similar to: panel function question

I have a data file with 50 columns. Among them, there are two coordinates, X and Y X Y 641673.78807 3607080.78438 641436.56207 3607108.30543 641165.28042 3607136.82957 640879.58373 3607116.20568 When I use read.table, it rounds X and Y to the maximal 8 decimal number as. 641673.8 3607081 641436.6 3607108 641165.3 3607137 640879.6 3607116 640683.5 3607105 My question

HI, I am working on a data set with multiple collections of mosquitoes at sampling sites. Each row represents a collection of individual samples with coordinates for each collection. ... X, Y,... 1 36.435 30.118 2 36.435 30.118 3 36.435 30.118 4 35.329 29.657 5 35.329 29.657 6 36.431 30.111 7 36.431 30.111 8 35.421 29.797 9 35.421 29.797 10 35.421 29.797

Hi, I am at the end of my wit to figure out how to run the optim function on a list. Basically, I have a data set of three columns as "Site", "Pool" and "Positivity" ( the full data set is copied at the end). I want to run the maximal likelihood estimation separately on subsets split by "Site" data<-read.table(...)

Hi, I ran into a problem when I complied a dataset with UTM coordinates. For calculating distances between sites, I need to reformat the coordinates from, for example, 32?35.421 N, to 35.421, i.e. I need to delete all digits before symbol ? and a space and N at the end of the string. What functions I should use? Thanks in advance. Weidong Gu, Department of Medicine University of

Dear listers, I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is:

Hi, I am new in statistics and i manage to make the linear model analysis but i have some difficulties in explaining the results. Can someone help me explalinig the output of my linear model analysis ? My data are with 2 variables habitat (e,s) and treatment (a,c,p) with multiple trials within. Thank you in advance Call: lm(formula = a$wild ~ a$habitat/a$treatment/a$trial) Residuals: Min

Hello all, Can any of you R gurus help me out? I?m not all that great at stats to begin with, and I?m also learning the R ropes (former SAS user). Here?s what I need help with? I have a nested sample design and ran a nested anova, but I don?t know how to interpret the results habitat (four different types) is nested in site (three types), and site is nested in gear (two types)

Dear R-users, A while ago, Deepayan Sarkar suggested some code that uses the group argument in bwplot to create some 'side-by-side' boxplots (https://stat.ethz.ch/pipermail/r-help/2010-February/230065.html). The example he gave was relatively specific and I wanted to generalize his approach into a function. Unfortunately, I seem to have some issues passing the correct arguments to the

Hi All, I am frustrated by mixed-effects model! I have searched the web for hours, and found lots on the nested anova, but nothing useful on my specific case, which is: a random factor (C) is nested within one of the fixed-factors (A), and a second fixed factor (B) is crossed with the first fixed factor: C/A A B A x B My question: I have a functioning model using the aov command (see

Dear All, I would like to make partial sums (or means or any other function) of the values in intervals along a sequence (spatial transect) where groups are defined. For instance: habitats<-rep(c("meadow","forest","meadow","pasture"),c(10,5,12,6)) observations<-rpois(length(habitats),2)

Dear fellow R users, Keywords: Kruskal-Wallis, Post-Hoc, pair-wise comparisons, Nemenyi-Damico-Wolfe-Dunn test, coin package, oneway_test I am using the "oneway_test" function in the R package "coin" and I am obtaining results which I cannot believe are accurate. I do not wish to waste anyone's time and so if the following problem is rather trivial, I apologize, however I

Dear R users, I face to a nested pattern and despite the numerous examples in the help I am still confused. I sampled bugs in different habitats within sites which were within rivers themselves within different regions. The habitat correspond to different substrata (not systematically present in all sites). For rivers and sites, I have environemental variables (e.g. altitude and slope of

Dear expeRts, I would like to colorize the backgrounds of a pairs plot according to the respective panel number. Here is what I tried (without success): count <- 0 mypanel <- function(x, y, ...){ count <<- count+1 bg. <- if(count %in% c(1,4,9,12)) "#FDFF65" else NA points(x, y, cex=0.5, bg=bg) } U <- matrix(runif(4*500), ncol=4) pairs(U, panel=mypanel) I

Dear all, I would like to solve a trivial problem (I guess it is) but can't find the right way. Maybe someone can help me ? I've got a table with two factors (station = station ID, buffer = buffer size in meters) and a value for each unique combination of those two factors (S = number of habitats within each buffer around each station) like this: TABLE 1 station buffer S Abaia01 200 2

I wish to create a multipanel plot (map) from several datasets ("d" and "q" in the example below). I can condition the main xyplot statement on the "site" variable, but I don't know how to pass a conditioning variable to panel.xyplot plot so that the x-y coordinates from dataset q are only plotted at the appropriate site. library(lattice) d <-

I wish to display a single-panel Lattice figure with grouped data and fitted regression lines. I don't seem to be able to get the individual regression lines to display, e.g.; d <- data.frame(q = rep(1:6, each=10), cc = rep(seq(10,100, 10),6)) # create data frame with group identifier 'q', independent variable cc d$ba = d$q*0.1*d$cc + 5*rnorm(nrow(d))

Hi, I have a data.frame df with names(df) = c("Var1", "Var2", "Var3", "Var4") and I plot data with xyplot(Var1+Var2~Var3|Var4, data=df) I want to use different panel functions for Var1 and Var2. How can I do ? Something like : panel.mypanel = function(x, y, ...) { if (Var1) panel.Var1Panel(x, y, ...) else panel.Var2Panel(x, y, ...) }

Hi, I am trying to create a plot with pairs() using a gplot.hexbin() for each pair. For pairs I can provide a custom upperPanel function: pairs(iris[1:4], panel=mypanel) and mypanel() calls plot.hexbin(): library(hexbin) # Bioconductor mypanel <- function(x, ...){ hb <- hexbin(x) plot(hb) } The problem is that gplot.hexbin() is based on the

Hello, I have been trying to make a graph that have error bars and text at specific position. I used the following code from the help file of xYplot(Hmisc) as an example except I add a myPanel function, which is just supposed to add letters from the alphabet at the position aligned at y = 3. It constantly gives me error: "Error using packet 1 argument "subscripts" is

Hi all, How can I decrease the number of ticks on the y-axis in a lattice levelplot()? I have as many ticks displayed on the y-axis as I have columns of data (1000 columns), how can I decrease this amount of ticks, while still properly displaying all the data? Note that I get my data from a matrix object, in which the z-values of the levelplot are the actual values in the matrix, whereas the