similar to: Changing sequential regression code to call systemfit

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

Surprisingly, I played around with some test code and below actually creates equations that look correct. tempmat<-matrix(10,nrow=6,ncol=6) restrictmat<-diag(6) colnames(tempmat)<-c("AUD.l1","CHF.l1","CAD.l1","GBP.l1","EUR.l1","JPY.l 1")

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

Hi there, I am really new to statistics in R and statistics itself as well. My situation: I ran a lot of OLS regressions with different independent variables. (using the lm() function). After having done that, I know there is endogeneity due to omitted variables. (or perhaps due to any other reasons). And here comes the Hausman test. I know this test is used to identify endogeneity. But what I

Hi all, I am stuck at ploting multiple graphs on one page. I don't why it doesn't work. All the 6 plots are either exactly the same, or they simply don't plot at all. I made sure that in each iteration the "datasub" and "factorsub" are different ... Could you please help me? Thanks a lot! I did my homework and followed the following advice:

Hello, I'd like to simulate data according to an SVAR model in order to demonstrate how other techniques (such as arima) yield biased estimates. I am interested in a 2 variable SVAR with 2 lags (in the notation of the vars vignette, K = 2, P = 2, where B = I_K). I'm using the {vars} package outlined here: http://cran.r-project.org/web/packages/vars/vignettes/vars.pdf I thought that the

Hi, I have a data set of 10000 rows and ran a linear regression by using the function lmres = lm(formula,data) then got the fitted value by using the value fit=fitted(lmres). but the number of rows in the fitted one is about 9548, What could be the reason for reduction in the number of rows in the fitted one -- View this message in context:

Hi everyone, I am looking to do some manual maximum likelihood estimation in R. I have done a lot of work in Stata and so I have been using output comparisons to get a handle on what is happening. I estimated a simple linear model in R with lm() and also my own maximum likelihood program. I then compared the output with Stata. Two things jumped out at me. Firstly, in Stata my coefficient

Hi everyone, I'm working with the Vector Autoregressive Model (VAR), and it seems like the ur.ca package provides the best function for this purpose. My problem is, that I don't know how to extract a certain value from the output without using the variables names. I was hoping that this could be done by using numerical value, e.g. [1], instead of writing for instance $Liabilities. The

Saludos Cordiales Estoy tratando de obtener la descomposición de varianza para un modelo de vectores autorregresivos estructural pero el módulo vars no permite hacerlo de manera directa, sin embargo, encontré programaciones de funciones específicas para los vectores autorregresivos estructurales que se acoplan directamente al modelo VARs, alguien me puede decir en que parte debo incorporar la

https://bugzilla.samba.org/show_bug.cgi?id=13953 Bug ID: 13953 Summary: error message instead of --stats informations (in case of vanished files), using rsync 3.1.1 and rsync 3.0.9 Product: rsync Version: 3.1.1 Hardware: x64 OS: Linux Status: NEW Severity: normal Priority: P5

Good day, I'm using a VAR model to forecast sales with some extra variables (google trends data). I have divided my dataset into a trainingset (weekly sales + vars in 2006 and 2007) and a holdout set (2008). It is unclear to me how I should predict the out-of-sample data, because using the predict() function in the vars package seems to estimate my google trends vars as well. However, I want

Hello, I would like to estimate a VAR model with HAC corrected standard errors. I tried to do this by using the sandwich package, for example: > library(vars) > data(Canada) > myvar = VAR(Canada, p = 2, type = "const") > coeftest(myvar, vcov = vcovHAC) Error in umat - res : non-conformable arrays Which suggests that this function is not compatible with the VAR command.

Did you see this http://llvm.org/viewvc/llvm-project?view=revision&revision=287140 ? Interpreting these numbers may be tricky because of hyper threading, though. On Wed, Nov 16, 2016 at 5:15 PM, Joerg Sonnenberger via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On Wed, Nov 16, 2016 at 12:44:46PM -0800, Rui Ueyama via llvm-dev wrote: > > I'm thinking to enable --threads

Hello, many of our platforms do not have a integrated floppy, some even don''t have a floppy controller. As pxelinux still has a problem with machines without a floppy in combination with some bios versions I need to chainload a different bootstrap loader which works on the floppyless platforms. But I also need to load a BartPE and the other BS loader does not support that. So I tried to

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LLD supports multi-threading, and it seems to be working well as you can see in a recent result <http://llvm.org/viewvc/llvm-project?view=revision&revision=287140>. In short, LLD runs 30% faster with --threads option and more than 50% faster if you are using --build-id (your mileage may vary depending on your computer). However, I don't think most users even don't know about that