search for: polychotom

Dear R users, Does anyone know if it is possible to use multinom to do a polychotomous fit using one categorical and one numeric variable as response. The doc. for multinom states that for formula , response can be K>2 classes. Is this 2 and more, or as I have understood it only greater than 2. I have tried fitting my data, but have only encountered error messages. On another...

I've seen references to "polymars", an R implementation of Friedman's MARS algorithm. Can anyone tell me where I might be able to find this (doesn't seem to be in the contributed packages. Thanks, David -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

...ry Data Analysis gee Generalized Estimating Equation models integrate numerical integration leaps Regression subset selection locfit Local Regression, Likelihood and Density Estimtion. mva Classical Multivariate Analysis polymars (polychotomous) regression based on Multivariate Adaptive Regression Splines polynom A collection of functions to implement a class for univariate polynomial manipulations spatial functions for kriging and point pattern analysis splines Regression Spline Fu...

...ry Data Analysis gee Generalized Estimating Equation models integrate numerical integration leaps Regression subset selection locfit Local Regression, Likelihood and Density Estimtion. mva Classical Multivariate Analysis polymars (polychotomous) regression based on Multivariate Adaptive Regression Splines polynom A collection of functions to implement a class for univariate polynomial manipulations spatial functions for kriging and point pattern analysis splines Regression Spline Fu...

...set, but do not know how. I've only thought of a few possibilities and write to seek advice and guidance on them or deepening or expanding my search. On smaller data sets, I have successfully loaded the data and issued commands such as: length(levels(factor(data$response))) [1] 6 # implies polychotomy library(nnet) result <- multinom(data$response ~ 1 + data$var1 + data$var2 + ...) # (I am interested in at most ten # parameters; usually less than six) For a 60-MB comma-separated-values text-format data file (with a few hundred thousand records), object.size(data) returns roughly 86 MB. N...

...n be very offputting, and could lead the rabbit to return to familiar SPSS territory. Finally, friendlier error messages would also help. It took me 3 days, and opening every function I could, to work out that '...cannot find function xxx.data.frame...' meant that MICE was unable to make a polychotomous logistic imputation model converge for the variable immediately preceding it. I am now off to the help files and FAQs to find out how to change graph parameters, as the plot.mids function in MICE a) doesn't allow one to select a subset of variables, and b) tells me that the graph it wants...