search for: lik

...With the following Sweave minimal file: ---<--------------------cut here---------------start------------------->--- \documentclass{article} \usepackage{Sweave} \begin{document} <<binom-sim>>= thetas <- seq(0, 1, by=0.001) prior <- rep(1, length(thetas)) / length(thetas) lik <- dbinom(1, 1, thetas) lik.p <- prior * lik post <- lik.p / sum(lik.p) <<binom-sim-fig, fig=TRUE, include=FALSE, height=3, echo=FALSE>>= layout(matrix(1:2, ncol=2)); par(mar=c(5, 4, 2, 1), cex=0.75) matplot(thetas, cbind(prior, lik, post), type="l", lty=c(2, 1, 1),...

Hi the list, I would need some advice on something that looks like a FAQ: the possibility of providing vectors to optim() function. Here is a stupid and short example summarizing the problem: -------------------------------- example 1 ------------ 8< ---------------------- library(stats4) data <- rnorm(100,0,1) lik1 <- function(m, v, data) { N <...

...ebook/panel4pt1.fn that applied to my data and in the console is as follows: > `desman.y` <- structure(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3", "4", > "5")) > > RN<-function(y=desman.y,J=5,nsites=39,Nmax=100){ + #### + lik<-function(parms){ + r<-expit(parms[1]) + lambda<-exp(parms[2]) + pvec<-1-(1-r)^(0:Nmax) + gN<-dpois(0:Nmax,lambda) + gN<-gN/sum(gN) + lik<-rep(NA,nsites) + for(i in 1:nsites){ + lik[i]<-sum(dbinom(y[i...

...ead.table("wtmatrix.txt",header=T,na.strings=T) elev<-data[,"elev"] forest<-data[,"forest"] elev<-scale(elev,center=TRUE) forest<-scale(forest,center=TRUE) pamat<-data[,c("y.1","y.2","y.3")] z<-pamat[,1] M<-length(z) lik<-function(parms){ b0<-parms[1] b1<-parms[2] b2<-parms[3] b3<-parms[4] ones<-rep(1,M) ### Compute binomial success probabilities probs<-expit(b0*ones+b1*elev+b2*(elev^2)+b3*forest) lik<-rep(0,length(z)) ### evaluate log of binomial...

...t;-`(`*tmp*`, value = c("V", "R")) : length of 'dimnames' [2] not equal to array extent" When I type in length(dimnames(data11a)[2]) I get the answer: [1] 1 which seems odd when dimnames(data11a)[2] gives [[1]] [1] "V" "R" I would like to ask "How can I get the names of the second dimension of the array(data11a) to have length "2" ? It seems to me that the analysis will run if I can make this array have the correct length dimnames I thank you for your help. ____________ * fd.data11a = data11a DEfd11a = Da...

Hi, I have reconstructed ancestral character states on a phylogeny using MuSSE in the diversitree package and plotted the character state probabilities as pie charts on the nodes. I would, however, like to colour the character states of my extant species, i.e. the tip labels, the same colours as my pie charts, such that all species in state 1 are e.g. blue, species in state 2 red and species in state 3 yellow, and have not been successful with my attempts. I am only able to colour them in repea...

Hello, I am trying to bootstrap a function that extracts the log-likelihood value and the nls coefficients from an nls object. I want to sample my dataset (pdd) with replacement and for each sampled dataset, I want to run nls and output the nls coefficients and the log-likelihood value. Code: x<-c(1,2,3,4,5,6,7,8,9,10) y<-c(10,11,12,15,19,23,26,28,28,30) pdd...

I'd like to have a class A that computes a likelihood, and a subclass B that computes the same likelihood by sometimes throws in an additional term (B includes measurement error). So B's likelihood needs to call A's, and then (sometimes) multiply by an additional term. It sounds as if, in the S3...

Hi, My name is Laura. I'm a PhD student at Queen's University Belfast and have just started learning R. I was wondering if somebody could help me to see where I am going wrong in my code for estimating the parameters [mu1, mu2, lambda1] of a 2-phase Coxian Distribution. cox2.lik<-function(theta, y){ mu1<-theta[1] mu2<-theta[2] lambda1<-theta[3] p<-Matrix(c(1, 0), nrow=1, ncol=2) Q<-Matrix(c(-(lambda1 + mu1), 0, lambda1, -mu2), nrow=2, ncol=2) q<-Matrix(c(mu1, mu2), nrow=2, ncol=1) for (i in 1:l...

hi folks, I'm trying to build a table that contains information about a series of General Linear Models in order to calculate Akaike weights and other measures to compare all models in the series. i have an issue with indexing models and extracting the information (loglikehood, AIC's, etc.) that I need to compile them into the table. Below is some sample code that illustrates my approach so far and my problem. I realize that somehow i need to provide actual object for the AIC or LogLik call, and I've tried a couple of different ideas (e.g., as.name, expr...

Hello, I am trying to use optim() on a function involving a summation. My function basically is a thinned poisson likelihood. I have two parameters and in most cases optim() does a fine job of getting the minima. I am simulating my data based on pre specified parameters, so I know what I should be getting. However when my true parameters fall in a particular range, optim() gives incorrect results. I have g...

