search for: heterocedasticity

...e been searching examples for this without any luck: #Assume x<-1:10  #x ranges from 1 to 10. y<-x*runif(10)+ 1.5*x  #y is a linear function of x with some error. Add uniform error that is scaled to be larger as x values also become larger #error is proportional to x size, this should cause heterocedasticity. #I know there are many methods to deal with heterocedasticity, but in my specific case, I want to use percent regression to minimize the mean absolute  #percentual error as opposed to regular regression that deals with the square of the errors. #Question, how to fit a linear model to minimize t...

Peter You question is difficult to answer without more information about the distribution of your residuals. Different residual patterns call for different transformations to stabilize the variance. One very common form of heterocedasticity is increasing variance with increasing values of an independent predictor, i.e. the variance of the residuals of y=x increase as x increases. In this case a log transformation of some, or all, of the independent variables of the helps. Please also note the comment by Bert Gunter (included below) in...

...ocedasticity in order to be able to use ANOVA. Unfortunately, no transformation that I have used transforms my data into data with homocedasticity. The histogram of variances is at http://phhs80.googlepages.com/hist1.png Is someone able to suggest to me a transformation to overcome the problem of heterocedasticity? Thanks in advance, Paul

Dear R users: I have some difficulties analizing data with mixed effects NLME and the last version of R. More concretely, I have a repeated measures design with a single group and 2 experimental factors (say A and B) and my interest is to compare additive and nonadditive models. suj rv A B 1 s1 4 a1 b1 2 s1 5 a1 b2 3 s1 7 a1 b3 4 s1 1 a2