similar to: 3d plotting with cloud and wireframe

Hi, I'm trying to run a basic simulation and sensitivity test by running an equation with two variables and then plotting the results against each of the vectors. R is running the vectors like this : 0 with 0, 1 with 1, etc. I would like it to run them like 0 for 1:100, 1 for 1:100, and then the reverse (so 100^2*100@ iterations. How do I get it to do that? Here's what I have so far:

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

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

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()

Dear people of the help list I am drying to analyze my data using the 'lmer' function and I keep having problems. This is the model: > fm1<-lmer(dbh~spec+scheme+(1|Plot),data=d, REML=FALSE). I analyse tree size (dbh) of 3 different species (spec) and 3 planting schemes (scheme). I have 5 plots, which I hope to model as a random factor. (However, the subsequent output is based on

Hello, I have a problem with my script. I don'y know how to apply subtitles. I have 9 charts per page (for combination of 3 blocks and 3 treatments). I want to have subtitles for this interaction (e.g. Block A Trt 1, Block A Trt 2, ...) MBE$bt<- interaction(MBE$Block,MBE$trt) par(mfrow=c(3,3)) for(i in unique(MBE$bt)){ ss <- MBE$bt==i plot(MBE$Year[ss], MBE$DBH[ss])

R gurus, I'm working on data analysis for a small project. My response variable is total vines per tree (median = 0, mean = 1.65, min = 0, max = 24). My predictors are two categorical variables (four sites and four species) and one continuous (tree diameter at breast height (DBH)). The main question I'm attempting to answer is whether or not the species identity of a tree has

Hello, I have a big table with 3 columns and 103918 rows. This is the example,            time             species                 dbh 5 1 4.9377297 575 1 11.64127213 575 1 109.8182438 575 1 8.029809521 5 1 24.32501874 575 1 4.895992119 575 1 11.40567637 575 1 2.795090562 575 1 21.79281837 575 1 52.57476174 575 1 27.7290919 575 1 3.23262083 575 2 19.30612651 575 1

Dear All, I seem to have stumbled across an AGI problem; I have written an AGI Script (bottom of this email); The script does the following; Makes a CDR entry when called Records the call Updates the CDR Finds a corresponding DNIS from the SMDR table (captured via a serial port logger) Matches up the record and updates the CDR. The script works perfectly in my test lab and has been doing so

hi,guys- I have a mysql database which stores host informations,so I wrote a function to get some values. - Here is the function rb(this function should return the type I defined in the database): #hosttype.rb require "mysql" module Puppet::Parser::Functions newfunction(:hosttype, :type => :rvalue, :doc => "Gets host type from db.") do |args|

*Dear All:* I need your help on following points. 1. Can I connect Ruby with MySQL in XAMPP server? 2. Could someone tell me that how to connect MySQL with Ruby? I have XAMPP server installed and want to connect with ruby. I am using Ruby1.8.7. I tried following code: require ''rubygems'' require ''mysql'' begin # connect to the MySQL server

Dear all, As part of a larger function, I am randomly removing rows from a data frame. The number of removed rows is determmined by a Poisson distribution with a low mean. Sometimes, the random number is 0, and that's when the problem starts: My data frame: > temp occ x y dbh age 801 0 2977.196 3090.225 6 36.0 802 0 2951.892 3083.769 8 40.6 803 0 2919.111

Dear all, I've used glm(family=binomial(link="logit")) several times, but now I think that a log link is more appropriate. I want to fit a model for probability of tree fall (TF)), with tree diameter (dbh) and soil moisure (soil) as predictors. A large number of trees have been checked every second year whether they stand up (0) or have fallen (1). I assume that the tree fall

Hi there, I trying to solve this problem for the whole day not going anywhere, so I really hope maybe somebody can help me in this community... I've got an object coefficient2 which I want to plot in differerent ways, with colors and labels added to the points, but somehow there seems to be a problem if a value is NA within the independent variable, resulting in false labels and false colors

Here''s some happy-fun Perl to make your storeconfig/virtual resources day better. I probably should have written this in Ruby, but perl comes naturally :) #!/usr/bin/perl # # Perl DBI to remove all related entries from Puppet''s storeconfigs database. # Use when a host is removed from the Puppet network forcibly # Alternatives: run puppet on host to be removed with a blank

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

I try to change something in ASTCC, but I am now totally blind, .... I hang on one line now. I changed: vpbx:/var/lib/asterisk/agi-bin # diff astcc-original.agi astcc.agi 22c22 < # exten => _00XXXXXXXXX,1,DeadAGI(astcc.agi,${CALLERIDNUM},${EXTEN}) --- > # exten => _00XXXXXXXXX,1,DeadAGI(astcc.agi,${CALLERIDNUM},${TARIFF},${EXTEN}) 35c35 < # exten =>