similar to: Scatter plot from tapply output, labels of data

Hello, Beginner, sorry if this is wasting anyone's time, but have been working on this for a couple of days now, think it should have take a few hours! The Problem: Error in Summary.factor(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, : max not meaningful for factors I have tried to re-arrange and check formula. I am working in SIAR, and cannot get model1 to run because of the error

Hi there, I am trying to run an MCMC on stable isotope data from certain organisms to determine their dietary habits in the package SIAR. I have prepared my data according to Inger, R., Jackson, A., Parnell, A., Bearhop, S. : SIAR V4 (Stable Isotope Analysis in R) an Ecologist's Guide (also better known as 'SIAR for dummies'), which is as follows: - consumer data table (columns

Help! model1 <- siarmcmcdirichletv4(data, source, tef, concdep=0, 500000, 50000) Error in matrix(1, ncol = (numsources + numiso) * numgroups, nrow = (siardata$iterations - : invalid 'ncol' value (too large or NA) In addition: Warning message: In Ops.ordered((numsources + numiso), numgroups) : '*' is not meaningful for ordered factors Previous message, but more problems:

I'm absolutely not brilliant with R yet and working with package SIAR. 1) SIAR reads the first column of a table.txt as "int" instead of "num". Who can help? 2) I therefore made tables with a data.frame() > that seems to work. But at the end of the loading proces of the SIARmodel, I get a warning screen with "Session Aborted". Everything crashes and I can start

Dear all, maybe somebody can provide some help for this problem: Example: I've got the following dataframe "data": grid.id<-c(1:4) lat<-c(10,12,13,15) species1<-c(0,0,0,1) species2<-c(1,1,0,0) species3<-c(1,1,1,1) data<-data.frame(cbind(grid.id,lat,species1,species2,species3)) How can I, out of "data" make a new dataframe, where the cells of value

Hello. Does anyone know of an existing function that takes a list in the form of: Plot1 Species1 Abundance1 Plot1 Species2 Abundance2 Plot2 Species1 Abundance1 Plot2 Species3 Abundance3 . . . PlotN SpeciesN AbundanceN and translates into a matrix in the form of Species1 Species2.... SpeciesN Plot1 Abundance1 Abundance2... AbundanceN Plot2 Abundance1

Hi, Dummy data script and scripts are attached below. I would like to change the plot to look like this:

Hi, I'm needing some help finding a function to read a large text file into an array in R. The data are essentially presence / absence / na data for many species and come as a grid with each species name (after two spaces) at the beginning of the matrix defining the map for that species. An excerpt could therefore be: SPECIES1 999001099 900110109 011101000 901100101 110100019 901110019

I was just thinking of a way to present data and if it is possible in R. I have a data frame that looks as follows (this is just mockup data). df location,"species1","species2","species3","species4","species5" "loc1",0.44,0.28,0.37,-0.24,0.41 "loc2",0.54,0.62,0.34,0.52,0.71 "loc3",-0.33,0.75,-0.34,0.48,0.61 location

Dear all, I have 4 sites and want to determine how different they are from each other. For this I have decided to use R though it seems a bit daunting to learn. I have read data in from a CSV the structure is : Species1 Species2 Species3 Site1 4 4 7 Site2 3 1 0 Site3 0 99 6 Site4 75 3 33 There are many more species than shown above this is just an example. Here are the

Dear R users, I am using lmer combined with AIC model selection and averaging (in the MuMIn package) to try and assess how isotope values (which indicate diet) vary within a population of animals. I have multiple measures from individuals (variable 'Tattoo') and multiple individuals within social groups within 4 locations (A, B, C ,D) crucially I am interested if there are

Hello dear subscribed Users, this is my first post, so please forgive me for any inconveniences. The following problem: I have a dataframe containing a factor column. For each column i would like to compare means as parted by the factor. Using the normal t.test function I have already achieved my goal. But i think, that for my original data, a permutational t.test would be better suited.

Hi, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

The code I'm using is shown below. I would like to have a larger median at the top of the plot so that I can show the entirity of "title_text". Several times I tried messing with "par(mar", but that seemed to make matters worse. By any chance can anyone provide any insight as to the best way to increase the top/upper/northern margin, so the entirity of the title is

Dear listers, I have a piece of code which performs an ANOVA type of analysis on 2D GC data. The code is shown below: # ANOVA 2D GC analysis # maxc <- number of samples # nreps <- number of samples maxc <- 2 nreps <- 4 sscl <- NULL cmean <- NULL # # Initial stat. variable # dftot <- nrow(mat)-1 dfcl <- maxc - 1 dferr <- dftot - dfcl totmean

I collected eggs laid by Springtails everyday over 28 days after swich to isotopically enriched diet. The eggs were pooled at day 7, 14, and 28 (+ day 0 = initial value) and analyzed for isotopes. After the diet switch the isotopic values of the adults and eggs change towards those of the new diet. Here are the d13C values (y) of the eggs: x y 0 -22.2 0 -22.2 0 -22.2 0 -22.0 7

I wantto run sequential ANOVAs (i.e. type I sums of squares), and trying to getresults including ANOVA tables and associated coefficients for predictive variables(I am using the R 3.4.2 version). I think ANOVA tables look right, but believecoefficients are wrong. Specifically, it looks like that the coefficients arefrom ANOVA with ?marginal? (type III sums of squares). I have tried both lme

Dear List, I often have to merge two or more data frames containing unique row names but with some columns (names) common to the two data frames and some columns not common. This toy example will explain the kind of setup I am talking about: mat1 <- as.data.frame(matrix(rnorm(20), nrow = 5)) mat2 <- as.data.frame(matrix(rnorm(20), nrow = 4)) rownames(mat1) <- paste("site",

I am attempting to join several dataframes that summarize sampling effort for different samples into one large data.frame/table. I have looked at the merge command, but have not been clever enough to figure out how to get it to do what I want. A simplified example of what I am trying to do: The dataframes I have look like this (they were generated using the table command) species1.effort

Dear list members, I have a data.frame so shaped: Sector Quadrants Plot Sic Time Species1 Species2 Species3 .. Species-n 1 1 1 1 5 0 0 1 . 0 2 1 1 1 12 1 1 1 . 0 3 1 1 1 34 0 1 0 . 0 4 1 1 1 23 1 1 0 . 0 5 2 1 1 22 1 1 1 . 1 6 2 1 1 10 1 1 1 . 1 7 2 1 1 2 1 0 0 . 0 8 2 1 1 2 0 0 1 . 0 9 3 1 1 12 0 0 0 . 1 . . . . . . . . . .