similar to: lm.fit error in scatterplot matrix

I am trying to create a heap of boxplots, by looping though a series of factors and variables in a large data.frame suing paste to constrcut the facto and response names from the colnames I thought I could do this using get() however it is not working what am I doing wrong? thanks Nevil Amos > sp.codes=levels(data.all$CODE_LETTERS) > > for(spp in sp.codes) { > > >

Hi, I am wondering if anybody has experience with scatterplot matrices where some (but NOT all) axis are transformed and the labels are nicely plotted. So far I looked into 1) pairs() 2) scatterplotMatrix() from package 'car' 3) splom() from packagae 'lattice' 4) plotmatrix() from 'ggplot2' I can see no easy way to get what I want which is: *) a scatterplot matrix of

Dear R-users, I'm studing a DB, structured like this (just a little part of my dataset): _____________________________________________________________________________________________________________ Site Latitude Longitude Year Tot-Prod Total_Density dmp Dendoudi-1 15.441964 -13.540179 2005 3271.16 1007 16993.25 Dendoudi-2 15.397321 -13.611607

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Hello, I am unable to figure out how to code a new column in a data frame based on an existing column that matches a column in a reference data frame, in a relational-db fashion. I would like this to maintain a minimum set of reference tables that may be reused over several similar datasets. Specifically, I have two data frames as listed below, 'Bos' and 'tree.' For each case in

Hello guys, I'm trying to do a pairs trading cointegration analysis on two stocks (AXAP and AXANY), but I get an error that I don't understand... Here's my code: setwd("S:/Users/Alexis/Desktop/Essai") #chemin du dossier contenant les donn?es donnees <- read.csv("Data_R.csv", head=T, sep=";", stringsAsFactors=F) library(xts) dates <-

Hi everyone, I am running a monte carlo and am getting an error that I haven't the slightest clue where to begin figuring it out. The error is as follows: Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases In addition: Warning message: In ltm.fit(X, betas, constraint, formula, con) : Hessian matrix at convergence is not positive definite;

Hello, I am new with R, and I'm trying to fit a linear model, I did the following and obtein this result, can anybody help? Thanks, > logdftodos7925vi <- log(dftodos7925vi) > logALTURA7925<- log(dftodos7925$ALTURA7917) > logtodos7925.lm <- lm (logALTURA7925~., data= logdftodos7925vi) Error en lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf en

I am using R.2.4.1 on Windows XP 5.1 (SP 2). I have the following line in my R code. Analysis=anova(lm(PM ~ x)) It works the first 60 or so times it is called but then I get the following error message. Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases In order to examine the input, I preceeded the call with the following. print(PM) print(x) This gave

is there a way to reduce the size of pdf files in R: ? compression? lower dpi ? or some other option?

Good day to the R community, I am interested to run the plot.count() function in the "untb" package. My script is as follows:- > library(untb) > Community1 <- > structure(c(371,167,119,78,74,53,50,31,28,25,20,19,19,17,13,12,12,10, > 9,9,8,8,7,7,7,7,6,6,6,6,5,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,1,1,1,1,1, > 1,1,1,1,1,1,1,1), .Dim = 60, .Dimnames =

##I am trying to test for fixed factor main effects in an unbalanced mixed effects model but when I fit the reduced model for "mic" factor effects, the extra degrees of freedom are being allocated to a nested term rather than the residuals. The model has inc, mic and spp are independent variables and vial nested within spp. inc and spp are already coded as factors since they were

Hello, I'm trying to convert a character column in several dataframes to lower case. ### # # Sample data and 'spp' column summaries: # dput(ban.ovs.1993[sample(row.names(ban.ovs.1993), 20), 1:4]) ban.ovs.93 <- structure(list(oplt = c(43L, 43L, 38L, 26L, 35L, 8L, 39L, 1L, 34L, 50L, 10L, 29L, 31L, 24L, 18L, 12L, 27L, 49L, 28L, 51L), rplt = c(NA_integer_, NA_integer_,

Dear R-help folks, Can someone guide me to a source where I can learn more about the / operator in model formulae? I found a reference to it in Venables and Ripley's MASS, p. 142, where it says, in reference to ANCOVA: "Terms of the form a/x, where a is a factor, are best thought of as 'separate regression models of type 1 + x within the levels of a.'..." This seems

Hi, consider the following example: I have a matrix like this: spp.mds$points [,1] [,2] CLAP0 1.79703164 -11.66716182 CLAP30 3.87034797 -7.48168377 YBI0000 10.27538316 -3.32226184 YBI0100 0.58463806 -1.25748701 hir10000 5.82907036 -4.09695960 hir10016 -2.22113472 -4.86563557 gyn30000 5.14643671 -3.58706541 gyn30032 2.99552434 -6.21815132 ...

Hi all, I'm fitting a linear model (using lm) to some 2500 data points. The model consists of 4 single terms and two combined terms. I get the following warning message: "Extra arguments projections are just disregarded. in: lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) " Can anybody clarify this ? I don't seem to find any pointer to what this might

Hi, I would need some help with the splans package in R. I am using a Shapefile (downloadable at) http://rapidshare.com/files/215206891/Redlands_Crime.zip and the following execution code setwd("C:\\Documents and Settings\\Dejan\\Desktop\\GIS\\assignment6\\DataSet_Redlands_Crime\\Redlands_Crime") library(foreign) library(splancs) auto_xy<-read.dbf("Auto_theft_98.dbf")

I have some square matrices with na values in corresponding rows and columns. M<-matrix(1:2,10,10) M[6,1:2]<-NA M[10,9]<-NA M<-as.matrix(as.dist(M)) print (M) 1 2 3 4 5 6 7 8 9 10 1 0 2 1 2 1 NA 1 2 1 2 2 2 0 1 2 1 NA 1 2 1 2 3 1 1 0 2 1 2 1 2 1 2 4 2 2 2 0 1 2 1 2 1 2 5 1 1 1 1 0 2 1 2 1 2 6 NA NA 2 2 2 0 1 2 1 2 7 1 1 1 1 1 1 0 2 1 2 8

Hello: I am using R mainly on windows XP, version 2.5. I?m a biologist, with a medium level statistics background. I have a problem stating a two-way factorial design where both factors are random. I?m using the lmer() function implemented in the Matrix package version 0.99. My design is as follows: Two species were randomly selected from a total of 4 species. This species are present

I need to replace <NA> occurrences in multiple columns in a data.frame with "000/000" how do I achieve this? Thanks Nevil Amos