in Splus atleast) use cdf.compare to compare the CDF (BTW: what is the R equivalent of the SPlus cdf.compare() function, if any?) However, if each point should not count equally, how can I weight the points before comparing the distributions? I was thinking of