search for: menten

Dear R users: I encountered difficulties in michaelis-menten equation. I found that when I use right model definiens, I got wrong Km vlaue, and I got right Km value when i use wrong model definiens. The value of Vd and Vmax are correct in these two models. #-----right model definiens-------- PKindex<-data.frame(time=c(0,1,2,4,6,8,10,12,16,20,24),...

...s richness estimation. Nonparametric estimation (such as Chao1, Jacknife1) can be done just using function "specpool()" and "estimateR()" in package "vegan". The problem is that I can not found any functions for parametric estimation (such as MMMeans, MMruns, Michaelis-Menten). Do you know any function for doing this? Thanks a lot. Best wishes, Wenjing

...get exactly what I would get if I copied and pasted from the terminal window. I've read the documentation on data export to text files here: https://cran.r-project.org/doc/manuals/r-release/R-data.html#Export-to-text-files write() does not work. > summary(mymodel) Model fitted: Michaelis-Menten (2 parms) Parameter estimates: Estimate Std. Error t-value p-value d:(Intercept) 213.435 67.094 3.1811 0.009801 ** e:(Intercept) 94.493 59.579 1.5860 0.143820 --- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 Residual standard error: 22.03492 (10 de...

...pied and pasted from the terminal window. > >I've read the documentation on data export to text files here: >https://cran.r-project.org/doc/manuals/r-release/R-data.html#Export-to-text-files > >write() does not work. > >> summary(mymodel) > >Model fitted: Michaelis-Menten (2 parms) > >Parameter estimates: > > Estimate Std. Error t-value p-value >d:(Intercept) 213.435 67.094 3.1811 0.009801 ** >e:(Intercept) 94.493 59.579 1.5860 0.143820 >--- >Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 > >Re...

Dear R users I recently migrated from Statistica/SigmaPlot (Windows) to R (Linux), so please excuse if this may sound 'basic'. When running a nonlinear regression (V = Vmax * conc / (Ks + conc), i.e. Michaelis-Menten) on SigmaPlot, I get the output listed below: >>>Begin SigmaPlot Output<<< R = 0.94860969 Rsqr = 0.89986035 Adj Rsqr = 0.89458984 Standard Error of Estimate = 4.1543 Coefficient Std. Error t P a 34.5878 2.7690 12.4910 <0.0001 b 6.8553 2.2949 2.9872 0.0076 Analysis of Vari...

...ed. Is this from painful experience that some link functions just don't work well? I can go ahead and hack my own version that allows inverse link, but it would be nice to know if I'm doing something dumb. (The reason I want to do this is that the inverse link linearizes the Michaelis-Menten function, y = a*x/(b+x) ...) cheers Ben Bolker -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 252 bytes Desc: OpenPGP digital signature URL: <https://stat.ethz.ch/pipermail/r-help/attachments/200809...

I'm just getting to grips with using ode function and have used the examples and vignettes to produce a small model of a one-pool, michaelis-menten, enzyme kinetic reaction. The rate of flux of substrate into pool A is constant (fluxoa) however the rate of flux out of pool A is controlled by the HMM equation (v = Vmax/ ( 1 + (Km / Concentration A )) ). This function works fine and gives correct answers for the size of the pool of quan...

...page: ## weighted nonlinear regression data(Puromycin) Treated <- Puromycin[Puromycin$state == "treated", ] weighted.MM <- function(resp, conc, Vm, K) { ## Purpose: exactly as white book p.451 -- RHS for nls() ## Weighted version of Michaelis-Menten model ## --------------------------------------------------------------- ## Arguments: `y', `x' and the two parameters (see book) ## --------------------------------------------------------------- ## Author: Martin Maechler, Date: 23 Mar 2001, 18:48 p...

