similar to: Loops, Paste, Apply? What is the best way to set up a list of many equations?

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)

Greetings R Users, I have a system of equations for which I would like to output all the R-squares. Assume there are four equations in my system, the only way I found to output all the R-squares is by calling them out one by one as this: summary(fitSUR$eq[[1]])$r.squared summary(fitSUR$eq[[2]])$r.squared summary(fitSUR$eq[[3]])$r.squared summary(fitSUR$eq[[4]])$r.squared But isn't there a

Hello, I've written a small function that's supposed to save me some time, and it's ending up killing it- the intention is to iteratively subset a dataset fram on framevec, fit a model (either lm or nls depending on type) and return the r2 or AIC from the model, respectively. Although as far as I can tell in my code the plots are dependent on the fit of the model to the data and the

Hello, I'm testing a simple delphi application that have 3 forms. >From FORM1 (the main form) I press a button to show FORM2, then from FORM2 I press a button to show FORM3, when I close FORM3, FORM1 becomes focused instead of FORM2. Every time you close a form or a dialog the application main form becomes the active one. This only happend in KDE, allowing windows manager to control the

Here is a function I wrote. It runs no problem, but generate empty pdf files. I can't find what is the problem. create.pdf<- function(x, dir) { dir.create(dir, showWarnings = FALSE) plist<- c("a", "b" , "c", "d") for(j in plist) { filedir<- paste(dir, "/", j, ".pdf",

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

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

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

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 all, I am relatively new to R, but enjoying it very much. I am hoping that someone on this list can help me with an issue I am having. I am having issues with iterations over nleqslv, in that the solver does not appear to clean up memory used in previous iterations. I believe I've isolated the/my issue in a small sample of code: library(nleqslv) cons_ext_test <- function(x){

Hi, I am estimating a regression but the summary command is unable to provide me results, while the coefficients are available from the coefficients value. I suppose that it cannot estimate the covariance matrix. Is there any command that I can relax the tolerance so it can estimate the covariance matrix. The code and the error of R is: eq1<-rq(y~factor(year)+factor(state)+x1+x2+x3,

I'm getting this error on the attached code and breaking my head but can't figure it out. Any help is much appreciated. Thanks, Vince CODE: library(deSolve) Res_DAE=function(t, y, dy, pars) { with(as.list(c(y, dy, pars)), { res1 = -dS -dES-k2*ES res2 = -dP + k2*ES eq1 = Eo-E -ES eq2 = So-S -ES -P return(list(c(res1, res2, eq1, eq2))) }) } pars <- c(Eo=0.02,

Vince, When that happens, one possible reason is that your DAE is of index > 1, which cannot be solved by daspk. The solver radau, also from deSolve can handle DAEs up to index 3, but you need to rewrite the problem in the form M*y' = f(x,y), where M is a mass matrix. If you do that for your problem, and solve it with radau, then radau complains that the "matrix is repeatedly

I need to have all elements of a matrix multiplied by a weight before being post-multiplied by itself, as shown in the forst block of codes below. I can also multiply the matrix by the square root of the weight and then take the outer product. Actually, what I need is this. Denote each row of the matrix by a row vector as xi and each element of the weighting vector as wi. Then, I need the

Is this a question? You seem to have three possible calculations, have already implemented two of them (?) and it is unclear (to me) what you think the right answer for any of them is supposed to be. -- Sent from my phone. Please excuse my brevity. On June 7, 2017 8:50:55 PM PDT, Steven Yen <syen04 at gmail.com> wrote: >I need to have all elements of a matrix multiplied by a weight

Hello, I want to solve a nonlinear 3SLS problem with "nlsystemfit()". The equations are of the form y_it = f_i(x,t,theta) The functions f_i(.) have to be formulated as R-functions. When invoking "nlsystemfit()" I get the error Error in deriv.formula(eqns[[i]], names(parmnames)) : Function 'f1' is not in the derivatives table

Hello to everyone, I found some problems using R in the estimation of systems of nonlinear equations like SURE (Seemingly Unrelated Regression Equations) with mutual parameters as the following system example: EQ1 PQ1=P1*G1+B1*(Y-P1*G1-P2*G2-P3*G3) EQ2 PQ2=P2*G2+B2*(Y-P1*G1-P2*G2-P3*G3) where G1,G2,G3,B1,B2 are the coefficients to estimate. command "nls" accept only single

TO: r-help at lists.R-project.org r-help at stat.math.ethz.ch Hello to everyone, I found some problems using R in the estimation of systems of nonlinear equations like SURE (Seemingly Unrelated Regression Equations) with mutual parameters as the following system example: EQ1 PQ1=P1*G1+B1*(Y-P1*G1-P2*G2-P3*G3) EQ2 PQ2=P2*G2+B2*(Y-P1*G1-P2*G2-P3*G3) where G1,G2,G3,B1,B2 are the

Dear listusers, I don't know whether my problem is statistical or computational, but I hope I could recieve some help in either case. I'm currently working on a MC-simulation in which I would like to control the skewness of a heteroscedastic dependent variable defined as: y=d*z+sqrt(.5+.5*x^2)*e (eq.1) where d is a parameter and, z, x, and e are gamma r.vs. The variables x

Hi useRs, I'm trying for the first time to use a sem. The model finally runs, but gives a warning saying : "In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, : Could not compute QR decomposition of Hessian. Optimization probably did not converge. " I found in R-help some posts on this warning, but my attemps to modify the code didn't change