...ector("numeric",length(1:2)) for (k in 1:2){ ll<-function(p){ cmh<-delta[,k]*(h[,k]*log(0.5))+p*log(gamma(1+1/p)) for(s in 1:10){ integrand<-function(x) x^d[s,k]*exp(-x*gamma(1+1/p))^p*p*x^(p-1)*exp(-x*h[s,k]) } integ<-integrate(integrand,0,Inf)$value cmhn<-as.vector(cmh) lik<-sum(cmhn+integ) -lik } initial<-c(1) t<-nlm(ll,initial) out[k]<-t$estimate } est<-as.vector(out) -- View this message in context: http://r.789695.n4.nabble.com/Error-in-integrate-integrand-0-Inf-non-finite-function-value-tp4646868.html Sent from the R help mailing list archive a...

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...use of adapt. I'm new to R so I would appreciate any comment on my code below. Thanks Angelo ---------------------------------------------------------------------------------------------------------- DATA<-read.table("Data.csv",header=TRUE,sep=",") library(adapt) mnl.lik<-function(theta,y){ th1<-theta[1] th2<-theta[2] tha<-theta[3] thb<-theta[4] thc<-theta[5] thp<-theta[6] thmu<-theta[7] alfz1<-theta[8] alfz2<-theta[9] alfc<-theta[10] alf<-theta[11] r<- 1 s<- 1 n<-2000 lik<-numeric(n) int<-numeric(n) v<- numeric...

...R for a standard normal distribution, I've been trying for a good week or so now with multiple attempts and have finally given up trying to do it on my own as I'm beginning to run out of time for this, would somebody please tell me what is wrong with my latest attempt: n=100 mu=0 sigma=1 lik<-function(theta) exp(((theta-mu)^2)/2*sigma) alpha<-function(theta,phi) min(lik(phi)/lik(theta),1) theta1<-matrix(0,n,2) theta1[1,]<-mu for(i in 2:n){ theta<-theta1[i-1,] phi<-theta+runif(-0.5,0.5) k<-rbinom(1,1,alpha(theta,phi)) k1<-k1+k theta1[i,]<-theta+k*(phi-theta) }...

...ocuments/PhD/Swaption vols.csv" , header=TRUE, sep=",") X<-ts(vols[,2]) #X dcOU<-function(x,t,x0,theta,log=FALSE){ Ex<-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t) Vx<-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2]) dnorm(x,mean=Ex,sd=sqrt(Vx),log=log) } OU.lik<-function(theta1,theta2,theta3){ n<-length(X) dt<-deltat(X) -sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE)) } require(stats4) require(sde) set.seed(1) #X<-sde.sim(model="OU",theta=c(3,1,2),N=10000,delta=1) mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1), m...

hi , lik <- function(nO, nA, nB, nAB){ loglik <- function(par) { p=par[1] q=par[2] r <- 1 - p - q if (c(p,q,r) > rep(0,3) && c(p,q,r) < rep(1,3) ) { -(2 * nO * log (r) + nA * log (p^2 + 2 * p * r) + nB * log (q^2 + 2 * q * r)...

...2,1,0,0,1,1,0,1,2,2,1,0),nrow=10,ncol=2) h<-matrix(runif(20,0,1),10) integ<-matrix(c(0),nrow=10, ncol=2) ll<-function(p){ for (k in 1:2){ for(s in 1:10){ integrand<-function(x) x^d[s,k]*exp(-x*gamma(1+1/p))^p*p*x^(p-1)*exp(-x*h[s,k]) integ[s,k]<-integrate(integrand,0,Inf)$value } } lik<-colSums(integ) -lik } initial<-c(1) t<-nlm(ll,initial) Error in nlm(ll, initial) : invalid function value in 'nlm' optimizer Any suggestions will be greatly appreciated. Thank you in advance -- View this message in context: http://r.789695.n4.nabble.com/likelihood-function-...

...red-expressed model fit-step") would be appropriate: GoF.ltm <- function(object, B = 50, ...){ liFits <- list() for(i in 1:B){ rndDat <- rmvlogis(nrow(object$X), coef(object)) liFits[[i]] <- ltm(rndDat ~ z1) } distr <- sort(sapply(liFits, function(x)return(x$log.Lik))) return(max(which(distr <= object$log.Lik))/length(distr)) } The rationale behind was to directly use the sorted sequence of (log)likelihoods of models fitted to 2PL-fitting-datasets where the parameters of <object> hold. The return value was intented to roughly mirror how many 2PL-Da...

...<-rownames(data11, do.NULL = FALSE, prefix = "Obs.") colnames=c("V","R") varnames=c("one","two") dimnames(data11)<-list(rownames(data11), varnames, colnames) data11a<-as.array(data11, dimnames=dimnames(data11)) The analysis that I would like to do with R(CollocInfer) runs as follows(I print for the sake of introduction here though to run this line of code requires extensive setup) res11a = inneropt(coefs, times=times, data=data11a, lik=lik, proc=proc, pars=spars, in.meth='nlminb', control.in=control.out) The response I get...