similar to: Predicting from an nls model

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'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

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 - 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,

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

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

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 - 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 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

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)

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

What code can i use to convert a table like this: Tag# Date 1 1 2 1 3 1 4 1 2 2 4 2 1 3 2 3 4 4 Into one like this: Tag 1 2 3 4 #Date header 1 1 0 0 1 2 1 1 1 0 3 1 0 0 0 4 1 1 0 1 Thanks, Ben Cox Research Assistant (M.S.) Montana Cooperative

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,

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

All - I think I'm being dense, but for the life of me, I can't figure out why I get error message with the code below. I have data that looks like param level perc.surv asin.tran DO 3 0.6864407 0.9764544 DO 3 0.1250000 0.3613671 DO 3 0.8738739 1.2077299 DO 4 0.4615385 0.7468986 DO 4 0.5691057 0.8547258 DO 4 0.8504673 1.1737517 DO 6 0.5494505 0.8349297 DO

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:

All - I have data that looks like psd Species Lake Length Weight St.weight Wr Wr.1 vol 432 substock SMB Clear 150 41.00 0.01 95.12438 95.10118 0.0105 433 substock SMB Clear 152 39.00 0.01 86.72916 86.70692 0.0105 434 substock SMB Clear 152 40.00 3.11 88.95298 82.03689 3.2655 435 substock SMB Clear

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:

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 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,