search for: secchi

...c regression model. for example: first I run the model, "name<-glm(dep~env1+env2..., family= binomial, data=new)" after that, I did stepwise for name name.step<-step(name, direction="backward") here, I still got those variables which were not significant, for example: secchi was not significant (see below example), but still it was in the model. how can I remove those variables which are not significant in forward/backward stepwise?. another question, when I wrote direction="backward", I got the results same as in the process of "forward". It is r...

...on to have a "jackknifed corrected var/cov estimate" (as described in MacKinnon and White 1985) in a standard OLS regression? 2. Does R possess a LAD (Least Absolute Deviation) regression function? Any help? Thanks -- ======================================================== Angelo Secchi PGP Key ID:EA280337

...oncentration measures (Gini, Herfindal, ...) and I was wondering if there's around also a function to calculate standard error on these measures. If not, is anybody aware of where I can find a reference on this point? Thanks. -- ======================================================== Angelo Secchi PGP Key ID:EA280337

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2 Sample 3 Sample 4 Sample 5...

...4203.1415 ind2 1.0370 0.0000 668735.7195 taht is no std error I've already tryied puuting a "digits = 6" with no success. What is the proper way to ask R to provide more digits in the std error? Thanks -- ======================================================== Angelo Secchi PGP Key ID:EA280337

AFAIK most model fitting techniques will only deal with additive errors, not multiplicative ones. You might want to try fitting: log(y-x) = a*x + e which is linear. Andy > From: Angelo Secchi > > Hi, > is there a way in R to fit a non linear model like > > y=x+exp(a*x)*eps > > where a is the parameter and eps is the error term? > Thanks > Angelo > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > ht...

...he function in an IF statement like if (Q^3>R^2) results2 <- case1() else print('ciccio') I get Error in eval(expr, envir, enclos) : Object "theta" not found I do not understand why, any help? Thanks -- ======================================================== Angelo Secchi PGP Key ID:EA280337

Hi, I'm exploring the ismev package and in particular the pp.fit function. Documentation says that this function performs Maximum-likelihood fitting for the point process model, including generalized linear modelling of each parameter. Actually I'm afraid not to understand what it means with "Point process model". Any suggestion on possible references for further infos? thanks

Hi, How can I define a new psi function in the rlm comand? In particular I would like to implement the case for \rho(u)=0.5*(u^2) and \psi(u)=u in order to assume normally distributed errors. Any help? Thanks -- ======================================================== Angelo Secchi PGP Key ID:EA280337

Hello, i have a xls file. I will read it in r, what library-command i use for this?? any ideas?? Thanks Michele [[alternative HTML version deleted]]

...c regression model. for example: first I run the model, "name<-glm(dep~env1+env2..., family= binomial, data=new)" after that, I did stepwise for name name.step<-step(name, direction="backward") here, I still got those variables which were not significant, for example: secchi was not significant (see below example), but still it was in the model. how can I remove those variables which are not significant in forward/backward stepwise?. another question, when I wrote direction="backward", I got the results same as in the process of "forward". It is r...

Hi, I am running an ordered logistic regression model with an interaction, using the polr command. I am trying to find a way to calculate the marginal effects and their significance in R. Does anybody have any suggestion? Thank you! Enrico [[alternative HTML version deleted]]