similar to: Newey-West and SUR regression models

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

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

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

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 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

Is anyone aware of an R procedure similar to STATA's "heckprob" procedure? "Heckprob" fits maximum likelihood probit models correcting for sample selection bias. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric@auburn.edu [[alternative HTML version deleted]]

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 have weekly time series data with year, month, day, and price variables. The input data set for the weekly series takes the following form: Year month day price 1990 8 20 119.1 1990 8 27 124.5 1990 9 3 124.2 1990 9 10 125.2 1990 9 17 126.6 1990 9 24 127.2 1990 10 1 132.1 1990 10 8 133.3 1990 10 15 133.9 1990 10 22 134.5 1990 10 29 133.9 .. ... ... ... ... ... .... .... 2008 3 3 313.7 2008

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

Can someone direct me to a resource or resources that list the formulae used by R functions (i.e. predict.lm ) to calculate the statistic reported. I am not a programmer and studying the r code is extremely slow going. I have searched r-project.org and all the function help files without success. For example I have attempted to replicate by hand the se.fit calculation from a lm object

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

I am relatively new to R and object oriented programming. I have relied on SAS for most of my data analysis. I teach an introductory undergraduate forecasting course using the Diebold text and I am considering using R in addition to SAS and Eviews in the course. I work primarily with univariate or multivariate time series data. I am having a great deal of difficulty understanding and working with

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

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]]

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

Hi, In one of my packages (maxLik), I would like to add an S3 method, where the generic function (estfun) is defined in another package (sandwich). Everything works fine if my package "Depends" on the other package and I import the generic function "estfun" from the "sandwich" package and define the new method in the NAMESPACE file. However, I prefer not to load the

I am trying to build a package (GWASTools, submitted to Bioconductor) that uses the "sandwich" package. I have references to "sandwich" in DESCRIPTION: Imports: methods, DBI, RSQLite, sandwich, survival, DNAcopy and NAMESPACE: import(sandwich) In the code itself is a call to vcovHC: Vhat <- vcovHC(mod, type="HC0") I have sandwich version 2.2-7 installed.

Hi, I'm using maxlik with functions specified (L, his gradient & hessian). Now I would like determine some robust standard errors of my estimators. So I 'm try to use vcovHC, or hccm or robcov for example but in use one of them with my result of maxlik, I've a the following error message : Erreur dans terms.default(object) : no terms component Is there some attributes

I have an ascii data set of monthly observation starting in Jan 1946 with a header. hstarts 57 65 95 103 103 97 94 . . . Which I read with the following code tab6.1<-ts(read.table(fname, header=TRUE),frequency=12,start=c(1946,1)) I would like to run a time series model with dummy variables for each month. If I had a variable which take values from 1 to 12 indicating the month I could use