similar to: optim not giving correct minima

Hi, 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)

Here's some code to make lissajous dance. I've attached a small sample GIF. Cheers, Rob Steele robsteele at yahoo dot com plot.lissajous = function(omega.x, omega.y, delta = 0, num.thetas = 200) { thetas = seq(0, 2 * pi, length = num.thetas) xs = sin(omega.x * thetas + delta) ys = cos(omega.y * thetas) plot(xs, ys, type = 'l', lwd = 3, ann = FALSE, axes = FALSE) }

Dear R users, How to find all single minima within each next part of analyzed vector (table) Select all minima (mass_value=min & mass_value<2) (many) in vector(table), BUT first put mask on table in order to select within one window mask (5 elements) only one local minimum, and next to search within the next time window mask the second minimum (only one local along second mask)

Hi there, I use the surf.gls() function to fit a variable measured over a surface. When I plot the predicted surface, there are local minima/maxima in almost every coordinate where data were measured, which seems aberrant. For instance: ?? x <- c(343,293,343,243,293,343,443,543,593,243,293,343,393,443,493,543,593,143,193,243,293,343,393,443,

I have data in the form of (x,y) pairs and would like to find local minima and maxima (typically the zeros of the 2nd derivative) of the y values. I looked at numericDeriv, but I don't have an "expression" per se. I looked at optim, also, but it looks like it will find only one "global" max or min. I can code up my own piecewise derivatives, but wondered if there is

Hi, I have a data-matrix: > CB                    Zeit                Low 2   2011-05-02 08:05:05 7596.0 3   2011-05-02 08:10:06 7593.5 4   2011-05-02 08:15:11 7594.5 5   2011-05-02 08:20:15 7597.5 6   2011-05-02 08:25:18 7595.0 7   2011-05-02 08:30:20 7593.5 8   2011-05-02 08:35:21 7593.0 9   2011-05-02 08:40:21 7593.0 10  2011-05-02 08:45:25 7599.0 11  2011-05-02 08:50:34 7596.0 12 

I am using numerical optimization to fit a 1 parameter model, in which the input parameter is bounded. I am currently using optimize(), however, the problem turns out to have local minima, and optimize does not always seem to find the global minimum. I could to write a wrapping function that tries multiple intervals or starting values, but I would prefer a package that has built-in methods to make

Dear all, I am trying to optimize a logistic function using optim, inside the following functions: #Estimating a and b from thetas and outcomes by ML IRT.estimate.abFromThetaX <- function(t, X, inits, lw=c(-Inf,-Inf), up=rep(Inf,2)){ optRes <- optim(inits, method="L-BFGS-B", fn=IRT.llZetaLambdaCorrNan, gr=IRT.gradZL, lower=lw, upper=up, t=t, X=X)

Hi all, I'm making an animation of a rotating persp plot of some data. It's easy, really: I just plot the persp in a loop over the theta parameter, saving each plot, and then chain them together with ImageMagick (as suggested on Paul Johnson's R-tips page). But... when you run the animation, because each graph is individually re-scaled, the image is not the same size in each

Hello, I am trying to get the power function to report the sample size rather than the power. My goal is to input a variety of values for theta and then for the power function to report the corresponding sample sizes. I haven't had much luck trying to create my own function, something along the lines of: f <- function (x) {

This is not so much a question as a contribution, but comments are welcome. Comments: 1) thank you very much to Paul Smith in the post https://stat.ethz.ch/pipermail/r-help/2008-March/157249.html This is intended to build on that example with something more complex than a 2x2 set of constraints 2) "L-BFGS-B" does not appear to work in optimConst Problem: let's

Dear R-help, I am trying to estimate a Cox model with nested effects basing on the minimization of the overall AIC; I have two frailties terms, both gamma distributed. There is a error message (theta2 argument misses) and I don?t understand why. I would like to know what I have wrong. Thank you very much for your time. fitM7 <- coxph(Surv(lifespan,censured) ~ south + frailty(id,

Dear Researchers, I wrote two function to fit a circle using noisy data. 1- the fitCircle() is derived from MATLAB code of * zhak Bucher* from the link http://www.mathworks.com/matlabcentral/fileexchange/5557-circle-fit/content/circfit.m 2- the CircleFitByPratt() from MATLAB code of *Nikolai Chernov *from the link

Background: I administer a cluster of RedHat EWS 3U4 Linux workstations at a university. I built R 2.1.0 from source: ./configure \ --prefix=/sscc/opt/R-2.1.0 \ --with-blas=no \ 2>&1 \ | tee NUInstall.configure R is now configured for i686-pc-linux-gnu Source directory: . Installation directory: /sscc/opt/R-2.1.0 C compiler:

Hi, here comes my problem, say I have the following functions (example case) #------------------------------------------------------------ function1 <- function (x, theta) {a <- theta[1] ( 1 - exp(-theta[2]) ) * theta[3] ) b <- x * theta[1] / theta[3]^2 return( list( a = a, b = b )) } #----------------------------------------------------------- function2<-function (x, theta) {P

m0<-epxression((4*theta1*theta2-theta3^2)/(2*x*theta3^2)-0.5*theta1*x) params<-all.vars(m0) this reads all the params from m0 so theta1,2 and 3 correct? params<-params[-which(params=="x")] checks which params are multiplied by x? np<-length(params) for(i in 1:6){ esp<-get(sprintf("m%d",i-1))

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized

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