similar to: Rearranging Capture History Data in R

I have data that looks like lake,loglength,logweight 1,2.369215857,1.929418926 1,2.426511261,2.230448921 1,2.434568904,2.298853076 1,2.437750563,2.298853076 1,2.442479769,2.230448921 1,2.445604203,2.356025857 ... 102,2.722633923,3.310268367 102,2.781755375,3.502153893 102,2.836324116,3.683407299 102,2.802773725,3.583312152 102,2.790285164,3.546419267 102,2.806179974,3.599118565

All - Does anyone know if there is a method to calculate a goodness-of-fit statistic for quantile regressions with package quantreg? Specifically, I'm wondering if anyone has implemented the goodness-of-fit process developed by Koenker and Machado (1999) for R? Though I have used package quantreg in the past, I may have overlooked this function, if it is included. Citation: Koenker, R. and

All - Not sure if this is a real programming question, but here goes: I have data that looks like Lake Length Weight 1 158 45 1 179 70 1 200 125 1 202 150 1 206 145 1 209 165 1 210 140 1 215 175 1 216 152 1 220 150 1 221 165 ... where lake goes from 1 - 84 and the number of rows for each lake is variable (but > ~20). I'm trying to do two things: 1) build a simple linear model of the

I am trying to produce frequencies in defined intervals however I can't seem to figure out how to get R to bin my data the way I want it to. I have several thousand lengths of fish that I want to be binned as follows: Ex. Length Bin 209 200 219 210 431 430 727 720 That is, bins with any length equal to or greater than the lower

I'm tyring to fit a relatively simple nls model to some data, but keep coming up against the same error (code follows): Oto=nls(Otolith ~ Linf*(1-exp(-k(AGE-to))), data = ages, start = list(Linf=1000, k=0.1, to=0.1), trace = TRUE) The error message I keep getting is "Error in eval(expr, envir, enclos) : could not find function "k"". I've used this

All - I have a number of rows that I am assigning length classes to via l.class<-with(wae, ifelse((Length>=120)&(Length<130),"125", ifelse((Length>=130)&(Length<140),"135", ifelse((Length>=140)&(Length<150),"145", ifelse((Length>=150)&(Length<160),"155",

I keep running up against the same error when I try to plot a line from a nls model. The data is fisheries length/weight data. Code follows: require(graphics) pow = nls(Weight~alpha*Length^beta, data=wae, start=list(alpha=0.0000001, beta=3.0), trace=TRUE) predict(pow) plot(Weight~Length,

I have data that looks like YC Age Num 82 11 2 83 10 0 84 9 8 85 8 21 86 7 49 87 6 18 88 5 79 89 4 28 90 3 273 91 2 175 with a program mod1=lm(log(Num+1)~YC, data=box44) plot(log(Num+1)~YC, data=box44, pch=19, xlab="Year Class", ylab="Loge Number at age", ylim=c(0,6), xlim=c(91,82)) abline(lm(log(Num+1)~YC), col="blue", lwd=2) summary(mod1) I need to

All - I have data: TL age 388 4 418 4 438 4 428 5 539 10 432 4 444 7 421 4 438 4 419 4 463 6 423 4 ... [truncated] and I'm trying to fit a simple Von Bertalanffy growth curve with program: #Creates a Von Bertalanffy growth model VonB=nls(TL~Linf*(1-exp(-k*(age-t0))), data=box5.4, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) #Scatterplot of the data plot(TL~age, data=box5.4,

Colleagues, I have a routine in package labdsv that calls a FORTRAN subroutine. Recently, I was informed that it sometimes gives different results on a PC and Mac, and that the PC version is clearly wrong. I tested it on linux (because I don't have a PC), and I get the same (incorrect) behavior as the PC. Simply by inserting debug WRITE statements in the FORTRAN I would get different,

All - My question is a bit involved, so bear with me. I have some data that looks like: Lake LL LW 81 2.176091259 1.342422681 81 2.176091259 1.414973348 81 2.176091259 1.447158031 81 2.181843588 1.414973348 81 2.181843588 1.447158031 81 2.184691431 1.462397998 81 2.187520721 1.447158031 81 2.187520721 1.477121255 81 2.187520721 1.505149978 ... [truncated] I'm trying to: 1) fit a simple

I am trying to load a package called Rmark, but when I run library(Rmark) I get the following: > library(RMark) Error in !character.only : invalid argument type Error in library(RMark) : .First.lib failed for 'RMark' When I try to load Rmark from the packages menu, I get: > local({pkg <- select.list(sort(.packages(all.available = TRUE))) + if(nchar(pkg)) library(pkg,

I am interested in building a model with a subset of data from a column. The first 6 lines of my data look like this: QUAD YEAR SITE TREAT HERB TILL PLANT SEED Kweed 1 A4 2002 s 1 N N N N 55.00 2 A10 2002 s 1 N N N N 60.00 3 B2 2002 s 1 N N N N 35.00 4 C2 2002 s 1 N N N N 23.00 5 C9

I have data that looks like Year,Recruit,Spawner,Mtempcv 1958,4532,775,0.24125 1959,22996,2310,0.16319 1960,628,2990,0.46056 1961,879,1400,0.33028 1962,14747,1130,0.22618 1963,13205,790,0.20596 1964,31793,1195,0.19229 1965,10621,981,0.20363 1966,22271,870,0.3452 1967,8736,1104,0.27511 1968,8761,883,0.10884 1969,18885,1421,0.17799 1970,10098,1198,0.2106 1971,3394,760,0.22098 1972,1697,1354,0.39461

Dear R-help folks, I am seeing unexpected behaviour from the function mean with option na.rm =TRUE (which is removing a whole column of a data frame or matrix. example: testcase <- data.frame( x = 1:3, y = rep(NA,3)) mean(testcase[,1], na.rm=TRUE) [1] 2 mean(testcase[,2], na.rm = TRUE) [1] NaN OK, so far that seems sensible. Now I'd like to compute both means at once:

I have data that looks like O.lengthO.age 176 1 179 1 182 1 ... 493 5 494 5 514 5 606 5 462 6 491 6 537 6 553 6 432 7 522 7 625 8 661 8 687 10 704 10 615 12 (truncated) with a simple VonB growth model from within nls(): plot(O.length~O.age, data=OS) Oto = nls(O.length~Linf*(1-exp(-k*(O.age-t0))), data=OS, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) mod <- seq(0, 12)

Hi, I am interested in using the numeric output from the "gradient" attribute of deriv's output in subsequent analyses. But, I have so far been unable to determine how to do so. I will use the example from the deriv help to illustrate. > ## function with defaulted arguments: > (fx <- deriv(y ~ b0 + b1 * 2^(-x/th), c("b0", "b1", "th"),

I am trying to write a function that will solve a simple system of nonlinear equations for the parameters that describe the beta distribution (a,b) given the mean and variance. mean = a/(a+b) variance = (a*b)/(((a+b)^2) * (a+b+1)) Any help as to where to start would be welcome. -- Scott Story Graduate Student MSU Ecology Department 319 Lewis Hall Bozeman, Mt 59717 406.994.2670 sstory at

Any Rails Developers in Montana? Especially Helena or Bozeman? I don''t expect there''s enough of us to form a user group, but it might be nice to talk shop ''offline'' every once and a while. Eric (in Helena) --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Ruby on Rails:

Dear R-help-ers (Currently running Version 0.65.1 Release (October 07, 1999) on Solaris 2.6) My problem has to do with updates of the R language. When I install a new version, I would like to just change one directive, or a soft link to the current doc/html/ directory, to update a bookmark I have pointing to the current R doumentation directory. I've tried building a soft link: