similar to: Problem with area()

Hi, I have a dataset with x and y coordinates and in each point I have an identity of point, in some cases I can have more then one identity by point. My dataset is something like this: > x <- rep(c(1:4),4) > y <- rep(c(1:4),c(4,4,4,4)) > area1 <- sample(factor(rep(c("a","b","c","d"),4))) > area2 <-

Dear list, When I use VennDiagram package, I got a error as follow: venn.plot <- draw.pairwise.venn( area1 = 3186, area2 = 325, cross.area = 5880); Error in draw.pairwise.venn(area1 = 3186, area2 = 325, cross.area = 588) : Impossible: cross section area too large. Does anyone have suggestion? Thank you.

I'm reading Torgo (2010) *Data Mining with R*<http://www.liaad.up.pt/~ltorgo/DataMiningWithR/code.html>in preparation for a class I'll be teaching next quarter. Here's an example that is very non-functional. > pH <- c(4.5,7,7.3,8.2,6.3) > names(pH) <- c('area1','area2','mud','dam','middle') > pH area1 area2 mud dam

Hi there, I am not getting anywhere near a solution, so here is my question. I have searched the archives and didn't find a solution, but maybe my search didn't use the right words. So here it is: I have a dataframe with the following structure factor1 factor2 value In the (rather large) dataset I have to work on, there are some factor combinations missing, e.g. factor1 <-

Dear laurent, > But there are lots of commands I found in R docs which are "not found", > such as getTable. Deprecated (I successfully used dbListTables) or do I > simply miss a package ? >From RMySQL\NEWS: * added (almost) trivial convenience RS-DBI functions getTable(), assignTable(), existsTable(), and removeTable(). They all mimic the corresponding R/S get(),

My data frame looks like: SightingID PA1 PA2 PlotID InOverlap Area1 2001 1 -99 392 Y 0.22 2002 1 -99 388 Y 0.253 2008 1 NA 104 N 0.344 2010 1 NA 71 N 0.185 2012 1 NA 61 N 0.166 2013 1 NA 61 N 0.227 2014 1 NA 62

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

Dear all, I am trying to merge two data frames based on a common column but for this common column both data frame do not have the same length and associated information. I checked previous exemples in the list but was not able to apply them in my case... Is someone know how to do that? Below is my code with the expected result: # data frame 1 Id1 <- c(1,1,1,2,2,2,3,3,3) Habit1 <-

Note: I don't know if this is a problem withe I20 drivers or Rsync so I'm submitting to both the Kernel Bugzilla and the Rsync mailing list. I couldn't find a bugzilla for Rsync. I hope this was the correct way to submit this issue. Distribution: Debian Hardware Environment: Intel 850MV Mother board, Pentium 4 processor, 1Gig of RAM, Adaptec 2400A RAID Controler. Both the

Dear All I would really appreciate some help with a script which a colleague wrote for me (attached), but I am having problems running (and have not been able to contact my colleague). The script is designed to compare the area of suitable habitat in binary projections of a large number of species current and future distributions, and create an excel file detailing the total area suitable in the

Hello my name is Piercarlo and I've discovered a bug in smbd_audit when I trace a Samba 2.2.7 or 2.2.7a on red hat 7.3 -the error exist on the redhat 2.4.18-17kernel ,on the original rh73 2.4.18-3 kernel and on the standard linus kernel (I tried on 2.4.20)-->these kernels are all the kernels that I tried. This error appear when samba is configured as pdc with the roaming of the users

I used the supersmoother function in the modreg package as follows: super <- supsmu(ilogemp,award) Then I decided that I might want additional explanatory variables (other than ilogemp) in my model. The ppr function in modreg seemed a logical extension of supsmu from univariate to multidimensional explanatory variables. As a "check" I ran the following: pprest <-

Hi all: Here's a question about result of loglinear analysis. There're 2 factors:area and nation.The raw data is in the attachment. I fit the saturated model of loglinear with the command: glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis) After that,I extract the coefficients: result_sat<-summary(glm_sat) result_coe<-result_sat$coefficients I find that all the

Given the data structure below, how can I create a bar plot for the values of disc for each area grouped by year? bar <-structure(list(year = c(2003, 2003, 2003, 2003, 2003, 2003, 2003, 2007, 2007, 2007, 2007, 2007, 2007, 2007), area = structure(c(6L, 4L, 1L, 2L, 3L, 5L, 7L, 6L, 4L, 1L, 2L, 3L, 5L, 7L), .Label = c("AK", "ID", "MT", "NW",

Estimad en s, quería realizar una consulta Dado un data frame llamado aves, como puedo sustiuir las variables area, dist y distm por sus logaritmos en base10 y volver a crear un data frame? Muchas gracias Saludos Susana [[alternative HTML version deleted]]

I can't reproduce the more complex version. But the package on CRAN fails in the same way on 3.2.3 and 3.3.0. The problem is that your sysdata.rda includes a function that is generating this error. If you do f <- getFromNamespace(".RMXE", ns ="RobAStRDA")[["GEVFamily"]][["fun.N"]][[1]] g <- get("fct", environment(f)) and look at the

Can you provide a complete reproducible example? Sent from my iPhone > On May 1, 2016, at 6:51 AM, Peter Ruckdeschel <peter.ruckdeschel at web.de> wrote: > > Hi r-devels, > > we are seeing a new problem with our packages RobAStRDA (just new on CRAN, thanks > to Uwe and Kurt!) and RobExtremes (to be submitted). > > It must be something recent with the way you

Here's one way. Suppose your "time series" is in a vector called "x". top10 <- sort(x, decreasing=TRUE)[1:10] mean.index <- mean(which(x %in% top10)) HTH, Andy > -----Original Message----- > From: James Brown [mailto:jdb33 at hermes.cam.ac.uk] > Sent: Tuesday, September 23, 2003 7:51 AM > To: r-help at stat.math.ethz.ch > Subject: [R] Rank and

Dear R Users, I have a couple of proto objects like: wedge <- proto(expr={ start.year <- 2008 end.year <- 2050 }) star.rating <- wedge$proto( star = c(4, 5, 8, 10), gain = c(0, .3, .5, .7), cost = c(0, 2100, 4000, 7500), star.rating <- function(., year) 6.0, setup = function(.){ .$cost.for.star <- approxfun(.$star,

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating