similar to: R] Error message "cs_lu(A) failed: near-singular A (or out of memory)"

Hi there everyone, I have the following model (this is naturally a simplified version just for showing my problem, in case you're wondering this is a translog cost function with the associated cost share equations): C ~ á + â1 log X + â2 log Y + ã1 log Z + ã2 log XX C1 ~ â1 + â2 log YY + ã1 log ZZ Then I have some restrictions on the coefficients, namely that the sum of â equal 1 and the

Hello. I am still a newbie in R. Excuse me if I am asking something obvious. My efforts to get an answer through browsing the mailing archives failed. I want to perform an augmented Dickey-Fuller test and to obtain AIC and BIC and to be able to impose some linear restrictions on the ADF regression so as to decide the correct order of autoregression. However I could find no obvious way to impose

I am confused by the following description in http://www.maths.lth.se/help/R/.R/library/systemfit/html/hausman.systemfit.html what does the "Not run" mean? if we do not load systemfit, how can we run the following code? ## Not run: library( systemfit ) data( kmenta ) attach( kmenta ) ... I install the package of systemfit, and run the code. I got the warning: > library( systemfit

Hi, I added a new function "predict.systemfit" to our package "systemfit" to make it closer to other packages (e.g. lm). Now "R CMD check" complains that the generic function "predict" has only the argument "object", while our function "predict.systemfit" has more arguments. However, the function "predict.lm" has also more

The 'systemfit' function in systemfit 0.7-3 CRAN package seems to have a problem with formulas that contain transformed (eg. log) variables. If I have my data in a data frame, apparently systemfit doesn't "pass" the information of where the variables should be taken to the transforming function. I'm not entirely sure if this is a bug or just a limitation, I was just

Hi I was trying to estimate simultaneous equation system in R using systemfit. I used the following commands >library(systemfit) > data(Kmenta) > attach(Kmenta) >eqDemand<-consump~price+income > eqSupply<-consump~price+farmprice+trend > fitsur<-systemfit("SUR",list(demand=eqDemand, supply=eqSupply)) and got the following error messege Error in

I am having problem using output of lm() function for further analysing using systemfit package. Basicaly, the problem s following - I generate several formulas using lm() > fo1 <- lm(r98[,2] ~ f98[,1] + f98[,2] + ... + f98[,43]) > fo2 <- lm(r98[,1] ~ f98[,1] + f98[,2] + ... + f98[,43]) and than I want to estimate a general model using package systemfit. > fitsur <-

Dear list I am trying to install the systemfit package under unix, install.packages(systemfit) the installation failed. I am attaching the error and version information below, (if dependencies=TRUE, much more error) any help appreciated best, yong ===================================================================== > install.packages("systemfit") Warning in

Hello, i am new to R and have it on my Mac with OSX 10.2. I downloaded the systemfit package and tried to run it and it didn't work. I think i need to install the package, or update R to let it know that I have that in the library. (i simply placed the systemfit folder in the R library.) When i run update.packages(systemfit) or install.packages(systemfit) i get the following error:

Hi, I am trying to obtain the heteroskedasticity consitent standard errors (HCSE) after apply 2SLS. I obtain 2SLS through tsls from package sem or systemfit: #### tsls #### library (sem) Reg2SLS <-tsls(LnP~Sc+Ag+Ag2+Var+R+D,~I2+Ag+Ag2+Var+R+D) summary (Reg2SLS) #### systemfit #### library (systemfit) RS <- LnP~Sc+Ag+Ag2+Var+R+D Inst <- ~I2+Ag+Ag2+Var+R+D labels

Hi, can anybody tell me how the Hausman test for endogenty works? I have a simulated model with three correlated predictors (X1-X3). I also have an instrument W for X1 Now I want to test for endogeneity of X1 (i.e., when I omit X2 and X3 from the equation). My current approach: library(systemfit) fit2sls <- systemfit(Y~X1,data=data,method="2SLS",inst=~W) fitOLS <-

Hello !   I’m trying to estimate a system of equation (demand and supply) using the systemfit package.  My program is:   library(systemfit) demand <- tsyud ~ tsyud1 + tsucp + tspo + tssn supply <- tscn ~ tsyn + tsqn + tsksn + tsucp system <- list(demand=eqdemand, learning = eqsupply) labels <- list(demand="eqdemand", learning="eqsupply") inst <- ~ tsupp1 + tsupp2

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:

Hello all, I hope this question is appropriate for this ML. Basically, I am wondering if when you create a new variable, if the variable holds some information about how it was created. Let me explain, I have the following code to replicate an example in a textbook (Greene's Econometric Analysis), using the systemfit package. dta <-

Dear all, I am relatively new to R and have had some difficulty in understanding the user manual for a package that I have downloaded to evaluate non-linear simultaneous equations. The package is called systemfit. Does anyone have any experience of this package? What I am trying to do is solve a non linear simultaneous equations... Could anyone give me an example (please) of the code that

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

How does one specify the weights for WLS in the systemfit command ? That is, there is a weight option in lm(), but there doesn't seem to be weight option for systemfit("WLS") Thanks!

Hi, I have two products which are substitudes. I try to fix a system as below to mydata. Demand1 = A1 -B1*Price1 + C1*Price2 Demand2 = A2 +B2*Price1 - C2*Price2 I would expect C1 & B2 to be symmetric, If they are truly substitude. How can I enforce this symmetry when creating a system of equations via SystemFit ? -- View this message in context:

Thank you, Greg, and also to Scott Ellison, who replied privately. I am in the process of trying out both suggestions. After I sent my initial message, I came across the Systemfit package, which allows specification of constraints on parameters. In theory, this should solve my problem perfectly. However, I was not able to get it to work with my data, as every attempt yielded the following

I am an R beginner and trying to run a SUR model in R framework. subset(esasp500, Obs <=449 & Obs>=197, select = -Date) ->ev13sub c(Obs>=397) & c(Obs<=399) ->d13 c(Obs>=400) & c(Obs<=449) ->f13 SP500*f13 ->SP500f13 BBC~SP500+d13+SP500f13 ->sur132 BOW~SP500+d13+SP500f13 ->sur133 CSK~SP500+d13+SP500f13 ->sur134