similar to: Help with simulation of heteroskedasticity

Displaying 20 results from an estimated 2000 matches similar to: "Help with simulation of heteroskedasticity"

2010 Dec 27
0
Heteroskedasticity and autocorrelation of residuals
Hello everyone, I'm working on a current linear model Y = a0 + a1* X1 + ... + a7*X7 + residuals. And I know that this model presents both heteroskedasticity (tried Breusch-Pagan test and White test) and residuals autocorrelation (using Durbin Watson test). Ultimately, this model being meant to be used for predictions, I would like to be able to remove this heteroskedasticity and residuals
2012 Apr 15
0
correct standard errors (heteroskedasticity) using survey design
Hello all, I'm hoping someone can help clarify how the survey design method works in R. I currently have a data set that utilized a complex survey design. The only thing is that only the weight is provided. Thus, I constructed my survey design as: svdes<-svydesign(id=~1, weights=~weightvar, data=dataset) Then, I want to run an OLS model, so: fitsurv<-svyglm(y~x1+x2+x3...xk,
2010 Mar 22
0
using lmer weights argument to represent heteroskedasticity
Hi- I want to fit a model with crossed random effects and heteroskedastic level-1 errors where inferences about fixed effects are of primary interest. The dimension of the random effects is making the model computationally prohibitive using lme() where I could model the heteroskedasticity with the "weights" argument. I am aware that the weights argument to lmer() cannot be used to
2011 Jul 25
1
predict() and heteroskedasticity-robust standard errors
Hello there, I have a linear regression model for which I estimated heteroskedasticity-robust (Huber-White) standard errors using the coeftest function in the lmtest-package. Now I would like to inspect the predicted values of the dependent variable for particular groups and include a confidence interval for this prediction. My question: is it possible to estimate confidence intervals for the
2011 Nov 23
0
Error using coeftest() with a heteroskedasticity-consistent estimation of the covar.
Hey I am trying to run /coeftest()/ using a heteroskedasticity-consistent estimation of the covariance matrix and i get this error: # packages >library(lmtest) >library(sandwich) #test > coeftest(*GSm_inc.pool*, vcov = vcovHC(*GSm_inc.pool*, method="arellano", > type="HC3")) /Fehler in 1 - diaghat : nicht-numerisches Argument f?r bin?ren Operator/ something like:
2000 Dec 07
2
Heteroskedasticity in R
Hi all, I just discovered R a couple of days ago and I must say it rocks. I've been looking for heteroskedasticity tests and couldn't find any, however. Particularly, I've been told in one of my courses on econometrics of White's method (>< white.test()). The test's statistic is beta / sqrt(W), where W is Var(beta) "? la White", that is the beta(i) matrix is
2011 Nov 24
1
CAPM-GARCH - Regression analysis with heteroskedasticity
Hey Guys, i want to do a CAPM-GARCH model. I didn?t find anything posted online. (If there is something - shame on me - i didn?t find it.) My Problem: What is the difference if I let the residuals ?e? follow a garch process ? How do I do my regression analysis now? I began reading about regression analyis with heteroscedasticity, but didn?t get it. So i started programming. First
2009 Jun 26
1
Heteroskedasticity and Autocorrelation in SemiPar package
Hi all, Does anyone know how to report heteroskedasticity and autocorrelation-consistent standard errors when using the "spm" command in SemiPar package? Suppose the original command is sp1<-spm(y~x1+x2+f(x3), random=~1,group=id) Any suggestion would be greatly appreciated. Thanks, Susan [[alternative HTML version deleted]]
2010 Dec 20
1
After heteroskedasticity correction, how can I get new confidential interval?
I just corrected std.error of my 'model'(Multi Regression). Then how can I get new t and p-values? Isn't there any R command which shows new t and p values? -- View this message in context: http://r.789695.n4.nabble.com/After-heteroskedasticity-correction-how-can-I-get-new-confidential-interval-tp3095643p3095643.html Sent from the R help mailing list archive at Nabble.com.
