similar to: Using lm to estimate a parameter?

Dear all, For estimating Cobb-Douglad production Function [ Y = ALPHA * (L^(BETA1)) * (K^(BETA2)) ], i want to use nls function (without linearizing it). But how can i get initial values? ------------------------------------ > options(prompt=" R> " ) R> Y <- c(59.6, 63.9, 73.5, 75.6, 77.3, 82.8, 83.6, 84.9, 90.3, 80.5, 73.5, 60.3, 58.2, 64.4, 75.4, 85, 92.7, 85.4,

I am trying to fit a rank-frequency distribution with 3 unknowns (a, b and k) to a set of data. This is my data set: y <- c(37047647,27083970,23944887,22536157,20133224, 20088720,18774883,18415648,17103717,13580739,12350767, 8682289,7496355,7248810,7022120,6396495,6262477,6005496, 5065887,4594147,2853307,2745322,454572,448397,275136,268771) and this is the fit I'm trying to do: nlsfit

Shalini Raghavan 3M Pharmaceuticals Research Building 270-03-A-10, 3M Center St. Paul, MN 55144 E-mail: sraghavan at mmm.com Tel: 651-736-2575 Fax: 651-733-5096 ----- Forwarded by Shalini Raghavan/US-Corporate/3M/US on 08/16/2004 11:25 AM ----- Shalini

Hi, I have been brought back to the "R-Side" from MatLab. I have used R in graduate econometrics but only for statistics and regression (linear and nonlinear). But now I need to run general nonlinear optimization. I know about the add-in quadprog but my problem is not QP. My problem is a general nonlinear (obj funct) with linear constraints.I know about the "ms" and

Hi All, Could any one tells me if R or S has the capacity to fit nonlinear regression with Huber's M estimation? Any suggestion is appreciated. I was aware of 'rlm' in MASS library for robust linear regression and 'nls' for nonlinear least squares regression, but did not seem to be able to find robust non-linear regression function. Thanks and regards, Ray Liu

Hello, I want to find the roots of an equation in two variables. I am aware of the uniroot function, which can do this for a function with a single variable (as I understand it...) but cannot find a function that does this for an equation with more than one variable. I am looking for something implementing similar to a Newton-Raphson algorithm. Thanks. -- Bill Shipley North American Editor for

Dear R-Help, I am trying to use R to solve a nonlinear equation many times for different values. I am looking for a mathematical nonlinear equation solution which may not have a closed solution form. For example, I have equation: 2 = (t^2)/log(t) What is t? I am wondering how to solve it in R. Many thanks, Zhu Wang Statistical Science Department SMU.

Hello, I want to perform a nonlinear curve fit in order to obtain parameter estimates from experimentally determined data (y in dependence of x), but with an implicit function, thus, a function of which I cannot isolate y on the left-hand side of the equation. As far as I understand, the functions I found up to now (nls, optim) all work only for explicit functions. My data looks like

> > >From: robert-mcfadden w o2.pl > > >Date: 2008/04/02 Wed AM 09:58:28 CDT > > >To: r-help w r-project.org > > >Subject: [R] Nonlinear equation > > > > hi: you need to give an example and details or > > you won't get much response, if any. Equation e.g. (A, B are known constants): 3log(gamma(x))-log(gamma(x)*gamma(2x))+(x-1)*A+B=0

Hi all, I want to fit data called "metal" with a polynominal function as dP ~ a.0 + a.1 * U0 + a.2 * U0^2 + a.3 * U0^3 + a.4 * U0^4 The data set includes, the independant variable U0 and the dependant variable dP. I've seen that the combination of lm() and poly() can do that instead of using the nls() function. But I don't get how to interpret the results from the linear

You also need to reply-all so the mailing list stays in the loop. -- Sent from my phone. Please excuse my brevity. On December 19, 2017 4:00:29 PM PST, Timothy Axberg <axbergtimothy at gmail.com> wrote: >Sorry about that. Here is the code typed directly on the email. > >qe = (Qmax * Kl * ce) / (1 + Kl * ce) > >##The data >ce <- c(15.17, 42.15, 69.12, 237.7, 419.77)

Dear All, A couple of questions about the nls package. 1. I'm trying to run a nonlinear least squares regression but the routine gives me the following error message: step factor 0.000488281 reduced below `minFactor' of 0.000976563 even though I previously wrote the following command: nls.control(minFactor = 1/4096), which should set the minFactor to a lower level than the default

Do I modify auth-system.conf.ext only (sorry for the question) if yes, I've same problem Pol On 2017-09-05 13:34, Aki Tuomi wrote: > Try configuring like this: > > passdb { > args = scheme=SHA256 username_format=%u /etc/dovecot/users > driver = passwd-file > } > > passdb { > driver = static > args = username=%n noauthenticate > skip = authenticated

Hello Everybody, I am running R 2.2.0 with Windows XP i am trying to fit nonlinear differential equation to data sets which looks like this: Week N C 0 1 1 1 5 6 2 6.2 12.2 3 59 71.2 4 39 110.2 5 38 148.2 6 44 192.2 7 20.4 212.6 8 19.4 232 9 34.2 266.2 10 35.4 301.6 and i need to fit these data to the following diff equation: dNdt=a*N-b*N*C, dCdt=N^2, Where a=birth rate, b=death rate and N=

does not work :-/ Sep 05 13:49:41 auth: Debug: auth client connected (pid=31115) Sep 05 13:49:41 auth: Debug: client in: AUTH 1 PLAIN service=imap secured session=IFCT0m9Y0KjAqAFk lip=192.168.1.100 rip=192.168.1.100 lport=143 rport=43216 resp=AHBvbGhhbGxlbkBmdWNrYXJvdW5kLm9yZwBQYW5kb3JhMjAwMA== (previous base64 data may contain sensitive data) Sep 05

Dear all, I am trying to write an R function that can estimate Transfer functions *with additive noise* i.e. Y_t = \delta^-1(B)\omega(B)X_{t-b} + N_t where B is the backward shift operator, b is the delay and N_t is a noisy component that can be modelled as an ARMA process. The parameters to both the impulse response function and the ARMA noisy component need to be estimated simultaneously. I

Dear All, I am trying to fit to the data a nonlinear function, say z(tau;b) where tau is the independent variable and b is 3x1 vector of parameters. Following previous suggestions from the list, I am trying to find some "optimal" starting values for the three parameters by using the command 'optim' and then feed these values to nls for estimation. Does anybody know hot to

I am trying to figure out how to run maximum likelihood in R. Here is my situation: I have the following equation: equation<-(1/LR-(exp(-k*T)*LM)*(1-exp(-k))) LR, T, and LM are vectors of data. I want to R to change the value of k to maximize the value of equation. My attempts at optim and optimize have been unsuccessful. Are these the recommended functions that I should use to maximize

Sure :) thanks cat /var/log/dovecot/[...] Sep 05 13:26:02 auth: Debug: auth client connected (pid=30131) Sep 05 13:26:02 auth: Debug: client in: AUTH 1 PLAIN service=imap secured session=JK0Bfm9YuqfAqAFk lip=192.168.1.100 rip=192.168.1.100 lport=143 rport=42938 resp=AG1heEBmdWNrYXJvdW5kLm9yZwBQYW5kb3JhMjAwMA== (previous base64 data may contain

thanks Aki, but with all your advices I've same problem: in the logs always I see the authentication with user and domain name, so dovecot doesn't accept it any idea? thanks! Pol On 2017-09-05 10:58, Aki Tuomi wrote: > Oh right, you need to do it like this... > > after the passwd-file drivers add > > passdb { > driver = static > args = username=%n