search for: theta1

...o 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= exp(s[3]*xa+s[4]*xb+s[5]*xc+s[6]*xd) expo2= exp(s[9]*xa+s[10]*xb+s[11]*xc+s[12]*xd) expo3= exp(s[15]*xa+s[16]*xb+s[17]*xc+s[18]*xd) expo4= exp(s[21]*xa+s[22]*xb+s[23]*xc+s[24]*xd) expo5= exp(s[27]*xa+s[28]*xb+s[29]*xc+s[30]*xd) nume1=prob[1]*(s[2]^-s[1]*s[1]*t^...

Hi I am trying to find a parametric bootstrap confidence interval and when I used the boot function I get zero bias and zero st.error? What could be my mistake? Thank you and take care. Laila [[alternative HTML version deleted]]

Dear list I am calling the functiton bugs() provided by R2WinBugs to performs an IRT analysis. The function returns a set of estimated parameters over n replications/iterations. For each replication, two sets of person measures (theta1 and theta2) and two sets of item difficulty parameters (diff1 and diff2) are returned. The code used to obtain these estimates is as follows: sim <- bugs(data,init,model.file="drift.bugs",parameters=c("theta1","theta2","diff1","diff2"),n.chains=...

Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 = -0.05538), data=mod14data2_random) However, I got this error: Error in nls(y ~ theta1 - theta2 * exp(-theta3 * x), start = list(t...

...irst stopping index. E.g. If my first stopping index was 5. I want to set 6th observation from the generated normal variables as the first random number, and I stop at second stopping index. This is my code, alpha <- 0.05 beta <- 0.07 a <- log((1-beta)/alpha) b <- log(beta/(1-alpha)) theta1 <- 2 theta2 <- 3 cumsm<-function(n) {y<-NULL for(i in 1:n) {y[i]=x[i]^2} s=sum(y) return(s) } psum <- function(p,q) {z <- NULL for(l in p:q) {...

Hi, Could you please let me know to use a list in a for loop here geneset is a loop.I am trying to match the names of the list with 1st row of the output. result<- list() for(i in 1:length(output) { result[[i]] <- geneset(which(geneset %n% output[,1])) } Kindly help me out -- View this message in context: http://www.nabble.com/For-loop-tp18163665p18163665.html Sent from the R

Oh, sorry; I changed signs in the model, fitting theta0 + theta1*exp(theta2*x) So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = +.055 as starting values. -- Bert On Sun, Aug 20, 2023 at 11:50?AM Paul Bernal <paulbernal07 at gmail.com> wrote: > Dear Bert, > > Thank you so much for your kind and valuable feedback. I...

...out it Yours Faithfully Dr. Antonello Romani Dipartimento di Medicina Sperimentale Sezione di Patologia Molecolare e Immunologia via Volturno 39 43100 Parma Italy #----------------------------------------------------------------------------------------------- find.mu.alfa <- function(theta, theta1, x, ell, which,...) { # # find theta=c(beta,mu,alfa) which maximize # Expected Log-Likelihood given by ell # # Set lower and upper bounds for mu (-Inf,Inf) # and alfa (0,Inf) # lower <- c(which, T, 0) * theta lower[c(which, T, 0) == T] <- - Inf upper <- c(which, T, T) * theta upp...

...0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class = "data.frame") I did the following to try to fit a nonlinear regression model: #First, Procedure to Find Starting (initial) Values For Theta1, Theta2, and Theta3 mymod2 <- y ~ theta1 - theta2*exp(-theta3*x) strt2 <- c(theta1 = 1, theta2 = 2, theta3 = 3) trysol2<-nlxb(formula=mymod2, data=mod14data2_random, start=strt2, trace=TRUE) trysol2 trysol2$coefficients[[3]] #Fitting nonlinear Regression Model Using Starting Values Fro...

...I obtained the same results for parameters estimates and standarderrors, by using: glmer(cens ~ treat + heart + offset(log(SURVT) + (1 | INST), data=liver, family=poisson) After that, the authors present the same model, but now bi = log(gi) where gi has the following gamma distribution: f(gi | theta1) = gi ^ (1/theta1 - 1) exp(-gi/theta1)/ GAMMA(1/theta1)(theta1^(1/theta1) They used a set of transformations proposed in the paper, and with the following rotine fitted the model achieving estimates for the same fixed parameters and for theta1: proc nlmixed data=liver; parms theta1 = 1 b0 = -2:8...

