similar to: 'all subsets' fitting algorithm for Bayesian approach

Hi all A couple of questions about string processing from someone who has only scratched the surface so far. 1) I am wanting to send some strings into a function to allow flexibility inside. My first idea has been e.g. auto_io <- function( var_string, factors ) { # e.g. var_string sent as "test_file.txt" factors sent as "x1 + x2 + x3" # input data_name <- get(

Hi R people I am using regsubsets() to fit large numbers of models and collect summary statistics in order to perform a Bayesian analysis of multi-way ANOVA with specific prior information. In general the variables have differing numbers of levels >=2. This works well but with variable of more than 2 levels there are naturally some arbitrary decisions about which treatment contrasts to

OK, my last question didn't get any replies so I am going to try and ask a different way. When I generate contrasts with contr.sum() for a 3 level categorical variable I get the 2 orthogonal contrasts: > contr.sum( c(1,2,3) ) [,1] [,2] 1 1 0 2 0 1 3 -1 -1 This provides the contrasts <1-3> and <2-3> as expected. But I also want it to create <1-2> (i.e.

Dear List, I have the code below, where I am using the constrained optimisation package, 'constrOptim.nl' to find the values of two values, b0 and b1. I have no problems when I enter further variable information DIRECTLY into the functions, fn, and heq. In this instance I require fn to have -0.0075 appended to it, and in the case of heq, h[1] has -0.2. library(alabama)

I understand this isn't a r specific question. I'm switching departments to work with the analytics team at my company as a "service" side manager to better incorporate the analytics process into product design / production. We're an online gaming company. As I'm going through tools like R, rapidminer, tableau, I was also thinking that I should get some formal training

Good afternoon list, I have the following character strings; one with spaces between the maths operators and variable names, and one without said spaces. form<-c('~ Sentence + LEGAL + Intro + Intro / Intro1 + Intro * LEGAL + benefit + benefit / benefit1 + product + action * mean + CTA + help + mean * product')

Good morning R list, My apologies if this has *already* answered elsewhere, but I have not found the answer that I am looking for. I have a character string, i.e. form<-c('~ A + B + C + C / D + E + E / F + G + H + I + J + K + L * M') Now, my aim is to find the position of all those instances of '*' and to remove said '*'. However, I would also like to remove the

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

Dear R-users, I would like to announce the release of the new package JMbayes available from CRAN (http://CRAN.R-project.org/package=JMbayes). This package fits shared parameter models for the joint modeling of normal longitudinal responses and event times under a Bayesian approach using JAGS, WinBUGS or OpenBUGS. The package has a single model-fitting function called jointModelBayes(),

Dear R users, I have a problem. I would like to solve the following: I have pL = 1/(1+e^(-b0+b1)) pM = 1/(1+e^(-b0)) pH = 1/(1+e^(-b0-b1)) My target function is TF= mean(pL,pM,pH) which must equal 0.5% My non-linear constraint is nl.Const = 1-(pM/pH), which must equal 20%, and would like the values of both b0 and b1 where these conditions are met. I have searched widely for an answer,

Dear List, I am using constrOptim to solve the following fr1 <- function(x) { b0 <- x[1] b1 <- x[2] ((1/(1+exp(-b0+b1))+(1/(1+exp(-b0)))+(1/(1+exp(-b0-b1)))))/3 } As you can see, my objective function is ((1/(1+exp(-b0+b1))+(1/(1+exp(-b0)))+(1/(1+exp(-b0-b1)))))/3 and I would like to solve for both b0 and b1. If I were to use optim then I would derive the gradient of the

Hi, let's say I have a simple ANOVA model with 2 factors A (level A1 and A2) and B (level B1 and B2) and their interaction: aov(y~A*B, data=dat) It turns out that the interaction term is not significant (e.g. P value = 0.2), but if I used glht() to compare A1 vs. A2 within each level of B, I found that the comparison is not significant when B=B1, but is very significant (P<0.01) when

Hi, I have a data.frame that has a categorical variable, for which I would like to look at the distribution of levels of this variable, based on a grouping of two other variables. As an example: x <- data.frame(obs=sample(c('low', 'high'),100, replace=TRUE), grp1=sample(1:10, 100, replace=TRUE), grp2=runif(100)) cut.grp1 <- cut(x$grp1, 3) cut.grp2 <- cut(x$grp2, 3)

Dear all, I'm modeling growth curve of some ecosystems with respect to their rainfall-productivity relationship using a simple linear regression (ANPP(t)=a+b*Rain(t)) and a modified version of the Brody Model ANPP(t)=a*(1-exp(-b*rain(t))) I would like to know why the "best model" is function of the criteria that I use (maximizing the fit using R2 or testing the Null hypothesis with

Dear R developers, these days I'm working on some R code for fitting completely generic Bayesian Hierarchical Models in R, a la OpenBUGS and JAGS. A key feature of OpenBUGS and JAGS is that they automatically build an appropriate MCMC sampler from a generic model, specified as a directed acyclic graph (DAG). The spirit of my (would-be) implementation is instead more focused on experimentation

Looking for help with a project for the US Navy, requires knowledge of Bayesian Statistics, Bayesian Networks and Survival Analysis. Please respond with CV. Thanks. -- David Katz www.davidkatzconsulting.com [[alternative HTML version deleted]]

Hi, I am neither a statistician nor a user of R. I am a programmer trying to provide my users (both statisticians and R users) data in a format that works best for them. What is a data frame? Is source data easier to work with in this format or a csv file? Or yet another format? Thanks for your time. Bruce [[alternative HTML version deleted]]

I am not a pure Statistics background and therefore please forgive me if this question (which is not R related either) is too trivial. In many Statistics literature I find following statement: "restrictions in different coefficients matrices have to be imposed to ensure uniqueness of the parametrization". Can somebody tell me what is the meaning of Uniqueness in the parametrization?

Any advice on which package I can use for calculating effect sizes for two dependent samples? compute.es seems only to consider independent samples. Thanks in advance Steve Powell [[alternative HTML version deleted]]

Hi, everybody, I just want to pass arguments to a function as below: range <- c(0.1, 0.5) runif(1, range) But it doesn?t work. Does anyone have any suggestions to offer? Thanks. Lisa -- View this message in context: http://r.789695.n4.nabble.com/Arguments-of-a-function-tp3387643p3387643.html Sent from the R help mailing list archive at Nabble.com.