search for: eq1

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) #atempt 1 to "automate" above:eqSystem1 <-paste(paste("form", 1:4, sep=""), paste("EQ"...

Is there a way to apply paste to?list(form1 = EQ1, form2 = EQ2, form3 = EQ3, form4 = EQ4)?such that I don't have to write form1=EQ1 for all my models?(I might have a list of 20 or more)? I also need the EQs to read the formulas associated with them. For example, below, I was able to automate the name assignment but I could not figure out how...

...9;d prefer to avoid doing that unless it's entirely necessary. I'll post my solution to the list when I've worked it out. Regards, ~Owen # CODE FOR "sur" OPTION rm(list = ls()) library(Zelig) y1 = c(1,2,3,4) y2 = c(0,2,0,2) x = c(2,3,4,8) d = data.frame(cbind(y1, y2, x)) eq1 = y1 ~ x eq2 = y2 ~ x eqSystem = list (eq1, eq2) system_out = zelig(formula = eqSystem, model = "sur", data = d) summary(system_out) ----------------------------------------------------------------- # ERROR FROM REPLACING "sur" WITH "poisson" Error in switch(mode(x)...

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  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 You...

...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){ rows_x <- length(x)/2 x_1 <- x[1:rows_x] x_2 <- x[(rows_x+1):(rows_x*2)] eq1<- x_1-100 eq2<-x_2*10-40 return(c(eq1,eq2)) } model_test <- function() { reserves<-(c(0:200)/200)^(2)*2000 lambda <- numeric(NROW(reserves))+5 res_ext <- pmin((reserves*.5),5) x_test <- c(res_ext,lambda) #print(x_test) for(test_iter in c(1:1000)) nleqslv(x_test,cons_ext_tes...

...try to do something similar on my own data (called R_manuf and containing 3 columns named va98, ts98 and gom98) with the code library(systemfit) dati <- read.table("R_manuf",header=T,na.strings="nan") attach(dati) y1 <- va98/ts98 - 1; y2 <- gom98 - va98; eq1.formula <- y1.98 ~ a1*ts98^(b1-1) ; eq2.formula <- y2.98 ~ a2*ts98^b2 ; labels <- list("eq1", "eq2" ); start.values <- c(a1=-0.5, b1=1.02, a2=-0.8, b2=0.9 ); model <- list( eq1.formula, eq2.formula); model.ols <- nlsystemfit( "OLS", model, star...

...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 Isn't it possible to provide equations in the form eq1 ~ f1(x,t,theta) etc. to "nlsystemfit()" ? Kind regards, Kilian Plank [[alternative HTML version deleted]]

...E PROGRAM ################ YX<-as.data.frame(matrix(rnorm(280),ncol=14, nrow=20)) ## generate variables names(YX) <-c(paste("Y", 1:4, sep=""), paste("X", 1:10, sep="")) ## assign variables' names library(systemfit) ## EQUATIONS: EQ1 <- Y1 ~ X1 + X2 + X4 + X7 + X10 ## equation 1 formula EQ2 <- Y2 ~ X2 + X3 + X5 + X8 + X10 ## equation 2 formula EQ3 <- Y3 ~ X5 + X6 + X7 + X9 ## equation 3 formula EQ4 <- Y4 ~ X1 + X3 + X4 + X6 + X9 ## equation 4 formula eqSystem <-list(form1 = EQ1, form2...

...rt(w)*a; a t(a)%*%a On 1/4/2017 5:41 PM, Steven Yen wrote: > I need help with gls{nlme}. > Specifically, I am estimating an equation with AR(1) using > maximum-likelihood. I am not understanding the correlationoption > below. Help appreciated. > > === > library(nlme) > eq1<-log(chnimp)~log(chempi)+log(gas)+log(rtwex)+befile6+ > affile6+afdec6 > reg1<-gls(eq1,data=mydata,correlation=corAR1(),method="ML",verbose=T) > [[alternative HTML version deleted]]

...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, tau=0.05, data=data1) summary(eq1) summary(qr.05.nox) Error in solve.default(crossprod(x)) : system is computationally singular: reciprocal condition number = 4.51499e-31 Error in diag(solve(crossprod(x))) : error in evaluating the argument ...

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, So=0.02, k2=250, E=0.01); pars yini <- c(S=0.01, ES = 0.01, P=0.0, E=0.01); yini times <- seq(0, 0.01, by = 0.0001); times dyini = c(dS=0.0, dES=0.0, dP=0.0) ## Tabular output check of matrix...

...s-ascii 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, So=0.02, k2=250, E=0.01); pars yini <- c(S=0.01, ES = 0.01, P=0.0, E=0.01); yini times <- seq(0, 0.01, by = 0.0001); times dyini = c(dS=0.0, dES=0.0, dP=0.0) ## Tabular output check of matrix...

...017 5:41 PM, Steven Yen wrote: >> I need help with gls{nlme}. >> Specifically, I am estimating an equation with AR(1) using >> maximum-likelihood. I am not understanding the correlationoption >> below. Help appreciated. >> >> === >> library(nlme) >> eq1<-log(chnimp)~log(chempi)+log(gas)+log(rtwex)+befile6+ >> affile6+afdec6 >> reg1<-gls(eq1,data=mydata,correlation=corAR1(),method="ML",verbose=T) >> > > [[alternative HTML version deleted]] > >____________________________________________...

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 equation nonlinear model formula and package "systemfit" doesn't allows any nonlinear estimation. Do you kn...

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 coefficients to estimate. command "nls" accept only single equation nonlinear model formula and package "systemfit" doesn't allows any nonlinear estimation. Do you k...

...the heteroscedasticity) and z are assumed to be positively correlated. I thought that since the two terms on the rhs of eq.1 are uncorrelated the 3rd central moment of y should equal the sum of the 3rd central moments of the two terms on the rhs. This seems to be correct as long as x and z in eq1 are uncorrelated. But if I make x and z correlated the 3rd moment of y exceeds the sum of the 3rd moments of the terms on the rhs. My problem is that I cannot understand why this is the case (there seems to be no linear correlation between z and the multiplicative error term). Is it my statis...