search for: abundances

I'm having the most curious error while using the sem package. For the model I'm working with, I keep getting the following error: Error in J[cbind(1:n, observed)] <- 1 : subscript out of bounds I''ve used debug=TRUE with sem, and there don't appear to be any problems with model - there are no latent variables in this model. The variables in the covariance matrix

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

I'm looking over good-code a post-doc in my lab wrote and trying to learn how it works. I came across the following: rel.abundance <- as.matrix(read.delim("rel.abundance.csv",row.names=1,as.is =TRUE)) rel.abundance <- log2(rel.abundance-min(rel.abundance)+1) I'm not sure what the second line is doing. I ran each line in R and couldn't see a noticeable difference in

Hello, please excuse the simplicity of this question as I am not very good with stats. I am taking a class, using R which I am learning at the same time, and the questions asks us to "Estimate the average abundance using Poisson regression with a log link". I can estimate the abundance from "x", but I can seem to figure out how to get the average abundance in this method. Any

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root

Dear R users, I am having problems trying to fit quasipoisson and negative binomials glm. My data set contains abundance (counts) of a species under different management regimens. First, I tried to fit a poisson glm: > summary(model.p<-glm(abund~mgmtcat,poisson)) Call: glm(formula = abund ~ mgmtcat, family = poisson) . . . (Dispersion parameter

Hi fellow R users, I have a dataset that looks something like this. species class abundance K 1 592 K 2 288 G 1 254 G 2 239 C 2 173 D 2 123 E 3 89 F 2 87 B 2 86 H 2 82 I 1 79 J 2 76 B 1 73 D 3 72 A 2 62 L 2 58 I want to plot a stacked barchart. species is the x-axis, abundance is y-axis, and class will appear as the stacks in different colours. I need the species to be displayed in descending

Buenas tardes, tengo 2 dfs: Dieta de (108x11) y Abund de (591x108). Necesito multiplicar cada columna de la 1ª (108 elementos) por cada fila de la 2ª (108 elementos) y crear una nueva df con las sumas de esas multiplicaciones. He hecho esto, pero no sale y creo que está lejos de estar bien: Res <- matrix(nrow=nrow(Abund),ncol=ncol(Dieta)) Res <- as.data.frame(Res) for(i in

...g curves would then represent the abundance profiles with depth of the larvae. I have tried just switching depth and abundance in the plot formula/coding, but this means that the loess smoother is based on averaging depth values for each abundance, which means that the curves give multiple possible abundances at each depth level. Rather, I would like the loess smooth to still be based on 'averaging' abundance at each depth. Essentially, I would like a mirror image of the plot from this code: ord<-order(Zoo_nocyp$Depth_m, decreasing=TRUE) xyplot(log10Ab[ord]~factor(-1*Depth_m[ord])|StageF[or...

Hi guys, I'm very new to R and have been teaching myself over the past few months - it's a great tool and I'm hoping to use it to analyse my PhD data.As I'm a bit of a newb, I'd really appreciate any feedback and/or guidance with regards to the following questions that relate to generalized linearmixed modelling (or, at least, I think they do!)(if there is a 'better',

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...", "site3", "site4") ##### > abund2 spA spB spC spD spa spF spG site1 150 150 150 150 0 300 300 site2 300 300 0 0 300 300 0 site3 0 0 60 540 0 0 600 site4 360 240 0 0 240 360 0 How can I make a random subsample of 100 individuals from the abundances given for each site? This is probably really easy. Thanks. Bubba -- View this message in context: http://r.789695.n4.nabble.com/Subsampling-out-of-site-abundance-matrix-tp3263148p3263148.html Sent from the R help mailing list archive at Nabble.com.

Dear all, I have run the confint() function according to below and I get the following error message: > confint(stepAIC.glm.spe.var.konn2.abund, level=0.95) Waiting for profiling to be done... Error: missing value where logical needed In addition: Warning message: NaNs produced in: sqrt((fm$deviance - OriginalDeviance)/DispersionParameter) or > confint(stepAIC.glm.spe.var.konn2.abund,

Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I

I am using two mixed effect models. Firstly, what I am trying to do is to compare green roofs abundance with brownfield, green roof with green space abundance, and finally green space with brownfield abundance. I am unsure if I have done the correct model. I have to use a mixed effect model because my data is nested. This is the code and output >

hello list! I'm sorry, I just stumbled over this strange behaviour (at least I am not able to explain the behaviour, therefore I assume it to be a strange behaviour): attach(water) # I know, this is not recommended names(water[3:10]) [1] "temp" "pH" "DO" "BOD" "COD" "no3" "no2" "po4" for (i in

I am trying to understand my population abundance data and am looking into analyses of change point to try and determine, at approximately what point do populations begin to change (either decline or increasing). Can anyone offer suggestions on ways to go about this? I have looked into bcp and strucchange packages but am not completely convinced that these are appropriate for my data. Here is

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 26/0...

Hi, I would like to calculate the RELATIVE euclidean distance. Is there a function in R which does it ? (I calculated the abundance of 94 chemical compounds in secretion of several individuals, and I would like to have the chemical distance between 2 individuals as expressed by the relative euclidean distance. Some compounds are in very low abundance whereas others are in high abundance,

...hers: the name of species and the locality where they were collected. So, the samples are defined as 'each species on each locality'. For every sample I'd like to do multiple imputation (when applicable), test for the presence of outliers, standardize the variables, correct some species abundances, save individual samples to tab delimited text file, and assemble each individual sample (now, without NAs and outliers, corrected abundances, and with the new standardized variables) into a single data set. That task is pretty complex to me, since my programming knowledge is poor (and my free time...