Hi Rainer,
It is very simple to specify the constraints (linear or nonlinear) in
"alabama" . They are specified in a function called `hin', where
the constraints are written such that they are positive. Your two nonlinear
constraints would be written as follows:
hin <- function(x, LAI) {
h <- rep(NA, 2)
h[1] <- LAI^x[2] / x[3] + x[1]
h[2] <- 1 - x[1] - LAI^x[2] / x[3]
h
}
Please take a look at the help page. If it is still not clear, you can contact
me offline.
Best,
Ravi
Ravi Varadhan, Ph.D. (Biostatistics), Ph.D. (Environmental Engg)
Associate Professor, Department of Oncology
Division of Biostatistics & Bionformatics
Sidney Kimmel Comprehensive Cancer Center
Johns Hopkins University
550 N. Broadway, Suite 1111-E
Baltimore, MD 21205
410-502-2619
[[alternative HTML version deleted]]
Ravi Varadhan <ravi.varadhan at jhu.edu> writes:> Hi Rainer, > It is very simple to specify the constraints (linear or nonlinear) in > "alabama" . They are specified in a function called `hin', where the > constraints are written such that they are positive.OK - I somehow missed the part that, when the values x are valid, i.e. in the range as defined by the conditions, the result of hin(x) that they are all positive.> Your two nonlinear constraints would be written as follows: > > hin <- function(x, LAI) { > h <- rep(NA, 2) > h[1] <- LAI^x[2] / x[3] + x[1] > h[2] <- 1 - x[1] - LAI^x[2] / x[3] > h > }Makes perfect sense.> > Please take a look at the help page. If it is still not clear, you can contact me offline.Yup - I did. But I somehow missed the fact stated above. I am using constrOptim() and constrOptim.nl() for a paper and am compiling a separate document which explains how to get the constraints for the two functions step by step - I will make it available as a blog post and a pdf. I might have further questions concerning the different fitting functions and which ones are the most appropriate in my case. Thanks a lot, Rainer> Best, > Ravi > > Ravi Varadhan, Ph.D. (Biostatistics), Ph.D. (Environmental Engg) > Associate Professor, Department of Oncology > Division of Biostatistics & Bionformatics > Sidney Kimmel Comprehensive Cancer Center > Johns Hopkins University > 550 N. Broadway, Suite 1111-E > Baltimore, MD 21205 > 410-502-2619 > > > [[alternative HTML version deleted]] >-- Rainer M. Krug email: Rainer<at>krugs<dot>de PGP: 0x0F52F982 -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: application/pgp-signature Size: 454 bytes Desc: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20151001/aba6f3ad/attachment.bin>
I would recommend that you use auglag() rather than constrOptim.nl() in the package "alabama." It is a better algorithm, and it does not require feasible starting values. Best, Ravi -----Original Message----- From: Rainer M Krug [mailto:Rainer at krugs.de] Sent: Thursday, October 01, 2015 3:37 AM To: Ravi Varadhan <ravi.varadhan at jhu.edu> Cc: 'r-help at r-project.org' <r-help at r-project.org> Subject: Re: optimizing with non-linear constraints Ravi Varadhan <ravi.varadhan at jhu.edu> writes:> Hi Rainer, > It is very simple to specify the constraints (linear or nonlinear) in > "alabama" . They are specified in a function called `hin', where the > constraints are written such that they are positive.OK - I somehow missed the part that, when the values x are valid, i.e. in the range as defined by the conditions, the result of hin(x) that they are all positive.> Your two nonlinear constraints would be written as follows: > > hin <- function(x, LAI) { > h <- rep(NA, 2) > h[1] <- LAI^x[2] / x[3] + x[1] > h[2] <- 1 - x[1] - LAI^x[2] / x[3] > h > }Makes perfect sense.> > Please take a look at the help page. If it is still not clear, you can contact me offline.Yup - I did. But I somehow missed the fact stated above. I am using constrOptim() and constrOptim.nl() for a paper and am compiling a separate document which explains how to get the constraints for the two functions step by step - I will make it available as a blog post and a pdf. I might have further questions concerning the different fitting functions and which ones are the most appropriate in my case. Thanks a lot, Rainer> Best, > Ravi > > Ravi Varadhan, Ph.D. (Biostatistics), Ph.D. (Environmental Engg) > Associate Professor, Department of Oncology Division of Biostatistics > & Bionformatics Sidney Kimmel Comprehensive Cancer Center Johns > Hopkins University > 550 N. Broadway, Suite 1111-E > Baltimore, MD 21205 > 410-502-2619 > > > [[alternative HTML version deleted]] >-- Rainer M. Krug email: Rainer<at>krugs<dot>de PGP: 0x0F52F982