Hi there, I have a data frame as listed below: > Ca.P.Biomass.A P Biomass 1 334.5567 0.2870000 2 737.5400 0.5713333 3 894.5300 0.6393333 4 782.3800 0.5836667 5 857.5900 0.6003333 6 829.2700 0.5883333 I have fit the data using logistic, Michaelis?Menten, and linear model, they all give significance. > fm1 <- nls(Biomass~SSlogis(P, phi1, phi2, phi3), data=Ca.P.Biomass.A) > fm2 <- nls(Biomass~SSmicmen(P, phi1, phi2), data=Ca.P.Biomass.A) > fm3 <- lm(Biomass~P, data = Ca.P.Biomass.A) I hope to compare the difference among the...

Hello! I work with : R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.1 (2006-06-01) On Windows XP Professional (Version 2002) SP2. At this moment I use the function "nls" combined with a selfStar model (SSmicmen, related to Michaelis-Menten equation, and provided by the "stats" package). When I realise the following operation (cf. p 59 of the "An Introduction to R" manual, http://www.r-project.org/, for more details): > fit<-nls(y~SSmicmen(x, Vm, K), df) > summary(fit) I obtain the values of Vm and K....

Dear list, Has anyone created a version of SSmicmen that allows testing for group differences? The basic Michaelis-Menten equation is: (Bmax * X) / (Kd + X). The nlme package allows modeling of random effects for Bmax and Kd as needed, but I curious how I can build in group differences? I have receptor binding data for strains of mice, and following Pinheiro and Bates' lead in their book, a random effort f...

...nspecific binding parameter ns. This equation describes two fitted lines, a linear fit for observed nonspecific binding, and a nonlinear fit for observed total binding. The linear component ns*X + background is shared. In our experiments we don't actually observe data for the Michaelis- Menten component of the equation. It is inferred by subtraction of observed total and observed nonspecific data, or estimated in the combined data by sharing the ns parameter by adding a 1-0 indicator variable to the equation (1 for total, 0 for nonspecific). I now need to do the same kind of estim...

Dear all, Is there a way to retrieve standard errors from nls models? The help page tells me that arguments such as se.fit are ignored... Many thanks and best wishes Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW, Agroecology Waldweg 26 D-37073 Goettingen Germany phone +49 (0)551 39 8807 fax +49 (0)551 39 8806 Homepage http://www.gwdg.de/~cscherb1

Dear R Community, I am attempting to perform a weighted non-linear least squares fit. It has already been noted that the weights option is not yet implemented for the nls function, but no one seems to offer any suggestions for getting around this problem. I am still curious if a) anyone has code they have written which includes a weight options for nls, or b) if there is another model which

...his? I tried "https://svn.r-project.org/R-packages/trunk" and found 'nlme' and other packages but not core R like 'stats'. ##################### ## ## SLIGHT MODIFICATIONS TO CURRENT EXAMPLES ## THAT DON'T WORK (except with my modifications) ## # Weighted Michaelis-Menten model # with data = a list that can not be coerced to a data.frame TreatIrreg <- with(Treated, list(conc1=conc[1], conc.1=conc[-1], rate=rate)) # Passing arguments using a list that can not be coerced to a data.frame weighted.MM1 <- function(resp, conc1, conc.1, Vm, K){ conc <- c(conc1,...

Hi there, I'm trying to fit a growth curve to some data and need to use a weighted least squares estimator to account for heteroscedasticity in the data. A weights argument is available in nls that would appear to be appropriate for this purpose, but it is listed as 'not yet implemented'. Is there another package which could implement this procedure? Regards, Robert Brown

Hello I followed the example in page 59, chapter 11 of the 'Introduction to R' manual. I entered my own x,y data. I used the least squares. My function has 5 parameters: p[1], p[2], p[3], p[4], p[5]. I plotted the x-y data. Then I used lines(spline(xfit,yfit)) to overlay best curves on the data while changing the parameters. My question is how do I calculate the residual sum of squares.

...y Function lvplot.qrrvglm Latent Variable Plot for QO models maxwell Maxwell Distribution Family Function mccullagh89 McCullagh (1989) Distribution Family Function mckaygamma2 McKay's Bivariate Gamma Distribution micmen Michaelis-Menten Model multinomial Multinomial Logit Model nakagami Nakagami Distribution Family Function negbinomial Negative Binomial Distribution Family Function normal1 Univariate normal distribution paralogistic Paralogistic Distribution Family...