search for: welsch

...ficients(rlm(y~1)) (Intercept) 5.9204 I was surprised to get two different results. The function huber() works directly with the definition whereas rlm() uses iteratively reweighted least squares. My surprise is because I vaguely remember @ARTICLE{hw77, author = {Holland, P. W. and Welsch, R. E.}, title = {Robust Regression using Iteratively Reweighted Least-Squares}, journal = {Communications in Statistics: Theory and Methods}, volume = {A6(9)}, number = {}, pages = {813-827}, year = {1977} } as saying that the two methods were equivalent. Obviously they...

...icients(summary(lm(fitted(m1)~d1$R)))[2,2] #SE of slopes se2<-coefficients(summary(lm(fitted(m2)~d1$R)))[2,2] df1<-df.residual(lm(fitted(m1)~d1$R)) #D. of f. df2<-df.residual(lm(fitted(m2)~d1$R)) kk<-function(se1,se2,df1,df2){(se1^2+se2^2)^2/(se1^4/(df1-1)+se2^4/(df2-1))} #D. of f. for Welsch test tt<-function(s1,s2,se1,se2){(s1-s2)/sqrt(se1^2+se2^2)} pp<-function(s1,s2,se1,se2,df1,df2){2*pt(-abs(tt(s1,s2,se1,se2)),df=kk(se1,se2,df1,df2))} pp(s1,s2,se1,se2,df1,df2) # p-value ## Theoretical line s3<-0.75 se3<-0 df3<-0 pp(s1,s3,se1,se3,df1,df3) # p-value pp(s2,s3,se2,se...

...he X matrix. B = ROBUSTFIT(X,Y,'WFUN',TUNE) uses the weighting function 'WFUN' and tuning constant TUNE. 'WFUN' can be any of 'andrews', 'bisquare', 'cauchy', 'fair', 'huber', 'logistic', 'talwar', or 'welsch'. Alternatively 'WFUN' can be a function that takes a residual vector as input and produces a weight vector as output. The residuals are scaled by the tuning constant and by an estimate of the error standard deviation before the weight function is called. 'WFUN'...

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Dear all, How can I test for collinearity in the predictor data set for multiple linear regression. Thanks Alex [[alternative HTML version deleted]]

Hi All, Is the Levenberg-Marquardt algorithm available in R. This method combines the steepest descent algorithm and Newton's method. Thanks in Advance, Dermot MacSweeney. ************************************************************** Dermot MacSweeney NMRC, Email: dsweeney at nmrc.ucc.ie Lee Maltings, Tel: +353 21 904178 Prospect Row, Fax: +353 21 270271 Cork, WWW:

Dear list, I want to perform a logistic regression analysis with multiple categorical predictors (i.e., a logit) on some data where there is a very definite relationship between one predicator and the response/independent variable. The problem I have is that in such a case the p value goes very high (while I as a naive newbie would expect it to crash towards 0). I'll illustrate my problem

Short version If I have a data frame X and I suspect that there is a dependency between the columns how do I confirm that, and how do I tell which subset of columns is involved? ================================== Long version A colleague had been trying to use the SPSS RELIABILITY procedure. It told her that the determinant of the matrix was small. She asked me what that meant and I told her

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

While talking about my RailsConf presentation with Ben Wiseley, he suggested writing a book on the same topic... so I did! The Money Train is an e-book about building e-commerce sites using Ruby on Rails. Read my blog entry about it at http://www.bencurtis.com/archives/ 2006/06/rails-e-commerce-e-book/ or head to http:// www.agilewebdevelopment.com/book to dive right in. As always, a big