similar to: Correlation between package output

Dear all, I have a question about FD package. I?m trying to calculate functional diversity indices using insect data. My trait data includes dispersal ability (0, 0.5, 1), body size (continuous) and five feeding guilds coded as in percentages (for example; 0,0,0.5,0.5,0) since some of the species can have two different feeding guilds. However, the package only calculates when I run ?calc.Frich=

Hi everyone, I am working with the dbFD function of the FD package, and there's something funny happening with the value of sing.sp in the output. Basically, I have a species-function matrix and a community matrix. One site in particular has 6 species, 4 of which have identical functional coding. I thus expect nbsp = 6 and sing.sp = 2 for this site. However, nbsp = sing.sp = 6. This

Dear useRs, The FD package is intended for ecologists interested in functional diversity (FD). It measures different functional diversity indices from multiple traits (any type of traits). The first version of FD (1.0-0) is now available on CRAN: http://cran.r-project.org/web/packages/FD/ The main functions of FD are: dbFD: Compute different multidimensional FD indices gowdis: Gower

Dear useRs, The FD package is intended for ecologists interested in functional diversity (FD). It measures different functional diversity indices from multiple traits (any type of traits). The first version of FD (1.0-0) is now available on CRAN: http://cran.r-project.org/web/packages/FD/ The main functions of FD are: dbFD: Compute different multidimensional FD indices gowdis: Gower

Hi, I had a core dump while using rc25. Here are the backtraces: Mar 5 00:52:31 rouge dovecot: IMAP(XXXXXX): Maildir /home/XXXXXX/Mail/.Sent sync: UID < next_uid (1 < 2, file = 1173024945.P2421Q0M874108.rouge:2,S) Mar 5 00:52:31 rouge dovecot: IMAP(XXXXXX): file client.c: line 401 (_client_input): assertion failed: (!client->handling_input) Mar 5 00:52:31 rouge dovecot: child 29120

On Apr 27, 2007, at 3:50 PM, David Greene wrote: > The saga continues. > > I've been tracking the interface changes and merging them with > the refactoring work I'm doing. I got as far as building stage3 > of llvm-gcc but the object files from stage2 and stage3 differ: > > > warning: ./cc1-checksum.o differs > warning: ./cc1plus-checksum.o differs > >

The saga continues. I've been tracking the interface changes and merging them with the refactoring work I'm doing. I got as far as building stage3 of llvm-gcc but the object files from stage2 and stage3 differ: warning: ./cc1-checksum.o differs warning: ./cc1plus-checksum.o differs (Are the above two ok?) The list below is clearly bad. I think it's every object file in the

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 configure:17280: result: no configure:17300: checking for mblen configure:17356: gcc -o conftest -O3 -m64 -mtune=native -pipe -Wall -Wpointer-arith -Wuninitialized -Wsign-compare -Wformat-security -Wsizeof-pointer-memaccess -Wno-pointer-sign -Wno-unused-result -fno-strict-aliasing -D_FORTIFY_SOURCE=2 -ftrapv -fno-builtin-memset

Hi, I am trying to combine a long list but I can't work out how to do it, for example: abun<-list(rep(0,5),rep(0,7),rep(0,4),rep(0,10)) nb<-c(5,5,1,8) fill.abun <- function(x, y) { set <- sample(1:length(x), size = y) x[set] <- rlnorm(length(set)) return(x) } abun <- mapply(fill.abun, abun, nb) abun ## I want all the data in one

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

Hi All, I am writing a simulation that examines the effects of species extinctions on ecological communties by sequentially removing individuals of a given species (sometimes using weighted probabilities) and replacing the lost individuals with species identities randomly sampled from the remaining individuals. Thus I use two dataframes. One contains all the individuals and their species

Hello, I am really new to R and it's still a challenge to me. Currently I'm working on my Master's Thesis. My supervisor works with SAS and is not familiar with R at all. I want to run an Anova, a tukey-test and as a result I want to have the tukey-grouping ( something like A - AB - B) I came across the HSD.test in the agricolae-package, but... unfortunately I do not get an output

Hello, Im working on a 50933 point count bird abundance dataset. I've succeeded in calculating a distance matrix for this entire set, but I don't have sufficient memory to convert this to a matrix, as below... abun.dist <- dist(abun.mat[1:50993,1:235) test <- rowMeans(as.matrix(abun.dist)) Error in matrix(0, size, size) : too many elements specified ive been able to run a hclust()

Can anyone point me in the right direction of figuring out what downweight() is doing? I am using vegan to perform CCA on diatom assemblage data. I have a lot of rare species, so I want to reduce the influence of rare species in my CCA. I have read that some authors reduce rare species by only including species with an abundance of at least 1% in at least one sample (other authors use 5% as a