similar to: Matrix-like plot

Hello i did a stacked barplot using ggplot and R arranged the bars of the items in different orders. i don?t know why. but i want to have the same order in every stacked bar. I used the code data1 <- read.table("N_O_W_MAI.txt", header=TRUE, dec = ",") attach(data1) Teich1<-factor(Teich,levels=c(5,7,9,11,"G") ,ordered=is.ordered(Teich))

hi everyone . Now I want to draw several lines in one frame.And it seems needs more colors except for blue red,black .Where can i found these color name or define some new color ?thank you . -- TANG Jie Email: totangjie@gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China [[alternative HTML version deleted]]

Dear r-helpers, I wonder whether, given the "#rrggbb" representation of a colour, there is a simple way to select the complementary colour, also expressed as a "#rrggbb" string. Any suggestions would be appreciated. John -------------------------------- John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604

Dear Lists, At several stations distributed regularly in space[1], we sampled repeatedly (4 times) the abundance of organisms and measured environmental parameters. I now want to compare the spatial distribution of various species (and test wether they differ or not), or to compare the distribution of a particular organism with the distribution of some environmental variable.

Hi All I am not clear quite how one could use cca from package vegan and the associated predict.cca to predict species abundance from environmental data (or if this is possible in a generalised way). In other words, can one derive a cca object based on known community data and use that to predict e.g. species abundances in a different number of samples based on environmental data? The help

My laboratory is measuring the abundance of various proteins in the blood from either healthy individuals or from individuals with various diseases. I would like to determine which proteins, if any, have significantly different abundances between the healthy and diseased individuals. Currently, one of my colleagues is performing an ANOVA on each protein with MS Excel. I would like to analyze

Dear all, I have a question on the use of GAM with repeated measures. My dataset is as follows: - a number of study areas where bird abundance has been determined. Counts have been performed in 3 consecutive years and there were 2 counts per year (i.e. in total 6 counts). - a number of environmental predictors that do not change over year Xi). When using a GLM, a repeated measures design would

Dear R friends- I'm attempting to generate a regression tree with one gradient predictor and multiple responses, trying to test if change in size (turtle.data$Clength) acts as a single predictor of ten multiple diet taxa abundances (prey.data) Neither rpart or mvpart seem to allow me to do multiple responses. (Or if they can, I'm not using the functions properly.) > library(rpart)

Hey, I am trying to create barplot of abundances over time (in days). The period is over 171 days, so I don't want to have all labels there but only the first day of the month. I couldn't find anything like this on the forum yet. Mostrly it's about year to year data. This is the relevant part of my table: datum month abundance 26/03/11 March 1 27/03/11 March 0 28/03/11 March 1

Hi, I?ve written a script to run several multivariate statistical analysis automatically. As one result a biplot and screeplot is produced. Now I?d like to display the name of the inputdatset as part of the title of these graphics and I do not want to enter it each time I run the script. How can I extract the name of a dataset? An (shortened) extraction from the script: >Test1 <-

Hello all, I'm trying to find all combinations of 4 numbers that satisfy 4 criteria, inside of a matrix (62 x 25). I've found a way to do this using for loops, but it is extremely slow because it involves checking every possible combination of numbers (567300) to see if the criteria are satisfied. Do you think there is a faster method of doing this? Or some functions that might help me

Dear, I would like to post the following question to the r-help on Nabble (thanks in advance for the attention, Gustavo Vieira): Hi there. I have a data set on hands with 5,220 cases and I'd like to automate some procedures (but I have almost no programming knowledge). The data has some continuous variables that are grouped by 2 others: the name of species and the locality where they were

The background: I'm trying to fit a Poisson-lognormal distrbutuion to some data. This is a way of modelling species abundances: N ~ Pois(lam) log(lam) ~ N(mu, sigma2) The number of individuals are Poisson distributed with an abundance drawn from a log-normal distrbution. To fit this to data, I need to integrate out lam. In principle, I can do it this way: PLN1 <- function(lam, Count,

Hi again all, Several replied ASAP that I also needed reshape loaded and not just reshape2. Hmmm tried that and I had some output but not the correct format. What I need is to run simulations of time overlap between species as per the simulation program data input constraints: The basis for the simulations is a species by _time-use matrix in which species are arranged in rows, and time

It is a trivial problem, but in the book I couln`t figure out how to put different colours at different regression lines plot(bif,abund,type="n", xlab= "number_bifurcations", ylab="abundances") sbif<-split(bif,stage) sabund<-split(abund,stage) points(sabund[[2]],sbif[[2]],pch=16, col="red") for(i in 1:2) abline(lm(sabund[[i]]~sbif[[i]])) Thanks in

Hi, I am doing canonical discriminant analysis using candisc function from the candisc package. My input is a table of species distribution (columns = abundance of each species in each sample) in samples that are split by categories (rows), and I want to know whether each category is associated with a particular set of species and their abundances. I have 20 rows (samples) split into 6

I've written a function that regularly throws the "cannot allocate vector of size X Kb" error, since it contains a loop that creates large numbers of big distance matrices. I'd be very grateful for any simple advice on how to reduce the memory demands of my function. Besides increasing memory.size to the maximum available, I've tried reducing my "dist" objects to 3

Hello, How can I randomly sample individuals within a sites from a site (row) X species abundance (column) data frame or matrix? As an example, the matrix "abund2" made below. ##### (sorry, Im a newbie and this is the only way I know to get an example on here) abund1 <- c(150, 300, 0, 360, 150, 300, 0, 240, 150, 0, 60, 0, 150, 0, 540, 0, 0, 300, 0, 240, 300, 300,

Dear useRs I am looking for a way to randomise the values within a matrix: the conditions are that the sums of the rows and the sums of the columns should remain the same as in the original matrix. Any help would be appreciated Cheers Yann

Hi, all I have a rather un-ideal dataset that I am trying to work with, and would appreciate any advice you have on the matter. I have 4 years worth of data taken at 3 depth-zones from which samples have been taken at random. I am looking at the abundance of organism A between depth zones and across years, and am interested in the possible interaction of organism A distributions shifting