similar to: Class attributes

Dear R-list, Seems simple but have tried multiple approaches, no luck. I have a list of column names:

Problem: I have a data frame with 1s and 0s denoting presence/absence of species (columns) for particular plot measurements (rows). What I want to do is make a new column whose entries for each row is a list of the column names in which a species is present (ie. for row one its entry might read: "sp1","sp2", etc.). I've tried various functions etc. but can't seem to

Dear R list, I've been attempting to interpret the results from a three-way ANOVA. I think I understand contrasts and the R defaults for these (treatment contrasts). My question is: what is the intercept in this test? As far as I can tell, its NOT the expected value of a point that belongs to the first level of all three explanatory factors (because there is only one point that satisfies these

Hi, I am trying to write a for loop with if else statements to calculate biomass density estimates for different types of sampling gear. My code is: bmd=for (i in 1:length(Gear)){ if (Gear==20) {bioden=Biomass/141} else {if (Gear==23) {bioden=Biomass/68}} else {if (Gear==160) {bioden=Biomass/4120}} else {if (Gear==170) {bioden=Biomass/2210}} else {if (Gear==300)

Hi there, I have a data frame as listed below: > Ca.P.Biomass.A P Biomass 1 334.5567 0.2870000 2 737.5400 0.5713333 3 894.5300 0.6393333 4 782.3800 0.5836667 5 857.5900 0.6003333 6 829.2700 0.5883333 I have fit the data using logistic, Michaelis?Menten, and linear model, they all give significance. > fm1 <- nls(Biomass~SSlogis(P, phi1, phi2, phi3), data=Ca.P.Biomass.A)

Dear all, I have a problem with interactions in lmer. I have 2 factors (garden and gebiet) which interact, plus one other variable (home), dataframe arr. When I put: / lmer (biomass ~ home + garden:gebiet + ( 1|Block), data = arr)/ it writes: /Error in lme4::lFormula(formula = biomass ~ home + garden:gebiet + (1 | : rank of X = 28 < ncol(X) = 30/ In the lmer help I found out that if not

Evening folks, I'm trying to print a series of graphs to .jpeg using a variable as the title, but run into the difficultly that I can't find a way to append the file extension to the .jpeg (in this case extensionless!) files. Example: ---- species.name="CussoniaHolstii" dia<-10:100 biomass = -21.4863 + 0.5797 * (dia ^ 2) biomass jpeg(species.name) plot (biomass,

Hi R users, I need your help to write a code in r that does the following calculation from three different datasets; ac = 1/sum (NPP from date 1 to date 2, dataset=1) * (biomass at date 2 -biomass at date 1, dataset = 2) + (littfall at date 2, dataset=3). all the dates are in yr-month-day format. Which library or function Should I use to tell R do these calculations of these variables at

I was surprised to find that just changing the base level of a factor variable changed the number of significant coefficients in the solution. I was surprised at this and want to know how I should choose the order of the factors, if the order affects the result. Here is the small example. It is taken from 'The R Book', Crawley p. 365. The data is at

Dear R users, Does anyone knows how to run a glmm with one fixed factor and 2 random numeric variables (indices)? Is there any way to force in the model a separate interaction of those random variables with the fixed one? I hope you can help me. #eg. Reserve <- rep(c("In","Out"), 100) fReserve <- factor(Reserve) DivBoulders <- rep

Dear gracious R community, I would like to produce charts of phytoplankton biomass changes through time. Each species has a line, and the biomass varies in mirror form along the line for each species along the X time axis. Here is an example of what I'd like to do: http://www.er.uqam.ca/nobel/r30240/Succession.jpg Any suggestions? Thanks David Bird UQAM, Montreal

Hi all This is probably a simple problem but somehow I am having much trouble with finding a solution, so I seek your help! I have a data-set with continuous response variables. The explanatory variably is 4xpH treatments (so 8.08, 7.94, 7.81 and 7.71) so also continuous and not technically factorial. However I have decided to do Anova's (as well as regression) to explore the effect of

Hi, I have a situation here. I try this update: mmaa <- update(mma,biomass~qvartemp) but I have this message: Error in eval(expr, envir, enclos) : object "qvartemp" not found but this object exist: [1] "cont" "i" "levelsord" "mma" "qvar" "qvarmma" [7] "qvartemp" "test"

Hello! I urgently need to know if it is possible (and if so, how to do) to get the "Estimatet marginal means" from an ANOVA. Or explained more coplicated: It's about plants sewn in 2 densities & 2 patterns. The Variable is biomass and I also use a Covariate. There are highly significant differences between density & pattern but I don't know which of the 2 densities

Hello, I'm working on a problem using nested for-loops and I don't know if it's a problem with the order of the loops or something within the loop so any help with the problem would be appreciated. To briefly set up the problem. I have 259 trees (from 11 different species, of unequal count for each species) of which I am trying to predict biomass. For each tree species I have 10000

Dear list members, I'd like to perform a glm analysis with a hierarchically nested design. In particular, I have one fixed factor ("Land Use Classes") with three levels and a random factor ("quadrat") nested within Land Use Classes with different levels per classes (class artificial = 1 quadrat; class crops = 67 quadrats; and class seminatural = 30 quadrats). I have four

Hi Ahmed, Your problem appears trivial as you have already specified the form of the calculation. Learn how to "extract" specified elements from a data structure: # first value sum(dataset1$NPP[dataset1$date >= date1 & dataset1$date <= date2]) # second value dataset2$biomass[dataset2$date == date2] - dataset2$biomass[dataset2$date == date1] # third value

Sorry for the confusion, here is the edited question. The data= Stand_Height (attached) is recorded from 12/1/2009 to 12/31/2015 (25 observations) and the other dataset (leafbiom) is recorded from 10/7/2009 to 12/29/2016 (daily observations). I want to use the 25 observations of stand height to predict the daily stand height from 10/7/2009 to 12/29/2016. The daily stand height will be multiplied

Hi all, i'm fairly new to R and its graphing, but having unsuccessfully 'googled' and checked this forum to find answer to my problem, i'm posting my question here. I'm trying to plot stacked barplot. I have simple data that looks like this: bg ag 0.41 2.81 0.37 2.91 0.31 2.06 0.32 2.39 every row indicates a factor (1,2,3,4, see below in names.arg). Now when i plot

Hi everyone, I am trying to analyse my data from a small plant experiment (for a meeting tomorrow afternoon) and am a beginner to R so I apologise if this is a very basic question. I carried out a plant experiment examining plant interactions between two species (A and B) under different watering treatments. I had: - 7 watering treatments (7 different watering frequencies labelled 1-7) - 3