similar to: nonlinearity and interaction

Hello there, I wish to solve the following nonlinear System of equations: + u1 - Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) - Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) == 0 + u2 - Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) - Vmax21*S2/( S2 + Km21 *(1+S1/Km11)) == 0 + Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) + Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) - d1*P1 == 0 + Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) + Vmax21*S2/( S2 +

Dear R community, I have a nonlinear model describing average daily soil temperature. What test should I use to compare differences in soil temperature of the two studied vegetation types depending upon month? Building linear contrasts for the developed nonlinear model does not help since this model does not include variable “Months” (only “Days”). 1) Just a Student’s test is not probably

Dear R community, Using nlme library I have developed a nonlinear mixed model. Incorporating an autoregressive model gives me an error that I can't allocate vector of size X. The problem is that my computer does not have enough physical memory most probably due to a large number of observations (17,000). I was wondering what alternative options I might use: 1) To use ARIMA and

Dear all, I'm interested in testing 2 nonlinear restrictions on coefficients of a nls object. Is there a package for doing this? Something in the lines of `test(nls object, res=c("res 1","res 2"),...)' I only found the function delta.method in the alr3 library that calculates the se of a singleton nonlinear restriction of a nls object using the delta method. Thanks in

Hi, I'm working on leaf characteristics of trees. Each tree is characterised by about 10 leaf traits. The trees were sampled at 9 different locations (about 20 to 30 trees/location, NOT balanced), grouped in 3 different climatic zones (Sahelian, Soudanian and Guinean) (NOT balanced). Further, each tree is characterised by some degree of human pressure (mutilation degree), in total 4

I've been trying to figure out how to build a list of terms from a nonlinear model (terms() returns a error). I need to compute and evaluate the partial derivatives (Jacobian) for each equaiton in a set of equations. For example: > eqn <- q ~ s0 + s1 * p + s2 * f + s3 * a > sv2 <- c(d0=3,d1=4.234,d2=4,s0=-2.123,s1=0.234,s2=2.123,s3=4.234) > names( sv2 ) [1] "d0"

Dear all, I would like to know whether any specification test for linear against nonlinear model hypothesis has been implemented in R using the quantreg package. I could read papers concerning this issue, but they haven't been implemented at R. As far as I know, we only have two specification tests in this line: anova.rq and Khmaladze.test. The first one test equality and significance of

Hi,all: I am running a nonlinear regression and there is a problem. There is a data frame: data p s x t 1 875.0 12392.5 11600 0.06967213 2 615.0 12332.5 12000 0.06967213 3 595.0 12332.5 12000 0.06967213 4 592.5 12337.0 12000 0.06967213 5 650.0 12430.0 12000 0.06967213 6 715.0 12477.5 12000 0.06967213 . . . . str(data): 'data.frame': 234 obs. of 4 variables:

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

Dear all, I am trying to fit a mixed-effects non linear regression, but I have some trouble with it. My data are a balanced panel of 904 subjects with 8 observations (at regular periods) per subject. The functional form of my model is Y=Aexp(-BX1)X2 +e. I want to allow parameters A and B to vary among subjects and also include an autocorrelation term. I have already fitted a standard nonlinear

Dear all, A while ago I posted a message regading the way Samba is behaving and some problems that I was facing with Windows "loosing" the connection with the server... Here is another sample of what my /var/log/messages still looks like: Sep 19 15:08:01 Srv smbd-classic[3499]: [2004/09/19 15:08:01, 0] lib/util_sock.c:read_data(436) Sep 19 15:08:01 Srv smbd-classic[3499]:

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

I am using nonlinear regression to fit a couple of variables to a set of measurements. I would like to do some significance tests for the estimated parameters. I am able to check the confidence intervals using the Jacobian coming out of nonlinear regression. I do see in a paper which shows t-value (it says estimated by White method??), f-value, f-test, and j-test, are these available in matlab,

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.

On 15/05/2014 22:52, Tom Stellard wrote: > On Thu, May 15, 2014 at 10:41:08PM +0300, Alp Toker wrote: >> On 15/05/2014 22:12, Tom Stellard wrote: >>> On Thu, May 15, 2014 at 01:38:32PM +0200, Tuncer Ayaz wrote: >>>> On Thu, 15 May 2014 02:25:30 +0200, Tom Stellard wrote: >>>> >>>>> On Sat, May 10, 2014 at 11:48:23PM +0200, Tuncer Ayaz wrote:

Hello. I am trying to fit an asymptotic relationship (nonlinear) to some ecological data, and am having problems. I am interested in the upper bound on the data (i.e. if there is an upper limit to 'y' across a range of 'x'). As such, I am using the nonlinear quantile regression package (nlrq) to fit a michaelis mention type model. The errors I get (which are dependant on

Hello colleagues, I am attempting to determine the nonlinear least-squares estimates of the nonlinear model parameters using nls. I have come across a common problem that R users have reported when I attempt to fit a particular 3-parameter nonlinear function to my dataset: Error in nls(r ~ tlm(a, N.fix, k, theta), data = tlm.data, start = list(a = a.st, : step factor 0.000488281

Hi there: I'm trying to run a large number of nonlinear regressions on a time series dataset, where the data will be formatted something to the effect of: ObservationID,time,dependentvar I'll have a number of time and dependentvars for each observation, and I want to apply a nonlinear regression to one ObservationID at a time, and I want to have a dataset that is the parameter

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 am running R-2.3.1-i386-1 on Slackware Linux 10.2. I am a former matlab user, moving to R. In matlab, via the cftool, I performed nonlinear curve fitting using the method "nonlinear least squares" with the "Trust-Region" algorithm and not using robust fitting. Is it possible to perform the same analysis in R? I read quite a lot of R documentation, but I could not find