search for: gammas

Please can someone explain why I seem to get these contradictory results? choose(5,2) [1] 10 gamma(6)/(gamma(3)*gamma(4)) [1] 10 gamma(6)/(gamma(3)*gamma(4)) == choose(5,2) [1] TRUE # all's well so far. # now look what happens: gamma(21)/(gamma(6)*gamma(16)) == choose(20,5) [1] FALSE # check individual terms: gamma(21)/(gamma(6)*gamma(16)) [1] 15504 choose(20,5) [1] 15504 # so they are the

...Error in La.chol2inv(x, size) : 'size' cannot exceed nrow(x) = 10 If I go with the Gauss-Newton algorithm I get an singular gradient matrix error, so I tried the Golub-Pereyra algorithm for partially linear least-squares. It also seems the nls model tries to find ten different gammas, but I want only one single gamma parameter for the function. I appreciate your help and support. Thank you. sol lucet omnibus Mark Hempelmann

Dear all, I am relatively new to R and have had some difficulty in understanding an error i get when running a code to solve a system of non-linear equations, with four equations and two variables. This is my code: ALPHA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) BETA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) GAMMA <- c(0.3940672148378, 0.1, 0.15,

Dear all i want to estimated the parameter of the gamma density(a,b,d) f(x) = (1/gamma(b)*(a^b)) * ((x-d)^(b-1)) * exp{-(x-d)/a)} for x>d f(x) = Age specific fertility rate x = age when i run this in R by usling nls() gamma.asfr <- formula(asfr ~ (((age-d)^(b-1))/((gamma(b))*(a^b)))* exp(-((age-d)/a))) gamma.asfr1 <- nls(gamma.asfr, data= asfr.aus, start = list(b = 28, a = 1, d= 0.5),

Hi! I would like to perform an F-Test over more than one variable within a generalized mixed model with Gamma-distribution and log-link function. For this purpose, I use the package mgcv. Similar tests may be done using the function "anova", as for example in the case of a normal distributed response. However, if I do so, the error message "error in eval(expr, envir, enclos) :

Hi, I was wondering if someone can help me interpret the results of running weibreg. I run the following and get the following R output. > weibreg(Surv(time, censor)~covar) fit$fail = 0 Call: weibreg(formula = Surv(time, censor)~covar) Covariate Mean Coef Rel.Risk L-R p Wald p covar 319.880 -0.002 0.998 0.000 log(scale) 0.000 8.239

Dear all, Lets say I have the following data frame: > set.seed(1) > col1 <- c(rep('happy',9), rep('sad', 9)) > col2 <- rep(c(rep('alpha', 3), rep('beta', 3), rep('gamma', 3)),2) > dates <- as.Date(rep(c('2009-10-13', '2009-10-14', '2009-10-15'),6)) > score=rnorm(18, 10, 3) > df1<-data.frame(col1=col1,

Colleagues, I am fitting an Emax model using nls. The code is: START <- list(EMAX=INITEMAX, EFFECT=INITEFFECT, C50=INITC50) CONTROL <- list(maxiter=1000, warnOnly=T) #FORMULA <- as.formula(YVAR ~ EMAX - EFFECT * XVAR^GAMMA / (XVAR^GAMMA + C50^GAMMA)) ## alternate version of formula FORMULA <- as.formula(YVAR ~ EMAX - EFFECT / (1 + (C50/XVAR)^GAMMA)) FIT <-

Could I have some suggestions as to how (various ways) I can display my confidence interval results? rm(list = ls()) set.seed(1) func <- function(d,t,beta,lambda,alpha,p.gamma,delta,B){ d <- c(5,1,5,14,3,19,1,1,4,22) t <- c(94.32,15.72,62.88,125.76,5.24,31.44,1.048,1.048,2.096,10.48) post <- matrix(0, nrow = 11, ncol = B) theta <- c(lambda,beta) beta.hat <- 2.471546 for(j

I'm looking for goodness of fit tests for gamma distributions with large data sizes and for different data. I have a matrix with around 4.000 data values in it and i have fitted a gamma distribution with "fitdistr". You can see the example: > fitdistr(corpo,"gamma",lower=0.001) Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000, :

What??s happening with this following code: require(sem) Celpe.Mod.RAM <- matrix(c( # path parametro Inicio "Produ????o -> T1", "gamma.11", NA, "Produ????o -> T2", "gamma.12", NA,

Dear R users, I have to calculate gamma functions for negative numbers beyond -171.4. e.x. gamma(-500.4) I got following: > gamma(-170.4) [1] -5.824625e-308 > gamma(-171.4) [1] 0 Warning message: underflow occurred in 'gammafn' I have tried to use a recursion getting values a little futher -180. How could I solve this problem? Thank you beforehand. Chuse.

Greetings, all I am having difficulty getting the fitdistr() function to return without an error on my data. Specifically, what I'm trying to do is get a parameter estimation for fracture intensity data in a well / borehole. Lower bound is 0 (no fractures in the selected data interval), and upper bound is ~ 10 - 50, depending on what scale you are conducting the analysis on. I read in the

I am having following problem: I?m constructing model for calculation of area of triangle. I know sides a, b, and gamma angle. I wish to calculate the area using heron?s formula: S <- sqrt(s*(s-a)*(s-b)*(s-c)) where s <- (a+b+c)/2 and c is calculated using law of cosines: c <- sqrt(a^2 + b^2 -2*a*b*cos(gamma)) since i am calculating a regression model, i need derivation of this

Santi, In the second line of your function you have the following: f <- numeric(length(x)) This sets the length of this numeric vector (i.e., "f") to the length of the vector "x". Later, inside the function you assign to values to 4 elements of the vector "f". This assumes that "f" is at least 4 element in length. However, you define

Hi, all How can generate a sample from truncated inverse gamma distribution in R? thanks

Hello, I'm having problems getting my samba setup to work at a little LAN i partially maintain. I've been reading quite a lot about what I could think of being related to my problems/setup, and I've also googled my ass off :( So here I am, resorting to you guys in hope of help =] Sorry to say, but I don't have much experience, and therefore I'm a bit lost at the moment. Not

Hi, I'm using R to do a series of calculation and I have gotten several warnings that say "NaNS produced". Whatever I could read on line gives me an idea that this warning is produced when the number is use is a negative log or otherwise mathematically problematic. I'm getting this error while using factorial() and gamma () on strictly positive numbers (always greater than zero).

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

I have to calculate some formula like: gamma(x)/(gamma(x+y) and I observed that for relatively big values of x, R returns infinity and so cannot compute the formula. Is it possible to force R to give the real value of gamma(x) instead of Inf ? thanks