[I don't know whether you cc'd this to r-help or not, I'm cc'ing this back]
Without more context it's hard to say very much, and you might be better off on the r-sig-ecol...@r-project.org list , or on CrossValidated (http://stats.stackexchange.com), rather than the general r-help list (this is rapidly becoming a statistical/methodological question -- "what method should I use?" rather than "how can I do this in R"?) As you indicate below, there are lots of statistical approaches for prediction in this case -- logistic regression, penalized regression (glmnet package), random forests, MARSS, ... figuring out which is best in your case isn't trivial ... Ben Bolker On 14-01-25 01:52 PM, Daniel Patón Domínguez wrote: > Dear all: > > In the book "Logistic Regression: An Overview Lawrence M. Healy > Eastern Michigan University, College of Technology" I read this > paragraph: > > "Logistic regression techniques resolve inconsistencies associated > with dichotomous dependent data and the assumptions of ordinary sum > of squares regression methods. The independent variables that are > used for outcome prediction may be DICHOTOMOUS, categorical or > continuous." > > I had used logistic regression in few occasions to describe presence > of species along gradients with continuous variables but never with > dichotomous. This caused my confusion.... > > The multivariate regression trees seem another possibility when you > have many dependent variables too dichotomous. In other cases I had > used multivariate analysis with vegan but the assumptions of > linearity (PCA) or modal (CA) distributions are not always observed. > In this cases Principal Curve Analysis (pcurve) or Non Metric > Multidimensional Scaling using different distances can be used. > However in this case I had more interested in prediction of events > and not in determining factors in data or the general structure of > data. This caused my inquire about this methodological question. > > Regards, > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
