similar to: How to get confidence interval and coefficient in Logic Regression

I want to get some "simple" logic regression examples to work before exploring a hard problem. I can get results, but I'm having some problems using "cat" to save the logic regression equation to a disk file. Consider this: # Simple Logic Regression Example # efg, 23 Feb 2005 library(LogicReg) # Create simulated data with known logic equation: # "noise"

Hi there: recently i try to use LogicReg package for a tree model(logistics fit ) . i list my code and error below: > dim(model.dat) [1] 48000 745 > fit1 <- logreg(resp = model.dat[,745], bin=model.dat[, 9:700], type = 3, select = 3, ntrees = c(1,2), nleaves=c(1,7), ) Insufficient declaration LGCn1MAX in logreg() is 20000 LGCn1MAX should be at least 48000 Please fix and

Hello, I would appreciate *any* ideas on this problem. I'm the maintainer of a package ("subselect"), which on CRAN's Daily Package Checks is OK on all flavours of R, except r-devel Linux x86_64, where there is a "memory not mapped" segfault with the very first example that is tried out (output below). Additionally, a user with an AMD64 machine has just reported a

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

Dear list, I tried to apply the logistic regression to different response variables from a dataframe and would like to store the results using the function logistic.display from the "epicalc" package in a list, but got an error message "Error in eval(expr, envir, enclos) : y values must be 0 <= y <= 1". All the response variables have value of 0 or 1. It worked

Version 0.9-99 of package "subselect" is now on CRAN. The subselect package has functions that search for k-variable subsets of a p-variable (p>k) data set that are optimal under some criterion. Search algorithms include a full search algorithm "leaps", based on Furnival and Wilson's leaps and bounds algorithm, and three random search algorithms: a genetic algorithm

Version 0.9-99 of package "subselect" is now on CRAN. The subselect package has functions that search for k-variable subsets of a p-variable (p>k) data set that are optimal under some criterion. Search algorithms include a full search algorithm "leaps", based on Furnival and Wilson's leaps and bounds algorithm, and three random search algorithms: a genetic algorithm

I really like these Trellis graphics but how do I get this code to skip the missing? logreg<-read.csv("logreg.csv", header=TRUE, sep=",", na.string=" ") attach(logreg) bwplot(yesno~bc_pcb_tot |varlist, data=logreg, main="Box Cox PCB transformation", auto.key=TRUE, fontfamily = "HersheySans" ) Dean Sonneborn M.S. Public Health Sciences *

Trying to install subselect v0.8 on Redhat 7.3 and R 1.8.1 fails (below). Any help is greatly appreciated. Xiao-Jun * Installing *source* package 'subselect' ... ** libs f2c < anneal.f > anneal.c anneal: Error on line 263: Declaration error for fica: adjustable dimension on non-argument Error on line 263: Declaration error for valp: adjustable dimension on non-argument Error

I have been trying to run a logistic regression using a number of studies. Below is the syntax, error message & data. Any advice regarding what I am doing wrong or solutions are appreciated, regards Bob Green > logreg <- read.csv("c:\\logregtest.csv",header=T) > attach(logreg) > names(logreg) [1] "medyear" "where" "who"

R 2.7.2 PPC Mac OS X 10.4.11 library mice 1.13.1 I try to use mice for multivariate data imputation. My variables are numeric, factors, count data, ordered factors. First I created a vector for the methods to use with each variable ImpMethMice<-c(rep("logreg", 62), rep("polyreg",1), rep("norm",12), rep("polyreg",12)) next step was

Hi, I was trying to plot the logistic regression from a regression "logreg" I just ran. I downloaded the "car" package from the R website and went to Packages -> install package from local zip file I checked in my library file and the package is there. I restarted R. I then ran the command: reg.line(logreg,col=palette()[2], lwd=2, lty=1) And I get the error: Error: could

This is a function I coded a few years ago to calculate a confidence interval for a coefficient of variation. The code is based on a paper by Mark Vangel in The American Statistician. I have not used the function much, but it could be useful for comparing cv's from different groups. Kevin Wright confint.cv <- function(x,alpha=.05, method="modmckay"){ # Calculate the

Dear, We are trying to determine the (one-sided) CI for the coefficient of variation in a small sample (say n = 10), with mean 100 and standard deviation 21. It appears though that the R-function ci.cv() and our simulation do not agree. The R-code: library(MBESS) n = 10 ci.cv(mean = 100, sd = 21, n = 10, conf.level = 0.9) U10.95 <- 0.3551754 ci.cv(mean = 100, sd = 21, n = 10, conf.level =

Hello all, When attempting a classification tree using mvpart, I get the following error: > thesis2.mvp=mvpart(bat_sp~., data=alltrees.df) Error in all(keep) : unused argument(s) (c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,

Hi there, I've looked through the very helpful advice about adding fitted lines to plots in the r-help archive, and can't find a post where someone has offered a solution for my specific problem. I need to plot logistic regression fits from three differently-sized data subsets on a plot of the entire dataset. A description and code are below: I have an unbalanced dataset

I want to use the grplasso package on a data set where I want to fit a linear model.? My interest is in identifying significant?beta coefficients.? The documentation is a bit cryptic so I'd appreciate some help. ? I know this is a strategy for large numbers of variables but consider a simple case for pedagogical puposes.? Say I have?two 3 category predictors (2 dummies each), a binary

Hello. I have run the command imp<-mice(mydata, im=c("","pmm","logreg","logreg"),m=5)  for a variable with no missing data, a numeric one and two variables with binary data. I got the following message: There were 37 warnings (use warnings() to see them) > warnings() Warning messages: 1: In any(predictorMatrix[j, ]) ... : coercing argument of

Hi there, I am trying to plot some output from a FORTRAN (ifort) program using R (2.5.1) under batch mode. In the FORTRAN code, I call R in batch mode to execute a script called fig1.R using something like PROGRAM test USE IFPORT IMPLICIT NONE DO !Some function which makes an output file called ~/fortran_output.txt CALL myfunc() !System call to R plotting routine CALL SYSTEM