similar to: Rao's quadratic entropy with fuzzy coded trait data

Dear R-users, I'd like to announce the release of my new package "ltm" (available from CRAN), for fitting Latent Trait Models (including the Rasch model) under the Item Response Theory approach. The latent trait model is the analogous of the factor analysis model for Bernoulli response data. "ltm" fits the linear one- and two-factor models but also allows for

Dear R-users, I'd like to announce the release of my new package "ltm" (available from CRAN), for fitting Latent Trait Models (including the Rasch model) under the Item Response Theory approach. The latent trait model is the analogous of the factor analysis model for Bernoulli response data. "ltm" fits the linear one- and two-factor models but also allows for

Hello, I got an error message saying Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : NA/NaN/Inf in foreign function call (arg 5) when I try to analysis a binary trait using glmnet(R) by running the following code library(glmnet) Xori <- read.table("c:\\SNP.txt", sep='\t'); Yori <- read.table("c:\\Trait.txt", sep=',');

Is there a package that will allow me to fit Brownian motion and Ornstein?Uhlenbeck models of evolution for discrete traits? I know that geiger and ouch have commands for fitting these models for continuous traits, but these aren't suitable for discrete trait evolution, correct? -- View this message in context:

Good afternoon! My question is more of a "is there a package for doing........?" an inference regarding the mean, median, regression estimates, etc. by using the information from dual frame surveys? (this methodology is based on the work of BANKIER 1986, SKINNER 1991, LOHR and RAO 2000...) If one has 2 independent studies which both independently measure a trait of a

The ade4 package (v. 1.2-1) has been updated on CRAN. New features include: - functions based on Rao's axiomatization of diversity measures : Rao's diversity coefficient and dissimilarity coefficient (divc and disc) - functions based on Excoffier et al. analysis of molecular variance with tests of the difference among the factors (amova). - functions introducing double principal

The ade4 package (v. 1.2-1) has been updated on CRAN. New features include: - functions based on Rao's axiomatization of diversity measures : Rao's diversity coefficient and dissimilarity coefficient (divc and disc) - functions based on Excoffier et al. analysis of molecular variance with tests of the difference among the factors (amova). - functions introducing double principal

Hi, I am looking for any procedure in R to fit "Latent variables models" in particular "Latent trait models (i.e. for binary data)". could anyone help me? Many thanks , Dr Abderrahim Oulhaj Oxford University Department of Pharmacology Mansfield Road Oxford OX1 3QT Tel: +44 1865 224098 Fax: +44 1865 224099 Email: abderrahim.oulhaj@pharmacology.oxford.ac.uk

I have just committed some code to the r-devel branch to implement the Rao efficient score test. This is asymptotically equivalent to the LRT, but there is some indication that it might have better properties in smaller samples since it is based more directly on the distribution of the sufficient sums under the null hypothesis (e.g., if you have a divergent fit to the model under the alternative,

How do I calculate the confidence interval for the value x given by the intersection of two quadratics (i.e. parabolas)? I fit two quadratics of the form: y = C1 + B1*x + A1*x^2 y = C2 + B2*x + A2*x^2 to two sets of points N1 and N2. I test for whether they intersect, if they do then I calculate the roots of: 0 = (C1 - C2) + (B1 - B2)*x + (A1 - A2)*x^2 to determine where they intersect

Hi, I have a nested unbalanced data set of four correlated variables. When I do univariate analyses, my factor of interest is significant or marginally significant with all of the variables. Small effect size but always in the same direction. If I do a MANOVA instead (because the variables are not independent!) then my factor is far from being significant. How does that come about? I have

Dear all, I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes. 1) There is a new version of mvSLOUCH available. The most important change is that the

Dear all, I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes. 1) There is a new version of mvSLOUCH available. The most important change is that the

-----Original Message----- Message: 6 Date: Mon, 20 Jan 2003 01:11:24 +0100 From: Martin Michlmayr <tbm at cyrius.com> To: r-help at stat.math.ethz.ch Subject: [R] quadratic trends and changes in slopes I'd like to use linear and quadratic trend analysis in order to find out a change in slope. Basically, I need to solve a similar problem as discussed in

Hi, Does anybody have experience to solve an quadratic programming problem with quadratic constraints in R? It seems that the package "quadprog" only handles the quadratic programming with linear constraint. My probelm is to maximze x^T\Sigma_{xy} y, subject to x^Tx=1, y^T\Sigma_{yy} y=1, and sum(y)<t, or sum(y)=t, where x and y are the variable, and the Sigma's and t are

HI All, I am unable to solve a optimization Problem Please Help Me out of this to solve. The Optimization problem is as follows :- My objective function is linear and one of the constraint is quadratic. Min z = 5 * X1 + 9* X2 + 7.15 *X3 + 2 * X4 subject to X1 + X2 + X3 +X4 = 9 X1 + X4 < = 6.55 X3(X3 - 3.5) >=0 X1,X2,X3,X4 >=0 Now the problem is how to solve this kind of

Hi, I need to maximize a quadratic function under constraints in R. For minimization I used solve.QP but for maximization it is not useful since the matrix D of the quadratic function should be positive definite hence I cannot simply change the sign. any suggestion ? thanks -- View this message in context:

Hi Bert, I won't post any more messages on this thread as problem has shifted from Optimization in R to Graph Algorithms. Rest fine Khris. On Aug 2, 2012, at 9:13 PM, Bert Gunter [via R] wrote: > This discussion needs to be taken off (this) list, as it appears to > have nothing to do with R. > > -- Bert > > On Thu, Aug 2, 2012 at 2:27 AM, khris <[hidden email]>

I was playing around with a simple example using solve.qp ( function is in the quadprog package ) and the code is below. ( I'm not even sure there if there is a reasonable solution because I made the problem up ). But, when I try to use solve.QP to solve it, I get the error that D in the quadratic function is not positive definite. This is because Dmat is zero because I don't have a

Hi listers, Does anybody knows if the function qda for quadratic discriminant analysis provides the coefficients of quadratic discriminants... Well, I find out that for the linear discriminant analysis lda, the fonction provides the coefficients... Thanks in advance, Marcio -- View this message in context: http://www.nabble.com/Quadratic-Discriminant-Analysis-%28qda%29-tp22747647p22747647.html