search for: denomals

Hi, I'm compiling lldiv.c from the NetBSD standard library. It works on ARM, Mips, Microblaze,ppc, ppc64, and x86_64. On i386 a very strange thing happens. Here's the source: #include <stdlib.h> #define __weak_alias(sym) __attribute__ ((weak, alias (#sym))) lldiv_t lldiv(long long int num, long long int denom) __weak_alias(_lldiv); lldiv_t _lldiv(long long num, long

Dear R-experts, I am running a large simulation exercise where the enough complicated integration is required. The integral is computed within a C-function called Denom by use of function qags from the gsl library. Here is a piece of R-code: denom<-try(.C("Denom",as.double(x),as.integer(n), as.integer(p), as.double(param),

Dear all, It was a pleasure to meet you at Iowa State University. Two days ago I submitted two experimental packages to CRAN (hope it will be there soon): rindex: quick indexing of large objects (currently only character, see ?index) regtest: some first support for automated regression testing (heavily used in \dontshow{} section of ?index) With rindex you can for example i <-

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On Fri, Jan 13, 2012 at 2:53 PM, Richard Pennington <rich at pennware.com> wrote: > Hi, > > I'm compiling lldiv.c from the NetBSD standard library. It works on ARM, Mips, > Microblaze,ppc, ppc64, and x86_64. On i386 a very strange thing happens. > Here's the source: > > #include <stdlib.h> > #define       __weak_alias(sym) __attribute__ ((weak, alias

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)] ]

Dear members, I am trying to use boot () to compute the distributions of a statistic of a data set. The statistic is defined in the following code: eds<-function(x) { r<-cor(x) paren<-1-abs(r)/2 denom<-sum(sum(paren)+0.5) desvio<-sd(x) media<-mean(x) a<-desvio/media

Dear all, I have a function to optimize for a set of parameters and want to set a constraint on only one parameter. Here is my function. What I want to do is estimate the parameters of a bivariate normal distribution where the correlation has to be between -1 and 1. Would you please advise how to revise it? ex=function(s,prob,theta1,theta,xa,xb,xc,xd,t,delta) { expo1=

Dear all, I have discovered that there are many things that I used to do in my GIS which are easily done directly in R, for example calculating interpoint distances using geoR and pick out points inside a polygon using splancs. I now wonder, is there a function to create a line object like a watercourse and then calculate the distances between many points in space and this line? I couldn't

Hi all, I have some some problem with regard to finding the integral of a function containing an indicator function. please see the code below: func1 <- function(x, mu){ (mu^2)*dnorm(x, mean = mu, sd = 1)*dgamma(x, shape=2)} m1star <- function(x){ integrate(func1, lower = 0, upper = Inf,x)$val} T <- function(x){ 0.3*dnorm(x)/(0.3*dnorm(x)+0.7*m1star(x))} func2 <-

Hi I'm trying to develop some C code to find the fixpoint of a contraction mapping, the code compiles and gives the right results when executed in R. However R-gui session is frequently terminated. I'm suspecting some access violation error due to the exception code 0xc0000005 In the error report windows 10 gives me. It is the first time I'm writing any C-code so I'm guessing I

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

Hi All, My dependent variable is a ratio that takes a value of 0 (zero) for 95% of the observations and positive non-integer values for the other 5%. What model would be appropriate? I'm thinking of fitting a GLM with a Poisson ~. Now, becuase it takes non-integer values, using the glm function with Poisson family issues warning messages. Warning messages: 1: In dpois(y, mu, log = TRUE) :

Hello everyone: I'm a new member of this group. I have a question about "oneway.test". When I use "anova(lm(....))" to analysis the ANOVA, I can get the information about Sum Sq and Mean Sq. (The R code and the results are as follows.)

I wonder if anyone out there has written a routine to solve the simple linear calibration problem? - fit regression of y vs x - estimate the value x0 (with 95% CI) that gives y0 Thanks for any help. Bill -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Hello everyone, I want to calculate type I error rate for modified F statistic for one way robust anova. I need to find the j group trimmed mean and winsorized sum of squared deviations. Here I attached my code for j=2 to make it simple. Originally I have j=4. Hope you can help. I need to run it for 1000 times My problem is: i) the value of F-test obtain from my simulation below is in negative

I have a matrix of frequency counts from 0-160. x<-as.matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,1)) I would like to apply a function creating a new column (x[,2])containing values equal to: a) log(x[m,1]) if x[m,1] > 0; and b) for all x[m,1]= 0, log(next x[m,1] > 0 / count of preceding zero values +1) for example, x[1,2] should equal log(x[2,1]/2) = log(1/2) = -0.6931472 whereas x[3,2] should

Hi. I'm using lmer() from the lme4 package (version 0.8-3) and I can't get anova() to group variables properly. I'm fitting the mixed model Response ~ Weight + Experimenter + (1|SUBJECT.NAME) + (1|Date.StudyDay) where Weight is numeric and Experimenter is a factor, ie, > str(data.df) `data.frame': 4266 obs. of 5 variables: $ SUBJECT.NAME : Factor w/ 2133 levels

I have the following function for which I need to find the root of a: f <- function(R,a,c,q) sum((1 - (1-R)^a)^(1/a)) - c * q To give context for the problem, this is a psychometric issue where R is a vector denoting the percentage of students scoring correct on test item i in class j, c is the proportion correct on the test by student k, and q is the number of items on the test in total. I

I'm getting unexpected results from the coxph function when using weights from counter-matching. For example, the following code produces a parameter estimate of -1.59 where I expect 0.63: d2 = structure(list(x = c(1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1), wt = c(5, 42, 40, 4, 43, 4, 42, 4, 44, 5, 38, 4, 39, 4, 4, 37, 40, 4, 44, 5, 45, 5, 44, 5), riskset =