search for: terrestrialization

Dear R list, I am having some trouble drawing a bar-graph with two groups, both of which are stacked. A sample of my data (IUCN and national conservation status for marine and terrestrial species) look like this: Status IUCN Terrestrial IUCN Marine National CS Terrestrial National CS Marine NE 168 69 16 69 LC 41 6 148 6 NT 5 4 7 4 VU 4 2 7 2 EN 4 2 4 2 CR 1

Dear R list, It appears that my request from yesterday got a bit garbled. I have tried to rephrase and retype it - please let me know if you can help me - I am having some trouble drawing a bar-graph with two groups, both of which are stacked. I would like to plot the conservation status according to two classifications (i.e. my groups - IUCN status and national status), and for each of those

Hi, Assuming that your dataset is similar to the one below: set.seed(25) dat1<- data.frame(Algae.Mass=sample(40:50,10,replace=TRUE),Seagrass.Mass=sample(30:70,10,replace=TRUE),Terrestrial.Mass=sample(80:100,10,replace=TRUE),Other.Mass=sample(40:60,10,replace=TRUE),Site.X.Treatment=rep(c("ALA1A","ALA1U"),each=5),stringsAsFactors=FALSE) library(reshape2)

Hi: I am a very recent user of R 1.40 for MacOSX and went through the help files but did not not find the function that I am looking for. I have two comma separated files which I want to partly combine. File 1 has 49670 lines and 26 columns (separated by commas) and looks like this: ...

Dear Friends, I am really glad to share this link with you. Some of you have been instrumental to the success of the work. You are acknowledged accordingly. I am ever indebted. Best wishes Ogbos ---------- Forwarded message --------- From: Elsevier - Article Status <Article_Status at elsevier.com> Date: Wed, Oct 7, 2020 at 10:50 AM Subject: Share your article [ATP_105460] published in

Saludos, tengo una base de datos con tres variables: especie, tratamiento y abundancia. Quiero hacer comparaciones múltiples con Tukey. Ya había usado el comando TukeyHSD(aov(x~y)). La cuestión esque ahora tengo varios niveles del factor especie y varios niveles del factor tratamiento. Si hago TukeyHSD(aov(abundancia~especie:tratamiento)) me salen todas las comparaciones posibles, pero yo sólo

At 03:55 PM 2/29/2004, you wrote: >Hi Oddsock, > >Like Clement, I am sure Nullsoft is still "offering" AOL's bandwidth since I >think Nullsoft is not part of AOL anymore. About the new broadcasting >methods, is the multicast technology already available? I have heard only >few providers are equipped with multicast enabled routers. People have been chasing multicast

Hi, I'm trying to build a mixed-effects model in which I'd like to include either a distance matrix or a phylogenetic tree as a random effect. The troubles I've had are that: 1. Function lmer() in package lme4 only accepts a data frame column as a random factor and not a distance matrix. 2. Function MCMCglmm() in package MCMCglmm only accepts a rooted and ultrametric phylogenetic

Hi all, I've used R for basic programming and data management for a few years now. One of the things that I think could be improved is the data editor. Its a great feature and I use it alot by calling edit(data.frame); very useful to see if what you tried to do actually worked. However, one of the annoying things about it is that when you scroll down the window it doesnt show you all the

Hi Oddsock, Like Clement, I am sure Nullsoft is still "offering" AOL's bandwidth since I think Nullsoft is not part of AOL anymore. About the new broadcasting methods, is the multicast technology already available? I have heard only few providers are equipped with multicast enabled routers. What about p2p streaming, is it really reliable? When I see Peercast's statistics, only

Dear R-users with a bit of grief I had to repeat an extensive analysis because I did not suspect (and therefore did not read the documentation) that round was implemented as "for rounding off a 5, the IEC 60559 standard is expected to be used, 'go to the even digit'", resulting in round(1.5) = 2 round (2.5) = 2. As a non-mathematician I am both puzzled and intrigued by

Hello all. I've been a fan of the xiph project for some time, thank you for your excellent work. I am looking for a fully-developed, beta, or alpha open-source hardware platform for remote deployment to terrestrial fm transmitters and streaming to general internet listeners. Willing to participate in development/beta testing of projects or possible $ support for an existing project. Able

I try memory.size function to find out available memory size, but surprisingly R complains it can't find the function. ?memory.size also failed. Is it not in the base library? If so, why can't my R find it? I am using the binary 1.9.0 version for Mandrake 9.1. Thanks in advance. Daehyok Shin Terrestrial Hydrological Ecosystem Modellers Geography Department University of North

Greetings, I have some confusion with the use of if - else. Let's say I have a four variables as follows: Condition DateFound DateFirstEvent DateSecondEvent NA 10Jan2000 NA NA 0 05Jan2000 07Jan2000 10Jan2000 1 07Jan2000 07Jan2000

We have a number of DID's that do the standard VoIP tricks: ringing multiple locations, findme-followme etc. What is happening more and more is that customers call those DID numbers, and draw the reasonable conclusion that they are calling mobile numbers because they literally can HEAR that the called party is on a mobile. Consequently many of those customers draw the conclusion that they

hi all, I often have a data frame like this example data.frame(sq=c(1,1,1,2,2,3,3,3,3),area=c(1,2,3,1,2,3,1,2,3),habitat=c("garden","garden","pond","field","garden","river","garden","field","field")) for each "sq" I have multiple "habitat"s each with an associated "area". I

Hi all, This could be naivety/stupidity on my part rather than a problem with model output, but here goes.... I have fitted a fairly simple model m1<-glm(count~siteall+yrs+yrs:district,family=quasipoisson,weights=weight,data=m[x[[i]],]) I want to know if yrs (a continuous variable) has a significant unique effect in the model, so I fit a simplified model with the main effect ommitted...

Hi all, I have been trying to use zeroinfl() with the pscl package with R version 2.1.1. and with the newest versions of the contrib packages compatible with R 2.1.1. I have read the examples, the vignette and all the posts relating to zeroinfl() but I am still confused as to how to structure the model. Here is a small example; the error message is the same for big data sets

Once upon a time, Warren Young <warren at etr-usa.com> said: > a. It?s transmitting from a fixed location in a time zone you probably aren?t in ? US Mountain ? being the least populous of the lower 48?s four time zones. You therefore have to configure time zone offset and DST rules, which means additional software if you want it to track changes to these things. There were 10 batches of

Dear R-users, I'm new to R, so my apologies if this question doesn't make sense. I've tried the following model in lmer, and it works perfectly: model<-lmer(aphids~densroot+zone+(1|zone/site), family=quasipoisson) But if I try the exact same model with a different variable, totmas, the model looks as follows: model<-lmer(aphids~totmas+zone+(1|zone/site), family=quasipoisson)