similar to: Mallows' distance or Earth Mover's distance in R?

So I recognize that: 1. many people hate forward stepwise regression (i've read the archives)--but I need it 2. step() or stepAIC are two ways to get a stepwise regression in R But here's the thing: I can't seem to figure out how to specify that I want the criteria to be Mallow's Cp (and then to subsequently tell me what the Cp stat is). I know it has something to do with

I wanted to try out package distrMod, so I did > install.packages('distrMod') > library(distrMod) and played around, saved and quit. Now whenever I start up in this directory, I get distr and lots of other stuff loaded and lots of messages. How do I keep it from automatically loading, other than starting over in another directory? I read ?Startup, but I couldn't suss out

Hello R users, I have three questions and I would be grateful if someone could give me an answer to each of these. 1) I have constracted a function that returns an output, which runs in a while( condition ){ run function } loop. I would like to know if there is a way to get the outputs in different windows, every time the function runs, so as to compare easier the results. 2) In my

Dear all I am supposed to use Mallow's Cp creterion to select a model which require a "leaps" package. the version right now I am using is R 1.7.1(os:windows), the "leaps" package is not included. please let me know how and where can I get this package and add it to the current version, any caution on adding this package is highly appreciated. thank you best

As some of you will be aware, TeXLive 2009 was released last month having blocked updates on earlier versions since May. This has lead to a flood of updates of LaTeX packages, as a result of which the PDF manuals of R 2.10.0 and earlier will no longer build, for two separate reasons. For MiKTeX users: at least version 2.8 (the current one) has the same updates (a week or so later) and has

I am hoping to get some advise on the following: I am looking for an automatic variable selection procedure to reduce the number of potential predictor variables (~ 50) in a multiple regression model. I would be interested to use the forward stepwise regression using the partial F test. I have looked into possible R-functions but could not find this particular approach. There is a function

Hello, everybody, I hope somebody could help me with a dist() function. I have a data frame of size 2*4087 (col*row), where col corresponds to the treatment and rows are species, values are Hellinger distances, I should reconstruct a distance matrix with a dist() function. I know that "euclidean" method should be used. When I type: dist(dframe,"euclidean") it gives me a

Dear List members I am using the regsubsets function to select a few predictor variables using Mallow's Cp: > sel.proc.regsub.full <- regsubsets(CO2 ~ v + log(v) + v.max + sd.v + tad + no.stops.km + av.stop.T + a + sd.a + a.max + d + sd.d + d.max + RPA + P + perc.stop.T + perc.a.T + perc.d.T + RPS + RPSS + sd.P.acc + P.dec + da.acc.1 + RMSACC + RDI + RPSI + P.acc + cov.v + cov.a +

Hi, while working with decision trees and unbalanced data, I came across the use of the Hellinger distance as an alternative to information gain [1,2], when dealing with skewed data. Does anybody know of R implementations of this approach to decision trees? Thanks, [1] http://www.cse.nd.edu/Reports/2008/TR-2008-06.pdf [2] http://csmr.ca.sandia.gov/~wpk/slides/wdmda-sem.pdf -- Rajarshi Guha NIH

Dear R users and Dear authors of the distr package and sequels I am trying to use the (very nice) package distrMod as I want to implement maximum likelihood (ML) fit of some univariate data for which I have derived a theoretical continuous density (pdf). As it is a parametric density, I guess that I should implement myself a new distribution of class AbscontDistributions (as stated in the pdf

I'm trying to perform a RDA analysis in the vegan package using the "varpart" function. I have a matrix of community structure data in different sites (rows), which I want to explain using 3 matrices of environmental data. The 3 matrices are: water quality parameters; local land use variables; total land use variables. In each matrix, the number of the rows is the same (the

Hello, Newbie here, be gentle ;) I have a reference book that discusses regression model selection using several methods - what they call 'Forward Model Selection' i.e. add one variable at a time and examining R, R^2, Mallow's C-p value, etc., 'Backward Model Selection' i.e. starting out with all the variables included and then remove them one at a time, and examining for

Hi In trying to fit a linear model , I use the leaps() function to determine wich predictors I should include in my model. I would like to plot the Mallow's Cp criteria against p with the indexes of selected model variates as points labels Is there already such a function? (I could not find it) Thanks Anne [[alternative HTML version deleted]]

Hi, Is there any package for logistic model selection using BIC and Mallow's Cp statistic? If not, then kindly suggest me some ways to deal with these problems. Thanks. -- View this message in context: http://www.nabble.com/Stepwise-logistic-model-selection-using-Cp-and-BIC-criteria-tf4464430.html#a12729613 Sent from the R help mailing list archive at Nabble.com.

Hello I am trying to use all subsets regression on a test dataset consisting of 11 trails and 46 potential predictor variables. I would like to use Mallow's Cp as a selection criterion. The leaps function would provide the required output but does not work with this many variables (see below). The alternative function regsubsets should be used, but I am not able to define the function in

Hii rstudio members I am learning rstudio, For my manuscript I am trying to plot CCA using species and environmental data. But I am getting error like Error in cca.default(sptrans, envtrans) : all row sums must be >0 in the community data matrix *My code is like * library(vegan) library(ggplot2) library(dplyr) rassspec<-read.csv("C:/Users/hp/Desktop/R_data/rassspec.csv",

I am not familiar with the vegan package, so I am just making a guess here. If 'na.action=na.omit' is part of the call to varpart, try removing it from the function call and moving it above as follows: options(na.action="na.omit") RDA_Ger <- varpart(comm, x1, x2, x3, transfo="hellinger", scale = FALSE) Maybe that will help. Regards, Eric On Sat, Sep 16, 2017 at

Dear all, I'm performing RDA on plant presence/absence data, constrained by geographical locations. I'd like to constrain the RDA by the "extended matrix of geographical coordinates" -ie the matrix of geographical coordinates completed by adding all terms of a cubic trend surface regression- . This is the command I use (package vegan): >rda(Helling ~

I'm in the process of converting some S3 methods to S4 methods. I have this function : setGeneric("enrichmentCalc", function(rs, organism, seqLen, ...){standardGeneric("enrichmentCalc")}) setMethod("enrichmentCalc", c("GenomeDataList", "BSgenome"), function(rs, organism, seqLen, ...) { ... ... ... })

Is there any automatic mechanism for extracting a likelihood or test statistic distribution (PDF or CDF) from an object of class "htest" or from another object of a general class encoding a hypothesis test result? I would like to have a function that takes "x", an object of class "htest", as its only argument and that returns the likelihood or test statistic