search for: varaince

Dear, I would like know the way to calculate the variance explained of a regression tree. I use the function "ctree" from library "party" many thanks [[alternative HTML version deleted]]

Hello, for my meta-analysis I try to test if two varainces are equal without using the raw scores. I have is the SD's, N's and the Means. I want to test the variances from dependent and independend samples. I assume I can use the var.test procedure for the independent samples, but what about the dependent samples ? Has anyone an idea how to re...

...am searching for an R-Package that does an exentsion of the Mantel-Haenszel test for ordinal data as described in Liu and Agresti (1996) "A Mantel-Haenszel type inference for cummulative odds ratios". in Biometrics. I see packages such as Epi that perform it for binary data and derives a varaince for it using the Robbins and Breslow variance method. As well as another pacakge that derives it for nominal variables but does not provide a variance or confidence limit. Does a package exist that does this? I have searched the list archives and can't seem to see such a package but I could b...

...y lm. This would explain for the increase of the std error (and hence the size of the confidence interval) from m0.lm to m1.lme. - Is its possible to use lme without a random term, or alternatively with a trivial random term? - Is the overall approach: use of blocking factors to reduce the residual varaince, and hence to decrease the width of the confidence intervals valid? Using lmer, alternatively to the calculation of CIs, credible intervals can be calculated: > m1.sample = mcmcsamp( m1.lmer, n =10000 ) > m1.ci = apply( m1.sample, 2, function(x)quantile(x, prob=c(.025,0.975))) > m1.ci[,...

...pt) : (Intercept) 0.4355866 target : numeric(0) Within : methodMACCS methodXXX.pg.trained methodXXX.rpg.trained 0.1136190 0.1533571 0.1088655 I have the following questions: - Is the overall approach: use of blocking factors to reduce the residual varaince, and hence to decrease the width of the confidence intervals valid? - Why does the call of summary.lm fail for m1.aov and m2.aov? - Why are the fitted parameters different for m0.aov compared to m1.aov and m2.aov? Please note that I made similar attempts using lme and lmer. I failed in both cases....

Greets, I'm trying to use nlminb() to estimate the parameters of a bivariate normal sample and during one of the iterations it passes a parameter vector to the likelihood function resulting in an invalid covariance matrix that causes dmvnorm() to throw an error. Thus, it seems I need to somehow communicate to nlminb() that the final three parameters in my parameter vector are used to