search for: bertalanffy

..., 2009L, 2011L, 2008L, 2012L, 2010L, 2008L)), .Names = c("Length", "Age", "Cohort", "Year"), class = "data.frame", row.names = c(NA, -42L)) Code: BLG=read.csv("BLGa.csv", header=T) attach(BLG) names(BLG) dput(BLG,"") $ Von Bertalanffy Growth Model$ source("http://www.rforge.net/NCStats/InstallNCStats.R") source("http://www.rforge.net/FSA/InstallFSA.R") library(FSA) library(NCStats) library(nlstools) # provide starting values svCom <- list(Linf=199.8132, K=0.5631745, t0=-1.960147) svCom <- vbStarts(Le...

...Now, the problem that I am now stuck with is incorporating a growth model into the three new datasets to estimate growth parameters. Since there are now three new datasets I want to get three new estimates of the growth parameters, essentially one from each new dataset. I am using the von Bertalanffy growth model. Here is my code: par<-list(Linf=700, K=0.20, to=-0.1) #these are the starting values for parameters vb<-nls(Length~Linf*(1-exp(-K*(Age-to))), start=par, data=???) #this is the growth model with the parameters estimated with non linear least squares (nls) I t...

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, pch=19, xlab="Age (yr)", ylab="Total length (mm)") #In...

..., Cynthia M. Jones wrote a paper (Fitting growth curves to retrospective size-at-age data, Fisheries Research 46(2000):123-129; abstract at http://www.elsevier.nl/gej-ng/10/19/44/70/24/37/abstract.html)where the SAS procedure MIXED, Macro NLINMIX (Littell et. al., 1996)was used to estimate the von Bertalanffy growth function parameters assuming that data from the same fish are repeated-measures with autoregressive correlation structure and fitting with a nonlinear repeated-measures model. Is there any similar procedure that I can use in R? Thanks, Antonio Olinto -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

...utlined on p 244 of MASS (or at least I'm trying to). Thus, I'm using mean data with heteroscedasticity so I'm weighting by n/ variance, where the variance is well known from a large data set. This weighting factor is available as the variable 'novervar'. The function is a von Bertalanffy curve of the form weight~(a*(1-exp(-b*(age-c))))^3. Thus I'm entering the command in the form: solb1wvb<-nls(~sqrt(novervar)*(weight-(a*(1-exp(-b*(age-c))))^3),data=solb1.na.rm,start=list(a=0.85,b=0.45,c=0.48)) Can anyone suggest what I'm doing wrong? I seem to be folowing the instru...

I am trying to compare Vbert growth curves from several years of fish data. I am following the code provided by: http://www.ncfaculty.net/dogle/fishR/gnrlex/VonBertalanffy/VonBertalanffy.pdf. Specifically the section on VBGM Comparisons between groups. ? This code is pretty cut and dry. I am able to run it perfectly with the "fake" data that is provided. But when I run it with my own data I get stuck with this line: fitGen <- nls(vbGen,data=LMB,start=s...

Dear colleagues, Von Bertalanffy model is commonly adjust to data on fish length (TL) and age (AGE) TL= Linf*(1-exp(-K*(AGE-t0)). Linf, K and t0 are parameters of the model. One main goal of the growth study is the comparison of growth parameter estimates between sexes of the same species, or estimates from different populations....

I am looking into fitting a so-called double von Bertalanffy function to fish length-at-age data. Attempting to simplify the situation, the model looks like this ... Y ~ f(X; a,b,c) if x < Z Y ~ g(X; a,d,e) if x >= Z where * f and g are non-linear functions (the "traditional" "single" von Bertalanffy growth function), * Y (leng...

Hi there, I'm a PhD student investigating growth patterns in fish. I've been using the minpack.lm package to fit extended von Bertalanffy growth models that include explanatory covariates (temperature and density). I found the nls.lm comand a powerful tool to fit models with a lot of parameters. However, in order to select the best model over the possible candidates (without covariates, with both covariates, or with only one of them)...

...mes and I want to get the 300 sets of parameter estimates and plot them in Excel. Here is my code: par<-list(Linf=700, K=0.3, to=-0.1) #starting values for parameter estimates vb<-nls(length~Linf*(1-exp(-K*(age-to))), start=par, data=small) #von Bertalanffy growth mode boo<- nlsBoot(vb, niter=300) #This bootstraps my data 300 times and applies the growth model I can get R to plot the 300 parameter estimates if I do the following function: plot(boo) However, I have tried different print function options...

R-help, I'm trying to estimate some parameters using the Maximum Likehood method. The model describes fish growth using a sigmoidal-type of curve: fn_w <- function(params) { Winf <- params[1] k <- params[2] t0 <- params[3] b <- params[4] sigma <- params[5] what <- Winf * (1-exp(- k *(tt - t0)))^b

I have a fisheries Ricker stock-recruitment non-linear model which I am trying to code up in R (after failing in MATLAB). There are two fixed parameters and a random environmental effect that is linked to a first order lagged correlation fixed parameter. Are there any examples of fitting this model I could follow? Cheers Norm Good Fisheries Biologist (Mathematician) Southern Fisheries Centre

Hi In a dataset I have length and age for cod. The age, however, is ony given for 40-100% of the fish. What I need to do is to fill inn the NAs in a correct way, so that age has a value for each length. This is to be done for each sample seperately (there are 324 samples), meaning the NAs for sampleno 1 shall be calculated from the known values from sampleno 1. As for example length 55 cm

Hi, I have great problems with my work in R. I look for to model the growth of fish. I have "Longitudinal data", a serie of repeated measures for each individual. Using the corresponding packages "nlme" in R. I treat to fit to the data different growth functions, wich were entered by me. Unfortunately for no it was arrived at the convergence, several error messages appeared. I

Hello, I am attempting to fit a non-linear model (Von Bertalanffy growth model) to fish length-at-age data with the purpose of determining if any of the three parameters differ between male and female fish. I believe that I can successfully accomplish this goal assuming an additive error structure (illustrated in section 1 below). My trouble begins when I attem...

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti= age i, and t0= age of length 0. I'd solved the problem using nls but the points are not independent. The length-at-age data are correlated for each fish because I'm f...

CRAN (and crantastic) updates this week New packages ------------ * EffectStars (1.0) Maintainer: Unknown Author(s): Gunther Schauberger License: GPL-2 http://crantastic.org/packages/EffectStars The package provides functions to visualize regression models with categorical response. The effects of the covariates are plotted with star plots in order to allow for an optical