search for: sandwich

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. Wh...

Dear useRs, a new version 2.0-0 of the sandwich package for estimating sandwich covariance matrices is available from the CRAN mirrors. The tools for computing heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators, including the Eicker-Huber-White estimator) have been generalized ove...

Hello Is there any function to calculate White's standard errors in R in an NLS regression. The sandwich and car package do it but they need an lm object to calculate the error's. Does anyone have idea how to do it for an NLS object ? Regards The woods are lovely, dark and deep But I have promises to keep And miles before I go to sleep And miles before I go to sleep ----- [[alternative HTML ver...

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car packag...

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car packag...

Hi, I would like to estimate coefficients using poisson regression and then get standard errors that are adjusted for heteroskedasticity, using a complex sample survey data. Then I will calculate prevalence ratio and confidence intervals. Can sandwich estimator of variance be used when observations aren?t independent? In my case, observations are independent across groups (clusters), but not necessarily within groups. Can I calculate the standard errors with robust variance, in complex sample survey data using R? Outputs: design_tarv<-...

...ors, and potentially heteroskedasticity. The Ruppert et al textbook on semiparametric regression uses GLS to account for correlated errors. I haven't really used GLS much and I don't think it solves the autocorrelation problem. I'm more accustomed to using a cluster-robust "sandwich" estimator: (X'X)^{-1} (sum_j(X_j' e_j e_j' X_j)) (X'X)^{-1} In a penalized spline context, this would be something like the following: (X'X+\lambda K)^{-1} (sum_j(X_j' e_j e_j' X_j)) (X'X+\lambda K)^{-1} (where J are clusters -- units on whom obser...

Is there a way of reading in a file in a way that each line becomes a vector: for example: meals.txt breakfast bacon eggs sausage lunch sandwich apple marsbar crisps dinner chicken rice custard pie I want to read in this file and end up with 3 different vectors, one called breakfast which contains "bacon", "eggs", sausage" One called lunch with "sandwich", "apple"... etc So...

...$coef[,1]) > but do not see how to implement confidence intervals based > on "robust error variances" using the output in GLM. Thanks for the link to the data. Here's my best guess. If you use the following approach, with the HC0 type of robust standard errors in the "sandwich" package (thanks to Achim Zeileis), you get "almost" the same numbers as that Stata output gives. The estimated b's from the glm match exactly, but the robust standard errors are a bit off. ### Paul Johnson 2008-05-08 ### sandwichGLM.R system("wget http://www.ats.ucla.edu...

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

Is it possible to get the empirical (sandwich) S.E. estimates for the fixed effects in lme () (thus allowing possibly correlated errors within the group)? In SAS you can get it by the 'empirical' option to PROC MIXED. Cheers, Michael -- Na (Michael) Li, Ph.D. Division of Biostatistics A443 Mayo Building, MMC...

...ndard errors for that. In particular, I am worried about potential serial correlation for a given individual (not so much about correlation in the cross section). >From the documentation, it looks as if the vcovHC that comes with plm does not seem to do autocorrelation, and the NeweyWest in the sandwich package says that it expects a fitted model of type "lm" or "glm" (it says nothing about "plm"). How can I estimate the model and get robust standard errors? Thanks for your help. Max

Dear R-help, I have a four-part question about regression, matrices, and sandwich package. 1) In the sandwich package, I would like to better understand the meat() function. >From the bread() documentation, for a simple OLS regression, bread() returns (1/n * X'X)^(-1) That is, for a simple regression (per the documentation on bread()): MyLM <- lm(y ~ x) bread(MyLM)...

Dear R-Users: I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works...

...er of 'events' that occurred since the previous visit. ~50k rows, ~2k unique subjects so ~25 rows/visits per subject, some have 50 some have 3 or 4. In STATA there is an adjustment for the fact that you have multiple rows per subject, in that you can produce robust standard errors using sandwich estimators, to control for the fact there is a correlation structure within each subjects set of visits. This function is reasonably straight forward, however I'm trying to find something similar in R. http://www.stata.com/help.cgi?nbreg http://www.stata.com/help.cgi?vce_option I'll admi...

...don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my function. As an example: here is a clustering function I wrote: cl <- function(dat, na.rm = TRUE, fm, cluster){ attach( dat , warn.conflicts = F) library(sandwich) library(lmtest) M <- length(unique(cluster)) N <- length(cluster) K <- fm$rank dfc <- (M/(M-1))*((N-1)/(N-K)) uj <- data.frame(apply(estfun(fm),2, function(x) data.frame(tapply(x, cluster, sum)) ) ); vcovCL <- dfc*sandwich(fm, meat=crossprod(uj)/N) coeftest(fm, vcovCL) }...

Hello, I am trying to extract an estimator for the bread of the sandwich function. I used bread(fitted model) however it seems that I have missed something as an error message "no applicable method for "bread" appears. My fitted model is a Spatial simultaneous autoregressive error model.(errorsarlm in spdep package) Can anyone please tell me what I migh...

...w to R and have only used SPSS befor this (which can't do this at all...). I'm trying to output some regression results to latex. The regressions are normal OLS and I'm trying to output the results with standardized regression coefficients and t-statistics based on "Huber-White sandwich estimator for variance". The final result should be one big table for several regressions with this data (and N, R^2). I found the mtable package, which does what I need for lm(...) regressions, lm.beta to output standardized coefficients and package "sandwich" to output the cor...

...have robustness along the "big" dimension is some sort of nonparametric truncation. So: ** 1st (possible) solution ** In my opinion, you would actually need a panel implementation of Newey-West, which is not implemented in 'plm' yet. It might well be feasible by applying vcovHAC{sandwich} to the time-demeaned data but I'm not sure; in this case, vcovHAC should be applied this way (here: the famous Munnell data, see example(plm)) > library(plm) > fm<-log(gsp)~log(pcap)+log(pc)+log(emp)+unemp > data(Produc) > ## est. FE model > femod<-plm(fm, Produc) > #...

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 entire other package just to use a single gene...