similar to: simulation for equation with two variables

Hi, I'm trying to plot an equation in two variables to get a feel for sensitivity to its parameters. I've run expand.grid to get made-up vectors of the combinations of the two independent variables, and am trying to plot the output of the dependent, M, against both the dependent in a 3d space. t <- 0:100 DBH <- 10:100 TxDBH<-expand.grid(t,DBH) time<-TxDBH[,1]

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,

Sub: using glmer to fit a mixed-effects model with gamma-distributed response variable Hello, I'm currently trying to fit a mixed effects model , i.e.: > burnedmodel1.2<-glmer(gpost.f.crwn.length~lg.shigo.av+dbh+leaf.area+ bark.thick.bh+ht.any+ht.alive+(1|site/transect/plot), family=gaussian, na.action=na.omit, data=rws30.BL) If I run this code, I get the error below: Error:

Hi all, I'm trying to fit models for data with three levels of nested random effects: site/transect/plot. For example, modelincrBS<-glmer(l.ru.ba.incr~shigo.av+pre.f.crwn.length+bark.thick.bh+Date+slope.pos.num+dens.T+dbh+leaf.area+can.pos.num+(1|site/transect/plot), data=rws30.UL, family=gaussian, na.action=na.omit) but I get the following error: Error: length(f1) == length(f2) is not

Dear all, Last autumn there was some discussion on the list of the warning Warning message: fitted probabilities numerically 0 or 1 occurred in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y, when fitting binomial GLMs with many 0 and few 1. Parts of replies: "You should be able to tell which coefficients are infinite -- the coefficients and their standard errors will

Dear r helpers; I'm interested in reading from and writing to large .xlsx files fairly regularly. (Why, the naysayers may ask - and the answer is basically colleagues and clients who prefer that format). I've tried out the XLConnect and xlsx libraries, but the java implementation they use just takes too much RAM for the files I'm working with. gdata leverages perl and works really

Dear R users, I'm starting to use 'apply' functions rather than for loops in R, and sometimes the output is a bit different than what I want. In this case, the command was tapply(myvector,myindex,cumsum) And the output was something like this: $`SNRL1 Core 120` [1] 2.8546 4.0778 5.2983 6.3863 7.5141 8.5498 9.5839 10.6933 $`SNRL1 Core 230` [1] 7.6810 8.7648 9.8382

Hello, I'm just trying to wrap my head around the syntax for creating loops, functions in R. I have an array of values from a .csv. Looks something like header<-c(species,coefficient1, exponent1, coefficient2, exponent2, constant) with a species name for the first column, and values for coefficient1, exponent1, coefficient2, exponent2, constant for each species. The values are

Apologies for continuing to ask about this but . . in my quest to fit a gamma GLMM model to my data (see partial copy of thread below), I'm exploring using hglm today. The question of the day has to do with the errors I'm currently getting from the hglm package. Can hglm handle a model with nested random effects? I don't see an example of one of those in the package documentation. If

Dear R help; I'll preface this by saying that the example I've provided below is pretty long, turgid, and otherwise a deep dive into a series of functions I wrote for a simulation study. It is, however, reproducible and self-contained. I'm trying to do my first simulation study that's quite big, and so I'll say that the output of this simulation as I'd like it to be is

I have some elements in a vector with extraneous information (e.g. file name and sample IDs) that I'd like to strip from every element. For example, I would like "SPI1.S1.str1.P3.sample.tif" "SPI1.S1.STR2.P1.sample.tif" to read "SPI1.S1.str1.P3" "SPI1.S1.STR2.P1". Will someone help me with the syntax in gsub? It needs to be something like

Hello, I'm trying to create a vector of r^2 values for using a function which I will run in a "for" loop. Example: per<-rnorm(100,.5,.2)^2 x<-rnorm(100,10,5) y<-rnorm(100,20,5) fr<-data.frame(x,y,per) test<-rep(0,9) plotter<-function(i){ temp.i<-fr[fr$per <=(i*.10),] with(temp.i, plot(x, y, main=(i*.10),)) mod<-lm(y~x-1,data=temp.i)

Addendum: I tried a gamma fit in glmmPQL and got the same errors. *Ben Caldwell* PhD Candidate University of California, Berkeley On Tue, May 17, 2011 at 3:51 PM, Benjamin Caldwell <btcaldwell@berkeley.edu>wrote: > Hello > After seeing this ( > https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005213.html) email > I thought I would check the issue with a gamma family

I ran into a problem with "subset" while working at home that I am not sure is a bug or not. I defined a custom function to take a data frame of tree positions, sizes, and types (containing the columns TRT, COMP, PLOT, X, Y, DBH and CON) and wanted to make a stem map of the plot using different symbols and colors to represent the different types of tree stems. I copied a bit of the

Hello all, * * I'm having some difficulty, and I think the problem is with how I'm using append() nested inside a for loop. The data are: y,x 237537.61,873 5007.148438,227 17705.77306,400 12396.64369,427 228703.4021,1173 350181.9752,1538 59967.79376,630 140322.7774,710 42650.07251,630 5382.858702,264 34405.82429,637 92261.34614,980 144927.1713,1094 362998.7355,1420 203313.6442,1070

Hey, So I have a scatter plot and I am trying to plot a curve to fit the data based on a Holling Type III functional response. My function is this: nll2<-function(a,b) { conefun<-(a*DBH^2)/(b^2+DBH^2) nlls2<-dnbinom(x=cones ,size=DBH, mu=conefun,log=TRUE) -sum(nlls) } and my plot is this: plot (DBH,cones) DBH is on the x-axis and cones is on the y-axis. How do I get the curve

Now I have the forest plot data with x, y locations, and I measured the DBH for every indivicuals. The data looks like that: x=runif(100,0,100) y=runif(100,0,100) dbh=runif(100,1,100) rdata=data.frame(x,y,dbh) > rdata[1:5,] x y dbh 1 99.5354145 1.412844 34.10112 2 0.8259361 87.737036 39.12914 3 6.5678613 65.699032 22.55990 4 67.2987881 72.053877 45.83978 5 2.2491372

I've been trying to figure out how to prevent a column that is the result of an aggregate function call so that I can use it in further calculations. For example, I would like to aggregate the expf for the data.frame by sp (character) and dbh (double d=rounded to integer) using the command: > st2 <- aggregate( ntrs$expf, by=list(sp=ntrs$sp,dbh=ntrs$dbh), sum ) > st2$expf <- st2$x

Dear R-help, Here's a simple example of nonlinear curve fitting where nls seems to get the answer wrong on a very simple exponential fit (my R version 2.7.2). Look at this code below for a very basic curve fit using nls to fit to (a) a logarithmic and (b) an exponential curve. I did the fits using self-start functions and I compared the results with a more simple fit using a straight lm()

I want to do "moran's I test" in R language. I try to use "gearymoran" in Package "ade4","moran" in Package "spdep", and Moran.I in Package "ape". But I do not know how to do it because data format is different. My data: x y dbh 111.03 10.7 7 118.11 0.28 1.2 165.36 0.36 8.4