similar to: New version of systemfit (not backward compatible)

Dear R users, The authors of the systemfit package have released a new version of this package with substantial enhancements. The systemfit package contains functions for fitting simultaneous systems of linear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares

Dear R users, The authors of the systemfit package have released a new version of this package with substantial enhancements. The systemfit package contains functions for fitting simultaneous systems of linear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares

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

I get the following error message after using the sysfit package's function 'systemfitClassic': Error in data[[eqnVar]] : subscript out of bounds When I do this: MSYS1 <- cbind(Y, Num, F, PO, PD, GO, GD) MigOLS1 <- systemfitClassic("OLS", F ~ PO + PD + GO + GD, eqnVar = "Num", timeVar = "Y", data = MSYS1) and I get this error message: Error in

Hi, I added the "tests" subdirectory and a test file (say "myTest.R") to our "systemfit" package. Up to now I create the "myTest.Rout.save" file with > R CMD BATCH --vanilla myTest.R myTest.Rout.save However, "R CMD check" reports two differences between myTest.Rout.save and the output of myTest.R: a) myTest.Rout.save contains following

Hi, I would like to obtain the names of all objects that are provided as further arguments ("...") in a function call. I have created a minimal example that illustrates my wish (but isn't useful otherwise): f1 <- function( ... ) return( deparse( substitute( ... ) ) ) x1 <- 1 x2 <- 2 x3 <- 3 f1( x1, x2, x3 ) [1] "x1" However, I would like to obtain the

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 have a vector, which contains both strings and numbers, e.g. > foo <- c("str1",1234,"str2",0.9876) I want to know if a distinct element of the vector is a string or a number and took "is.numeric", but > is.numeric(foo[2]) [1] FALSE because R treats the numbers in a mixed vectors as strings: > foo [1] "str1" "1234"

Dear All, I would like to publish a function for 'heckit' estimations together with two examples from Greene's and Wooldridge's econometric textbooks. These examples use the dataset of Mroz (1987) that is also available in John Fox' "car" package. However, not all variables that are used in my examples are available in the "car" package. Therefore, I

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 was really happy when I saw that in R version 2.3.0 "R CMD check" works for packages whose package name is different from the directory name in which it is located (see http://cran.r-project.org/src/base/NEWS). Now, I can have branches of my packages in directories like "[...]/branches/<version number>/", while I had to use "[...]/branches/<version

Dear R Users: The functions of our "micEcon" package [1,2] can be subdivided into three categories: - microeconomic demand and firm models - sample selection models (mainly selection()) - routines for (likelihood) maximisation (e.g. maxLik(), maxNR(), maxBHHH()) (mainly used for ML estimation of sample selection models) Although sample selection models are often used in

Hi, since nobody answered to my first message, I try to explain my problem more clearly and more general this time: I have a data set in my R package "micEcon", which has many variables (82). Therefore, I would like to avoid to describe all variables in the "\format" section of the documentation (.Rd file). However, doing this lets "R CMD check" complain about

Hi, I wrote a package for linear programming and want to submit it to CRAN. Since the package 'quadprog' has a function with the name 'solve.QP' to perform Quadratic Programming, I named my (main) function 'solve.LP'. However 'R CMD check' gives one warning: * checking generic/method consistency ... WARNING solve: function(a, b, ...) solve.LP:

Dear all, I have uploaded a new package called micEcon (version 0.1-3) to CRAN (an early version of this package has been already presented at useR! 2004). It contains tools for microeconomic analysis and microeconomic modeling. These are for instance: - tools for demand analysis with the 'Almost Ideal Demand System' (AIDS): e.g. econometric estimation, calculation of price and

Dear all, I have uploaded a new package called micEcon (version 0.1-3) to CRAN (an early version of this package has been already presented at useR! 2004). It contains tools for microeconomic analysis and microeconomic modeling. These are for instance: - tools for demand analysis with the 'Almost Ideal Demand System' (AIDS): e.g. econometric estimation, calculation of price and

Dear R Users: We have splitted up the micEcon package into three packages: a) Package "maxLik" provides tools for maximum likelihood estimations (see http://www.maxLik.org). b) Package "sampleSelection" provides tools for estimating Heckman-type sample selection/generalized tobit models (see http://www.sampleSelection.org). c) Package "micEcon" contains the

Dear R Users: We have splitted up the micEcon package into three packages: a) Package "maxLik" provides tools for maximum likelihood estimations (see http://www.maxLik.org). b) Package "sampleSelection" provides tools for estimating Heckman-type sample selection/generalized tobit models (see http://www.sampleSelection.org). c) Package "micEcon" contains the

Hi, I wrote a function to perform a two-step Heckman (also known as "heckit") estimation. This function is mainly a wrapper function to "glm" (1st step probit estimation) and "lm" (2nd step OLS estimation). Though this function is not perfect yet, it is IMHO already very useful. Since there were some questions about Heckmann estimation in this list, I would like

Hi, I have a dataframe (say myData) and want to get a list (say myList) that contains a matrix for each row of the dataframe myData. These matrices are calculated based on the corresponding row of myData. Using a for()-loop to do this is very slow. Thus, I tried to use apply(). However, afaik apply() does only return a list if the matrices have different dimensions, while my matrices have