similar to: Newey West and Singular Matrix + library(sandwich)

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

Hi, I want to calculate the t- and p-values for a linear model using the Newey West estimator. I tried this Code and it usually worked just fine: > oberlm <- lm(DYH ~ BIP + Infl + EOil, data=HU_H) > coeftest(oberlm, NeweyWest(oberlm, lag=2)) t test of coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.1509950 0.0743832 2.0300 0.179486 BIP

Hi, Does anyone read Verbeek's "A Guide to Modern Econometrics"? In its Section 4.11, how does the last two equations' HAC calculate? I've tried several groups of parameters in sandwich::NeweyWest, but I still cannot get the same result. I've tried lag=2 and lag=3, as long as prewhite=FALSE and prewhite=TRUE yet, but... Sincerely Hsiao-nan Cheung

I?m new to R so maybe this issue has been asked before and I still could not read the complete set of past messages sent to the list. I found a weird behabiour that I will explain with a simple example. Lets consider the following block of commands: > x <- diag(c(1,4,10)) > x [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 4 0 [3,] 0 0 10 > invx <- x^-1 > invx

Dear all, The background is that I'm trying to fix this bug in the geometry package: https://r-forge.r-project.org/tracker/index.php?func=detail&aid=1993&group_id=1149&atid=4552 Boiled down, the problem is that there exists at least one matrix X for which det(X) != 0 and for which solve(X) fails giving the error "system is computationally singular: reciprocal condition

Dear R-users, has anybody combined the glm function with the Newey-West estimator of variance, similar as in Stata 7.0? I'd like to estimate corrected standard errors within a logistic regression model, taking into account the auto-correlated binary observations within individuals. I use R1.5.1 on Mac OS X (10.2). Thanks, Christof

Hello: My dataset set contains several thousand rows of data, with each row containing information for a house. The variables include the sale price of the house, the quarter and year of sale, the attributes of the house, and the attributes of the neighborhood and the city in which the house is located. The data is for a 10-year period. No house is repeated in the dataset. In summary, the dataset

Is anyone aware of a procedure to apply Newey-West corrections for autocorrelation to a SUR regression model? The SANDWICH package seems to be applicable only to LM or GLM models. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric at auburn.edu

Dear all, I am looking for an equivalent to the "newey2"-extension in Stata, in order to compute Newey-West HAC standard errors in a regression using panel data. I would be very grateful for advice which R-package could do this. I thank you very much in advance. Dirius

I want to calculate Newey West robust standard error using NeweyWest. Comparing the results to what I get in STATA, in order to get the same results in I need to specify "prewhite=0". Can someone explain what this prewhite command means? Thanks [[alternative HTML version deleted]]

In the lm function the summary(lmobject) we have adjusted.r square and f statistics Do we have similar to the pls package and how to get it -- View this message in context: http://r.789695.n4.nabble.com/R-square-and-F-stats-in-PLS-tp3924484p3924484.html Sent from the R help mailing list archive at Nabble.com.

Hi Please let me know if we can store the linear model object in the data base and retrive the object and output from them Data<- read.csv("C:/FE and RE.csv") Formula="Y~X2+X3+X4 lmobject = lm(formula=Formula,data=Data) can i store the lm object in the database and and is it possible to retrive it and get the summary information -- View this message in context:

Hi, I am moving from Windows XP to Ubuntu 6.10 and installed R 2.4.0. When I run eg plot.lm (things work fine with plot.default - eg plot(rnorm(30),rnorm(30))) plot(lmobject) I can get the first plot and then this message: Hit <Return> to see next plot: Error in text.default(x, y, labels.id[ind],cex=cex, xpd=TRUE, : could not find any X11 fonts Check that the Font Path is correct

Dear all, I am working on a large dataset and need to use biglm() to perform OLS regressions. I have detected significant ARCH effects which I try to account for using the Newey-West correction. So far, I have worked with NeweyWest() in the sandwich package. NeweyWest() however seems to be unable to handle an object of class "biglm". Looking into the code, I figured out that

Dear R-users, I would like to compute a robust covariance matrix of two series of realizations of random variables: ###Begin Example### data <- cbind(rnorm(100), rnorm(100)) model <- lm(data ~ 1) vcov(model) library(sandwich) NeweyWest(model) #produces an error ###End Example### NeweyWest() produces an error but sandwich(), vcovHAC(), kernHAC, weave(),... do not produce any errors. It

Hi useRs, I had posted about Adobe FLEX talking to R for rich visualisation. Reply from Jeffery Horner contained links to the revolution-computing.com webpage which had information pertaining to the Bay Users R group Meetup on Web Dashboards with R. I have a very specific project that I need to implement. I wish to use the graphics capabilities provided by Adobe FLEX to visualise outputs from R.

Hi All, I am using R 2.11.0 on a Ubuntu machine. I estimated a model using "tsls" from the package "sem". Is there a way to get Newey West standard errors for the parameter estimates? When estimating the model by OLS, I used "NeweyWest" from the package "sandwich" to get HAC standard errors. But, I am not able to use the same method with the results of the

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both

# Using Moving/Rolling Windows, here we do an OLS Regression with corrections for #Heteroscedasticity and Autocorrelations (HAC) using Newey West Method. This code is a #extension of Ajay Shah?s code for moving windows simple OLS regression. # The easiest way to adjust for Autocorrelations and Heteroscedasticity in the OLS residuals is to #use the coeftest function that is included in the

Dear R experts, I am posting this question on behalf of a Japanese R user who wants to know how to change the siginificant codes default. As you know, R's default significant codes are: Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 But he says that it is usual in economics to give codes such as `***' for 0.01, `**' for 0.05 and `*' for