similar to: how to calculate the consistency of different clusterings

Dear Ruser's I ask for helps on how to substitute missing values (NAs) by mean of the group it is belonging to. my dummy dataframe is: > df group traits 1 BSPy01-10 NA 2 BSPy01-10 7.3 3 BSPy01-10 7.3 4 BSPy01-11 5.3 5 BSPy01-11 5.4 6 BSPy01-11 5.6 7 BSPy01-11 NA 8 BSPy01-11 NA 9 BSPy01-11 4.8 10 BSPy01-12 8.1 11 BSPy01-12 6.0 12

Dear R-listers, There is my data and my codes to create a plot. I want to know why there are two small circles in the upper right and lower left of the plot respectively. Could you please share your experience or advice with me? # dummy data factor<-rep(c("Alice","Jone","Mike"),each=100) factor<-factor(factor) traits<-c(rnorm(100, mean=1, sd=1), rnorm(100,

Dear R-listers, I have created a plot to display the density lines for the same variable by different entities. Now, I want to fill the area under the density lines with semitransparent colors. Though I have checked that in web-searching and book-reading, I still do not perform that. Could anyone please give me any helps or advice? Thank you in advance. The data and code I used listed below: #

Dear Ruser's I want to substitute each "NA" by the group mean of which the "NA" is belonging to. For example, substitute the first record of traits "NA" by the mean of "BSPy01-10" in the dummy dataframe. I have ever tried to solve this problem by using doBy package. But, I failed. I ask for the advice on how to use "lapplyBy" function of

> DATA [,1] [1,] -2.0314185 [2,] -0.3594015 [3,] -1.3225832 [4,] 1.5050892 [5,] -0.4535558 [6,] 3.6335036 [7,] 5.1965750 [8,] 4.2923129 [9,] 6.0913187 [10,] 4.9131070 > RESA [,1] [,2] [,3] [,4] [,5] [1,] -2.0314185 1.5050892 -1.3225832 -1.3225832 -2.0314185 [2,] -0.3594015 -0.3594015 4.2923129 -0.3594015

I need help on calling the svydesign function in the survey package (although this error appears not to be specific to svydesign). I am passing parameters incorrectly but am not sure how to correct the problem. ## Call the main function PS.sim (one of mine). The dots are parameters I omitted to simplify the question. ## y.col, str.col, clus.id, and PS.col are names of columns in the object pop.

Hello, I've used mantel tests a fair bit for standard genetic/geographic/landscape analyses. I realize it involves permutations of rows and columns in the matrix to obtain correlation coefficients. However, for a certain question, I am interested in populations that are nearest neighbours to each other, and identifying factors that affect genetic distance between them. So because of

Dear WizaRds, I am trying to compute the (adjusted) Rand Index in order to comprehend the variable selection heuristic (VS-KM) according to Brusco/ Cradit 2001 (Psychometrika 66 No.2 p.249-270, 2001). Unfortunately, I am unable to correctly use cl_ensemble and cl_agreement (package: clue). Here is what I am trying to do: library(clue) ## Let p1..p4 be four partitions of the kind

Dear people, A somewhat clueless question follows: I just discovered that the lme function in contrib package nlme for R, while similar to the lme function in Splus, does not use the cluster function option. This difference does not appear to be documented in the V&R `R Complements' file. I have data which is divided into 6 groups The lme model is of the form (simplified from the actual

Dear Mao Jianfeng, "r-help-owner" is not the place for help, but: r-help at r-project.org (CC-ed here) In any case, strsplit() does the job, i.e.: > unlist(strsplit("BCPy01-01", "-")) [1] "BCPy01" "01" You can work with the whole variable, like: splitpop <- strsplit(df1$popcode, "-") then access the first part with >

Dear R-help listers, I am new. I just want to get helps on how to plot two histograms overlapped in the same plane coordinate. What I did is very ugly. Could you please help me to improve it? I want to got a plot with semi- transparent overlapping region. And, I want to know how to specify the filled colors of the different histograms. I also prefer other solutions other than ggplot2. Many

Hi, R-listers, Failed, when I tried to merge df1 and df2 by "codetot" in df1 and "codetoto" in df2. I want to know the reason and how to merge them together. Data frames and codes I have used were listed as followed. Thanks a lot in advance. df1: popcode codetot p3need BCPy01-01 BCPy01-01-1 100.0000 BCPy01-01 BCPy01-01-2 100.0000 BCPy01-01 BCPy01-01-3 100.0000 BCPy01-02

Dear all, This is a simple probability problem. I want to know, How to generate a normal distribution with mean=1, min=0.2 and max=0.8? I know how the generate a normal distribution of mean = 1 and sd = 1 and with 500 data point. rnorm(n=500, m=1, sd=1) But, I am confusing with how to generate a normal distribution with expected min and max. I expect to hear your directions. Thanks in

Hello dear R-users, I have a tricky problem of data manipulation with R. Although it seems very easy, I can not solve it by myselves. The problem is a variable in my dataset is usually be readed as "factor" (variable mode), however I want it be a "numeric" one. I want to know how can I define an variable/column in a dataframe as numeric mode, after I imported a large

Dear R-listers, I am new to R in linux. And, I am now confused by updating R in Ubuntu 9.10 linux system. I would like to seek some advice on that problem. I have done what are listed in CRAN linux installation guide: 1. add an entry like "deb http://cran.cnr.berkeley.edu/bin/linux/ubuntu karmic/" in /etc/apt/sources.list file in my computer. 2. To install the complete R system, use

Dear R-Helpers, I am using qtl package to analyze qtl data from QTL cartographer. I have the map file and cro file from QTL cartographer. I was trying to import these two files in R using qtl package. data=read.cross("qtlcart", ".", "crofile.txt", "mapfile.txt") ### I have matched the file structure with the one on the website of qtl package - It matches

Dear R-helpers I want to express my respect and thankfulness to all of you. I just switch from windows xp to Ubuntu linux platform. I am facing two problems when I run R in Ubuntu. I need your helps and advice, thanks in advance. ----------------------------------------------------------------------------------------------------------------------------------------------------------- 1. JGR()

Hi, can anyone help me fit betabinomial model to the following dataset where each iD is a cluster in itself , if i use package aod 's betabinom model it gives an estimate of zero to phi(the correlation coeficient ) and if i fix it to the anova type estimate obtained from icc( in package aod) then it says system is exactly singular. And when i try to fit my loglikelihood by

Hi, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

Is there a package that will allow me to fit Brownian motion and Ornstein?Uhlenbeck models of evolution for discrete traits? I know that geiger and ouch have commands for fitting these models for continuous traits, but these aren't suitable for discrete trait evolution, correct? -- View this message in context: