[EMAIL PROTECTED] wrote: > Given a data set and a set of predictors and a response in the data, > we would like to find a model that fits the data set best. > Suppose that we do not know what kind of model (linear, polynomial > regression,... ) might be good, we are wondering if there is R-package(s) > can auctomatically do this. > Otherwise, can you direct me, or point out reference(s), > basic steps to do this. Thanks. > > -james
The best-fitting model for any data is a model with a lot of parameters, so maybe the best fitting model for any data is a model with an infinite number of parameters. However, any model with more parameters than data will have a negative number of degrees of freedom, and you do not want that. The best-fitting model for any data subject to the constraint that the number of degrees of freedom is non-negative, is the data itself, with zero degrees of freedom. The AIC tells you this too. The AIC for the model formed by the data itsel is 2n, whereas the AIC for any model with negative degrees of freedom is > 2n. But I guess you want to make inference from sample to population. If that is indeed the case, then you should consider changing your focus from finding "a model that fits the data set best" to a model that best summarizes the information contained in your sample about the population the sample comes from. To do that, start by defining the nature of your response variable. What is the nature of the natural process generating this response variable? Is it continuous or discrete? Is it univariate or multivariate? Can it take negative and positive values? Can it take values of zero? After you have clarified the probabilistic model for the response variable, then you can start thinking about the mathematical relation between the response variable and the predictors. Is it linear or nonlinear? Are the predictors categorical or continuous? Read the posting guide, formulate a clear question, and maybe you will be given more specific help. Rubén ______________________________________________ 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.