similar to: Maximum likelihood estimation of a truncated regression model

Dear R helpers, >From the lrm( ) model used for binary logistic regression, we used the L.R. model value (or the G2 value, likelihood-ratio chi-squared statistic) to evaluate the goodness-of-fit of the models. The model with the lowest G2 value consequently, has the best performance and the highest accuracy. However our model includes rsc() functions to account for non-linearity. We

Hello, I am struggling for some time now to estimate AR(1) process for commodity price time series. I did it in STATA but cannot get a result in R. The equation I want to estimate is: p(t)=a+b*p(t-1)+error Using STATA I get 0.92 for a, and 0.73 for b. Code that I use in R is: p<-matrix(data$p) # price at time t lp<-cbind(1,data$lp) # price at time t-1

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

Dear all, I need to simulate data which fit to a double poisson time series model with certain parameters. Then, check whether the estimated parameter close to the true parameter by using maximum likelihood estimation. Simulation: set.seed(10) library("rmutil") a0 = 1.5; a1 = 0.4; b1 = 0.3; g1= 0.7 ; n=100 #a0, a1 and b1 are parameter where n is size. nu = h =

Hello, I am trying to estimate parameters of mean reverting process with jumps given by: dp=k(mu-p)dt+sigma*dz+Jdq where dp represents change in log of price, k is reversion factor, mu is long run level of price, sigma is standard deviation, and dq equals one with probability lambda if jump occurs and 1-lambda otherwise. J is jump size with mean muj and standard deviation delta. Therefore, when

Hi: I'm trying to estimate a latent variable model in mnl discrete choice framework using R. I need to do first a uni dimensional integral within each observation (row) in the database and then sum over observations. I'm stacked in the point shown below. Apparently I have a dimensionality problem in the definition of the integral. Maybe it does not identify that what I need is only one

Hi everyone, I am looking to do some manual maximum likelihood estimation in R. I have done a lot of work in Stata and so I have been using output comparisons to get a handle on what is happening. I estimated a simple linear model in R with lm() and also my own maximum likelihood program. I then compared the output with Stata. Two things jumped out at me. Firstly, in Stata my coefficient

Dear R-helper, I am trying to do maximum likelihood estimation in R. I use the "optim" function. Since I have no prior information on the true values of the parameters, I just randomly select different sets of starting values to feed into the program. Each time, I get the following error message: Error in optim(theta0, lf, method = "BFGS", hessian = T, Y = Y, X = X, :

R-help, I'm trying to estimate some parameters using the Maximum Likehood method. The model describes fish growth using a sigmoidal-type of curve: fn_w <- function(params) { Winf <- params[1] k <- params[2] t0 <- params[3] b <- params[4] sigma <- params[5] what <- Winf * (1-exp(- k *(tt - t0)))^b

Hello everyone... We were trying to implement the Newton-Raphson method in R, and estimate the parameters a and b, of a function, F, however we can't seem to implement this the right way. Hope you can show me the right way to do this. I think what we want R to do is to read the data from the website and then peform maxNR on the function, F. Btw the version of R being used is "RGui for

Greetings, I use maxNR function under maxLik package to find the REML estimates of the parameters of variance components in heteroskedastic linear regression models. I assume that in the model there is additive/multiplicative/mixed heteroskedasticity and I need estimate the respective parameters of additive/multiplicative/mixed variance components. For my research purposes I make a

Hi, I have trouble getting MOH to work after an upgrade from asterisk 1.4 to 1.6.1.4. The call goes on hold, MOH is started, and then stops right away. Here are the files both of type .raw: Tsunami*CLI> moh show files Class: default File: /etc/asterisk/musiconhold/Fr?d?ric Chopin - Polonaises Op. 40-2 File: /etc/asterisk/musiconhold/Fr?d?ric Chopin - Polonaises Op. 40-1 These files

Hi, I'm having trouble getting Dial to exit when the caller hangs up in Asterisk 1.4.21.2. I use a POTS line to call into the DiD given to me by VOIP service provider. When the call comes in, I have the VOIP provider send it to another POTS line. All this works fine however when the caller (me) hangs up, the Dial command does not exit. The callee stays connected (and my billing

Hi R-users, Recently, I use maxNR function to find maximizer. I have error appears as follows Error in maxNRCompute(fn = fn, grad = grad, hess = hess, start = start, : NA in the initial gradient My code is mu=2 s=1 n=300 library(maxLik) set.seed(1004) x<-rcauchy(n,mu,s) loglik<-function(mu) { log(prod(dcauchy(x,mu,s))) } maxNR(loglik,start=median(x))$estimate Does anyone know how

Dear R-list I have been trying to make survreg fit a normal regression model with left truncated data, but unfortunately I am not able to figure out how to do it. The following survreg-call seems to work just fine when the observations are right censored: library(survival) n<-100000 #censored observations x<-rnorm(n) y<-rnorm(n,mean=x) d<-data.frame(x,y) d$ym<-pmin(y,0.5)

Hi all, I need some help, advice or whatever you can explain to me because I haven''t got a clear idea about how to do the following assembly, and I''d be very grateful if I got some help from an expert like you. I''m trying to build a system which represents the following: I''ve got a hosts unit (host1, host 2, ...) which have IP in the network 192

I have to register asterisk/sip with a sipproxy that does not support authentication, I do not know how to tell Asterisk not to send authentication request? # sip.conf [general] insecure=very permit=207.148.115.10/255.255.255.0 [myproxy] type=friend host=217.118.115.10 context=from-sip # Logging: <--- Reliably Transmitting (NAT) to 207.148.115.10:5060 ---> SIP/2.0 407 Proxy

I have a question about running an optimization function on an existing LOESS function defined in R. I have a very large dataset (1 million observations) and have run a LOESS regression. Now, I want to run a Newton-Raphson optimization to determine the point at which the slope change is the greatest. I am relatively new to R and have tried several permutations of the maxNR and nlm functions with

Hi, I have generated a profile likelihood for a parameter (x) and am trying to get 95% confidence limits by calculating the two points where the log likelihood (LogL) is 2 units less than the maximum LogL. I would like to do this by linear interpolation and so I have been trying to use the function approxfun which allows me to get a function to calculate LogL for any value of x within