search for: minpack

I am trying to install minpack.lm on R 3.3.3 (Debian version) on a Chromebook. But I get this error: ``` > install.packages("minpack.lm") Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? (as ?lib? is unspecified) trying URL 'https://cran.rstudio.com/src/contrib/minpack.lm_1.2-1.tar...

...e problem must be with the installation step: I should tell the compiler to look for libisl19 instead of libisl.so.19... On Tue, Jul 14, 2020 at 12:54 PM Dirk Eddelbuettel <edd at debian.org> wrote: > > > On 14 July 2020 at 12:26, Luigi Marongiu wrote: > | I am trying to install minpack.lm on R 3.3.3 (Debian version) on a > | Chromebook. But I get this error: > | ``` > | > install.packages("minpack.lm") > | Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? > | (as ?lib? is unspecified) > | trying URL 'https://cran.rs...

...should tell the > | compiler to look for libisl19 instead of libisl.so.19... > | > | On Tue, Jul 14, 2020 at 12:54 PM Dirk Eddelbuettel <edd at debian.org> wrote: > | > > | > > | > On 14 July 2020 at 12:26, Luigi Marongiu wrote: > | > | I am trying to install minpack.lm on R 3.3.3 (Debian version) on a > | > | Chromebook. But I get this error: > | > | ``` > | > | > install.packages("minpack.lm") > | > | Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? > | > | (as ?lib? is unspecified) &gt...

The package minpack.lm allows nonlinear regression problems to be addressed with a modification of the Levenberg-Marquardt algorithm based on the implementation of 'lmder' and 'lmdif' in MINPACK. Version 1.0-8 of the package is now available on CRAN. Changes in version 1.0-8 include: o possibilit...

The package minpack.lm allows nonlinear regression problems to be addressed with a modification of the Levenberg-Marquardt algorithm based on the implementation of 'lmder' and 'lmdif' in MINPACK. Version 1.0-8 of the package is now available on CRAN. Changes in version 1.0-8 include: o possibilit...

On 14 July 2020 at 12:26, Luigi Marongiu wrote: | I am trying to install minpack.lm on R 3.3.3 (Debian version) on a | Chromebook. But I get this error: | ``` | > install.packages("minpack.lm") | Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? | (as ?lib? is unspecified) | trying URL 'https://cran.rstudio.com/src/contrib/minpack....

...be with the installation step: I should tell the | compiler to look for libisl19 instead of libisl.so.19... | | On Tue, Jul 14, 2020 at 12:54 PM Dirk Eddelbuettel <edd at debian.org> wrote: | > | > | > On 14 July 2020 at 12:26, Luigi Marongiu wrote: | > | I am trying to install minpack.lm on R 3.3.3 (Debian version) on a | > | Chromebook. But I get this error: | > | ``` | > | > install.packages("minpack.lm") | > | Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? | > | (as ?lib? is unspecified) | > | trying URL 'htt...

Hello guys. I've built and uploaded to CRAN an R interface to MINPACK Fortran library, which solves non-linear least squares problem by modification of the Levenberg-Marquardt algorithm. The package includes one R function, which passes all the necessary control parameters to the appropriate Fortran functions. The package location is http://cran.r-project.org/...

Hello guys. I've built and uploaded to CRAN an R interface to MINPACK Fortran library, which solves non-linear least squares problem by modification of the Levenberg-Marquardt algorithm. The package includes one R function, which passes all the necessary control parameters to the appropriate Fortran functions. The package location is http://cran.r-project.org/...

Dear All, In the past I have often used minpack (http://bit.ly/zXVls3) relying on the Levenberg-Marquardt algorithm to perform non-linear fittings. However, I have always dealt with a function of a single variable. Is there any difference if the function depends on two variables? To fix the ideas, please consider the function f(R,N)=(a/(log(2*N...

...re crossprod() of the Jacobian of the model function cannot be inverted and fails with the message "Singular gradient". I wish that R could have a more reliable built-in nonlinear least squares solver. (I could also be holding it wrong.) Meanwhile, we have excellent CRAN packages nlsr and minpack.lm: minpack.lm::nlsLM( pHobs ~ pHm(SID, pK1, pK2, pK3), data.frame(pHobs = pHobs, SID = SID), start = c(pK1 = pK1, pK2 = pK2, pK3 = pK3), # the following is also needed to avoid MINPACK failing to fit lower = rep(-1, 3), upper = rep(9, 3) ) # Nonlinear regression model # model: pHobs ~ pHm(...

...e Jacobian of the model function cannot be inverted and fails with > the message "Singular gradient". I wish that R could have a more > reliable built-in nonlinear least squares solver. (I could also be > holding it wrong.) Meanwhile, we have excellent CRAN packages nlsr and > minpack.lm: > > minpack.lm::nlsLM( > pHobs ~ pHm(SID, pK1, pK2, pK3), > data.frame(pHobs = pHobs, SID = SID), > start = c(pK1 = pK1, pK2 = pK2, pK3 = pK3), > # the following is also needed to avoid MINPACK failing to fit > lower = rep(-1, 3), upper = rep(9, 3) > ) > # N...

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic...

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...

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

...tal spectrum. Then a fit is made to this data. Note that if 'w' in the upper limit is set to e.g 0.6, 0.7, or 0.8 the fit always hits this limit. If 'w'=Inf, the fit calculates to something around 0.06, which is correct. Why does the fit go wrong if 'w' is not Inf? library(minpack.lm) #Create x axis x<-seq(from=0.1,to=0.6,by=0.5/150) #Simulate a function with noise fu<-function(y0,A,w,xc,x){ eq<-y0 + 2*A/pi*w/(4*(x-xc)^2+w^2) eq<-jitter(eq,factor=200) } #Evaluate function aka Measured data y<-fu(0,0.01,0.06,0.23,x) data<-as.data.frame(cbind(x,y)) #St...

SAS has DUD (Does not Use Derivatives)/Secant Method for nonlinear regression, does R offer this option for nonlinear regression? I have read the helpfile for nls() and could not find such option, any suggestion? Thanks, Derek [[alternative HTML version deleted]]

...e model function cannot be inverted and fails with >> the message "Singular gradient". I wish that R could have a more >> reliable built-in nonlinear least squares solver. (I could also be >> holding it wrong.) Meanwhile, we have excellent CRAN packages nlsr and >> minpack.lm: >> >> minpack.lm::nlsLM( >> ? pHobs ~ pHm(SID, pK1, pK2, pK3), >> ? data.frame(pHobs = pHobs, SID = SID), >> ? start = c(pK1 = pK1, pK2 = pK2, pK3 = pK3), >> ? # the following is also needed to avoid MINPACK failing to fit >> ? lower = rep(-1, 3), upper...

Dear all, I would like to use the Levenberg-Marquardt algorithm for non-linear least-squares regression using function nls.lm. Can anybody help me to find a a way to compute confidence intervals on the fitted parameters as it is possible for nls (using confint.nls, which does not work for nls.lm)? Thank you for your help Michael

...kelihood' section I've read: After the fitting, out$minimum is the negative log-likelihood, and out$estimates are the maximum likelihood estimates of the parameters. To obtain the approximate SEs of the estimates we do: > sqrt(diag(solve(out$hessian))) As for me, I use MINPACK fortran library for NLS fitting in R, and there I also get the hessian matrix. What formula should I use in _this_ case? Well, some times ago I had a glance at gsl, GNU Scientific Library. It use converted-to-C MINPACK for NLS fit too. And, in the GSL ref. manual example http://www.gnu.org/sof...