...of freedom Multiple R-squared: 0.717, Adjusted R-squared: 0.696 F-statistic: 33 on 1 and 13 DF, p-value: 6.76e-05 Kind regards, Paul El dom, 20 ago 2023 a las 14:07, Bert Gunter (<bgunter.4567 at gmail.com>) escribi?: > Oh, sorry; I changed signs in the model, fitting > theta0 + theta1*exp(theta2*x) > > So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = > +.055 as starting values. > > -- Bert > > > > > > On Sun, Aug 20, 2023 at 11:50?AM Paul Bernal <paulbernal07 at gmail.com> > wrote: > >> Dear Bert, >&...

...ed R-squared: 0.696 > F-statistic: 33 on 1 and 13 DF, p-value: 6.76e-05 > > Kind regards, > Paul > > El dom, 20 ago 2023 a las 14:07, Bert Gunter (<bgunter.4567 at gmail.com>) > escribi?: > >> Oh, sorry; I changed signs in the model, fitting >> theta0 + theta1*exp(theta2*x) >> >> So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 >> = +.055 as starting values. >> >> -- Bert >> >> >> >> >> >> On Sun, Aug 20, 2023 at 11:50?AM Paul Bernal <paulbernal07 at gmail.com&gt...

I am having the following error in my function function(theta,reqdIRR) { theta1<-theta[1] theta2<-theta[2] n<-length(reqdIRR) constant<- n*(theta1+theta2) sum1<-lapply(reqdIRR*exp(theta1),FUN = sum) sum2<-lapply(exp(theta2 - reqdIRR*exp(theta1)),FUN = sum) sum = sum1 + sum2 log.fcn = constant - as.numeric(sum) result = - log.fcn return(result) } *error : ne...

...to find the Hessian matrix for a complicated function from a certain kind of data but i keep getting this error Error in f1 - f2 : non-numeric argument to binary operator the data is given by U<-runif(n) Us<-sort(U) tau1<- 2 F1tau<- pgamma((tau1/theta1),shape,1) N1<-sum(Us<F1tau) X1<- Us[1:N1] Ti<- theta1*qgamma(Us[1:N1],shape,1) w=N1+1 V<- Us[w:r] N2<- length(V) V1<-theta2*qgamma(V,shape,1) Tj<-V1+tau1-(theta2/theta1)*tau1 c1<-mat...

Hi, I am trying to do parameter estimation with optim, but I can't get it to work quite right-- I have an equation X = Y where X is a gaussian, Y is a multinomial distribution, and I am trying to estimate the probabilities of Y( the mean and sd of X are known ), Theta1, Theta2, Theta3, and Theta4; I do not know how I can specify the constraint that Theta1 + Theta2 + Theta3 + Theta4 = 1 in optim. Is there another method/package that I should use for this? Also, I wonder if there's a more elegant way to code this equation in R; right now my function looks s...

I am trying to fit a nonlinear regression model to data. There are several predictor variables and 8 parameters. I will write the model as Y ~ Yhat(theta1,...,theta8) OK, I can do this using nls() - but "only just" as there are not as many observations as might be desired. Now the problem is that we have a factor "Site" and I want to include a corresponding error component. I tried something like (excuse the doctored R output...

HiI have a specific sample coming from a gamma(alpha,theta1) distribution and then divided into two parts first part follows a gamma(alpha,theta1) the second is gamma(alpha,theta2) then I would like to find the mle`s for theta1 and theta2 which I found. Now I would like to simulate those estimates 500 or 1000 times.I tried for loop but it did not work It wo...

I got starting values as follows: Noting that the minimum data value is .38, I fit the linear model log(y - .37) ~ x to get intercept = -1.8 and slope = -.055. So I used .37, exp(-1.8) and -.055 as the starting values for theta0, theta1, and theta2 in the nonlinear model. This converged without problems. Cheers, Bert On Sun, Aug 20, 2023 at 10:15?AM Paul Bernal <paulbernal07 at gmail.com> wrote: > Dear friends, > > This is the dataset I am currently working with: > >dput(mod14data2_random) > structure(l...

...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) } plot(theta1) Thanks alot :) -Mike -- View this message in context: http://r.789695.n4.nabble.com/Metropolis-...

...)) } #----------------------------------------------------------- function2<-function (x, theta) {P <- function1(x, theta) c <- P$a * x * exp(-theta[2]) d <- P$b * exp(x) q <- theta[1] / theta[3] res <- c + d + q; res} # Function to be optimized function3 <- function(theta1,theta2,theta3) { n <- length(data) -sum( function2(x = data[2:n], theta = c(theta1, theta2, theta3) ))} # 'data' is my input ts class object #-------------------------------------------------------------------------------------- Then I want to maximize function3 with respect to theta(s)...