similar to: Problem with NLSYSTEMFIT()

I've been working on a new package and I have a few questions regarding the behaviour of the nlm function. I've been (for better or worse) using the nlm function to fit a linear model without suppling the hessian or gradient attributes in the objective function. I'm curious as to why the nlm requires 31 iterations (for the linear model), and then it doesn't work when I try to add

Hello everyone, I have estimated system of three linear equations with one non-linear restrictions with nlsystemfit. I was wondering how I can calculate the R-squared (or some alternative coefficient of determination) for the whole system. This is automatically given by linear systemfit but not by nlsystemfit. I can get the values for each of the equations separately, but apparently not for

Hi everybody, I'm a newbye with lots of problems :). I'm trying to use nlsystemfit, but I recieve two error messages whose origin that I don't understand. 1) When I try to reproduce the example reported in the systemfit package manual, that is library( systemfit ) data( ppine ) hg.formula <- hg ~ exp( h0 + h1*log(tht) + h2*tht^2 + h3*elev + h4*cr) dg.formula <- dg ~ exp( d0

Dear R-list members, I've had a hard time trying to solve a non-linear system (nls) of equations which structure for the equation i, i=1,...,4, is as follows: f_i(d_1,d_2,d_3,d_4)-k_i(l,m,s) = 0 (1) In the expression above, both f_i and k_i are known functions and l, m and s are known constants. I would like to estimate the vector d=(d_1,d_2,d_3,d_4) which is solution

I've got a package I would like to send out for testing and have noticed a "problem" with the \tabular portion of the help "compiler" the code for inserting vertical lines, in the tabular environment, causes the build to choke, but not the check command. C:\>rcmd build --binary -docs=all nlsystemfit \tabular{|l|c|c|c|}{ \hline Method \tab Instruments \tab

Hi everyone, I am new to R and keep getting the message Error in as.vector(x, mode) while trying to run nlsystemfit. Below is my exact code. The data is in Stata format because I only recently swapped to R and am trying to compare results from Stata to make sure I know what is going on. I have searched google and read sever R-help articles with this error. They all say the problem is to do

Hello R users, I am trying to estimate the parameters of a bimodal normal distribution using moments matching, so I have to solve a non-linear system of equations. How can I solve the following simple example? x^2 - y^2 = 6 x ? y = 3 I heard about nlsystemfit, but I don?t know how to run it exactly. I have tried the following code, but it doesn?t really work: f1 <-y~ x[1]^2-x[2]^2-6 f2

I am running R version 2.15.1 in Windows XP I am having problems with a function I'm trying to create to: 1. subset a data.frame based on function arguments (colname & parmname) 2. rename the PARMVALUE column in the data.frame based on function argument (xvar) 3. generate charts plotvar <- function(parentdf,colname, parmname,xvar,yvar ){ subdf <-

Hi, I would like to estimate a quadratic almost ideal demand system in R which is estimated usually by nonlinear seemingly unrelated regression. But there is no such function in R yet but it is readily available in STATA (nlsur), see B. Poi (2008): Demand-system estimation: Update, Stata Journal 8(4). Now I am thinking, what is quicker learning to "program" STATA which seems not really

Hi, I would appreciate if someone could help me on track with this problem. I want to compute some parameters from a system of equations given a number of sample observations. The system looks like this: sum_i( A+b_i>0 & A+b_i>C+d_i) = x sum_i( C+d_i>0 & C+d_i>A+b_i) = y sum_i( exp(E+f_i) * ( A+b_i>0 & A+b_i>C+d_i) = z A, C, E are free variables while the other

Hi, I am solving a projection pursuit regression problem, of the form y = \sum_i f_i (a_i^T x), where a_i are unknown directions, while f_i are unknown univariate link functions. The following is known about each f_i: 1. f_i (0) = 0  (that is, each f_i passes through the origin) 2. f_i is monotonic. Is there a way to ensure that the function ppr() in R produces solutions that respect the

Dear List Members,I am trying to set up a large system of equations and I am trying to find a simple way to set up the list command under the package system fit. Here is the example from system fit and what I am trying to do: EQ1 <- Y1 ~ X1 + X2 + X4EQ2 <- Y2 ~ X2 + X3EQ3 <- Y3 ~ X2 + X3 + X4EQ4 <- Y4 ~ X1 + X3 + X4eqSystem <-list(form1 = EQ1, form2 = EQ2, form3 = EQ3, form4 = EQ4)

Dear list members, Is there a package somewhere for jointly estimating two poisson processes? I think the closest I've come is using the "SUR" option in the Zelig package (see below), but when I try the "poisson" option instead of the "SUR" optioin I get an error (error given below, and indeed, reading the documentation of the Zelig package, I get the impression

Hello to everyone, I have 2 problems and would be very pleased if anyone can help me: 1) When I use the package "systemfit" for SUR regressions, I get two different variance-covariance matrices when I firstly do the SUR regression ("The covariance matrix of the residuals used for estimation") and secondly do the OLS regressions. In the manual for "systemfit" on page

Dear all, Given a LME model (following the notation of Pinheiro and Bates 2000) y_i = X_i*beta + Z_i*b_i + e_i, is it possible to extract the variance-covariance matrix for the estimated beta_i hat and b_i hat from the lme fitted object? The reason for needing this is because I want to have interval prediction on the predicted values (at level = 0:1). The "predict.lme" seems to

new klibc sparc build failure against gcc 4.2 ----- Forwarded message from Kilian Krause <kilian at debian.org> ----- Subject: Bug#440721: FTBFS on sparc while linking usr/klibc/libc.so From: Kilian Krause <kilian at debian.org> To: Debian Bug Tracking System <submit at bugs.debian.org> Date: Mon, 03 Sep 2007 23:35:23 +0200 Package: klibc Version: 1.5.6-2 Severity: serious

Hey, I want to implement a structural model with the package systemfit with some linear and nonlinear constraints. How to implement linear restrictions is clear. Does anybody know how to set up nonlinear restrictions in the systemfit packages. For example: beta1 = beta2-(beta4/beta6) I look forward to your reply -- View this message in context:

Hi Has anybody done THD or THD-N measurements with the CELT Codec (bext would be on various bit rates) If someone could share results for Mono at 64kBit and Stereo at 128 and 196kBit it would be great. thank you very much Jochen -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.xiph.org/pipermail/opus/attachments/20100817/b1da17cc/attachment-0002.htm

https://bugzilla.samba.org/show_bug.cgi?id=9783 Summary: please don't use client-server model for local copies Product: rsync Version: 3.0.9 Platform: All URL: http://lwn.net/Articles/400489/ OS/Version: Linux Status: NEW Severity: enhancement Priority: P5 Component: core

Hi  I want to fit two equations simultaneously EQ1<-Y1~X1+X2 EQ2<-Y2~X1+X2 eqsystem<-list(Y1HAT=EQ1,Y2HAT=EQ2) fitols<-systemfit(eqsystem, method="OLS", data=BB) How do I get coefficients for the first equation? R code How do I restrict coefficient of X2 in the first equation (say , restrict it to less than  zero). R code Your help is appreciated. Dereje [[alternative