similar to: Goodness of fit with robust regression

Dear R-list members, I'm using the 'effects' package to plot a graph with fixed values. For some reason, I cannot change the label for the 'x' axis using 'xlab=""'. The usual commands work for the y axis and for the main title. My last attempt used the following syntax: model.effects<-(all.effects(model.1)) plot (model.effects, main="Figure

Dear List members, I am runnning a logistic regression that includes sample weights (expressed by a variable called WEIGHT) using glmob (from robustbase). My model looks like this: B12<-glmrob(SERE~COMP+COM,family=binomial,weights=WEIGHT) When I include the weights, my standard error columns, as well as the p-values, show only NAs. If I exclude weights=WEIGHTS,

Dear All, When I run rlm to obtain robust standard errors, my output does not include p-values. Is there any reason p-values should not be used in this case? Is there an argument I could use in rlm so that the output does include p-values? Thanks in advance, Celso [[alternative HTML version deleted]]

I am trying to get robust standard errors in a logistic regression. Is there any way to do it, either in car or in MASS? Thanks for the help, Celso [[alternative HTML version deleted]]

Hello. I've got a dataset that may have outliers in both x and y. While I am not at all familiar with robust regression, it looked like the function lmrob in package robustbase should handle this situation. When I try to use it, I get: Too many singular resamples Aborting fast_s_w_mem() Looking into it further, it appears that for an indicator variable in one of my interaction terms, 98%

Dear List members, I am having a problem importing SPSS files. For some reason I do not understand, the variables in the data set come into R with different lengths, which seems to make regression analysis impossible. The strangest thing is this: it SOMETIMES work. I ran the same commands (always pasting the same thing from RWinEdt) yesterday, and, although it took a long time for

Hi, I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter p so that the effect of outliers is minimized? As a part of the estimation process, I also need to know which are the outliers in the data. I found glmrob which does robust estimation of Poisson and binomial random variables but not geometric

I'm looking for something in R to fit a multivariate linear model robustly, using an M-estimator or any of the myriad of other robust methods for linear models implemented in robustbase or methods based on MCD or MVE covariance estimation (package rrcov). E.g., one can fit an mlm for the iris data as: iris.mod <- lm(cbind(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) ~ Species,

Dear List, I apologize in advance if this is silly. I tried to replicate an analysis I did previously in SPSS using R, and was surprised to find different results. So my question is: shouldn't the following SPSS syntax REGRESSION DEPENDENT INC89 /METHOD=ENTER hiedyrs experien SE93rec. Yeld the same results of the following R command modelB<-lm(INC89~HIEDYRS+EXPERIEN+SE93REC) I

Lista dos aprovados em vestibular Junqueiro: Vale de S?o Domingos: ANA L?CIA MENDES DOS SANTOS, LUANA FELIX BIE, FRANCISCO PAULO DE OLIVEIRA MESQUITA, POLLIANA BRASILIANA DE SIQUEIRA, JO?O CARLOS MOREIRA DE CARVALHO, DANIELE SILVA OLIVEIRA, MARIA JOS? BATISTA LEITE, J?SSICA MAYARA P. PAULINO. SOLANGE FERREIRA ANDRADE, BRENA RODRIGUES MACIEL, LUIS FABRICIO DE FREITAS SOUZA, H?LIO BARROS FERREIRA,

You need to pay attention to the documentation more closely. If you don't know what something means, that is usually a signal that you need to study more... in this case about the difference between an input variable and a design (model) matrix. This is a concept from the standard linear algebra formulation for regression equations. (Note that I have never used RobPer, nor do I regularly

R-experts, I have fitted many different lines. The fast-tau estimator (yellow line) seems strange to me?because this yellow line is not at all in agreement with the other lines (reverse slope, I mean the yellow line has a positive slope and the other ones have negative slope). Is there something wrong in my R code ? Is it because the Y variable is 1 vector and should be a matrix ? Here is the

Dear R-experts, Here below my reproducible R code. I want to add many straight lines to a plot using "abline" The last fit (fast Tau-estimator, color yellow) will not appear on the plot. What is going wrong ? Many thanks for your reply. ########## Y=c(2,4,5,4,3,4,2,3,56,5,4,3,4,5,6,5,4,5,34,21,12,13,12,8,9,7,43,12,19,21)

Dear all, I have been using rlm() for robust regression. Could someone please suggest an appropriate measure of goodness-of-fit [1]? All I've found after trawling the web, literature databases, and previous r-help posts, is the "robust R^2" on pp. 362-363 of the S-plus manual, which is available at http://web.mit.edu/afs/athena/software/splus_v7.0/www/statman1.pdf (7.57 MB)

Hi, i. After estimating some coefficients using robust regression with rlm() or lqs(), I wonder if there exist some measures of the goodness-of-fit as those for standard linear model(R2)... or evenly if it's a statistics non-sense to look for since I do not find any mention of that in differents chapters on robust and resistant regression or in severals R documentation (Fox, Ripley and

On 31/03/2018 11:57 AM, varin sacha via R-help wrote: > Dear R-experts, > > Here below my reproducible R code. I want to add many straight lines to a plot using "abline" > The last fit (fast Tau-estimator, color yellow) will not appear on the plot. What is going wrong ? > Many thanks for your reply. > It's not quite reproducible: you forgot the line to create

Dear R-experts, I am trying to do cross-validation for different models using the cvTools package. I can't get the CV for the "FastTau" and "hbrfit". I guess I have to write my own functions at least for hbrfit. What is going wrong with FastTau ? Here below the reproducible example. It is a simple toy example (not my real dataset) with many warnings, what is important to

Lista dos aprovados em concurso Matriz de Camaragibe: Ant?nio Jo?o: ADEL?ENNE KIRLEY, JULIANA RODRIGUES ALVES, ERICH DOUGLAS MOREIRA CHAVES, MAYSA RAQUEL DA SILVA, JO?O CARLOS MOREIRA DE CARVALHO, CARLOS ALEXANDRE SILVA DE LIMA, MANOEL LEYVSON MACHADO MATOS, IANN MARZZO SAMPAIO LIBOS. ROBERTO BEZERRA FERREIRA, DIONE MARIA DA SILVA, MARIANA COSTA OLIVEIRA, JORGE ROBERTO PRUDENCIO NASCIMENTO,

Hello, I'm trying to use the GSM codec with Nufone H323 but it's not working. Does somebody has some idea? Have I missed something? Thanks!! Celso Fassoni Some additional info: (I'm using CVS-HEAD - downloaded today) monkey:~# cat /etc/asterisk/h323.conf [general] port = 1720 bindaddr = 192.168.0.100 ; this SHALL contain a single, valid IP address for this machine

Dear R-experts, I guess I have a problem with my fast function (fast tau estimator) here below. Indeed, zero errors look highly suspicious. I guess there is a bug in my R code. How could I correct my R code ? # install.packages( "robustbase" ) # install.packages( "MASS" ) # install.packages( "quantreg" ) # install.packages( "RobPer" ) #