2020 Jan 13
0
Introducing skedastic: Heteroskedasticity Diagnostics for Linear Regression Models
Dear All, I would like to introduce the above-named new package that is now available on CRAN: https://cran.r-project.org/web/packages/skedastic/index.html The package features numerous 'classical' heteroskedasticity tests (some not previously available in any published R package) as well as one very new test that appeared in the literature only in 2019. Feedback on bugs/issues is most
2020 Jan 13
0
Introducing skedastic: Heteroskedasticity Diagnostics for Linear Regression Models
Dear All, I would like to introduce the above-named new package that is now available on CRAN: https://cran.r-project.org/web/packages/skedastic/index.html The package features numerous 'classical' heteroskedasticity tests (some not previously available in any published R package) as well as one very new test that appeared in the literature only in 2019. Feedback on bugs/issues is most
2004 Jul 21
2
Testing autocorrelation & heteroskedasticity of residuals in ts
Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it
2006 Apr 25
5
Heteroskedasticity in Tobit models
Hello, I've had no luck finding an R package that has the ability to estimate a Tobit model allowing for heteroskedasticity (multiplicative, for example). Am I missing something in survReg? Is there another package that I'm unaware of? Is there an add-on package that will test for heteroskedasticity? Thanks for your help. Cheers, Alan Spearot -- Alan Spearot Department of Economics
2009 Sep 18
1
some irritation with heteroskedasticity testing
Dear all, Trying to test for heteroskedasticity I tried several test from the car package respectively lmtest. Now that they produce rather different results i am somewhat clueless how to deal with it. Here is what I did: 1. I plotted fitted.values vs residuals and somewhat intuitively believe, it isn't really increasing... 2. further I ran the following tests bptest (studentized
2002 Mar 22
3
heteroskedasticity-robust standard errors
I am trying to compute the white heteroskedasticity-robust standard errors (also called the Huber standard errors) in a linear model, but I can't seem to find a function to do it. I know that the design library in S+ has something like this (robcov?), but I have not yet seen this library ported to R. Anyone know if there is already a function built into R to do this relatively simple job?
2006 Sep 29
0
Heteroskedasticity test
The Brown-Forsyth test for homogeneity of variance is included in the HH package, downloadable from CRAN. library(HH) x <- c(rnorm(1000), rnorm(1000, 0, 1.2)) tmp <- data.frame(x=x, group=rep(c("s1","s1.2"), c(1000,1000))) plot.hov(x ~ group, data=tmp) hov(x ~ group, data=tmp)
2013 Apr 05
1
white heteroskedasticity standard errors NLS
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
2012 Sep 18
1
Contradictory results between different heteroskedasticity tests
Hi all, I'm getting contradictory results from bptest and ncvTest on a model calculated by GLS as: olslm = lm(log(rr)~log(aloi)*reg*inv, data) varlm = lm(I(residuals(olslm)^2)~log(aloi)*reg*inv, data) glslm = lm(log(rr)~log(aloi)*reg*inv, data, weights=1/fitted(varlm)) Testing both olslm and glslm with both ncvTest and bptest gives: > ncvTest(olslm) Non-constant Variance Score Test
2006 Apr 24
1
Modelling heteroskedasticity in a multilevel model
Dear list members, I am facing a 3-level model, for which my research hypotheses suggest that the variance of both level-1 and level-2 residuals may be a function of a level-3 variable. To be a bit more clear: I am fitting a longitudinal model for a panel of companies grouped in industries. I suggest that some industry variables may create 'unexpected' shocks at especific points in
2000 Dec 08
0
Re: R-help Digest V2 #283
R-help Digest wrote: > ------------------------------ > > Date: Thu, 07 Dec 2000 18:28:09 +0100 > From: Uwe Ligges <ligges at statistik.uni-dortmund.de> > Subject: Re: [R] Heteroskedasticity in R > > Vincent Leycuras wrote: > > > > Hi all, > > > > I just discovered R a couple of days ago and I must say it rocks. I've been > > looking