similar to: Sorting data for multiple regressions

Hi I am carrying out some logit regressions and want to (a) make sure I'm taking the right approach and (b) work out how to carry out some additional analysis. So, to carry out a logit regression where the dependent variable is a factor db, I use something like: res1_l <- glm(formula = db ~ y1 + + y5, family = binomial(link = "logit")) summary(res1_l) ...which is, I hope

I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution not homoscedasticity is given. I have a two questions: (1) Some sources say robust regression take care of both lack of normal distribution and heteroscedasticity, while others say only of normal distribution. What is true? (2) Are there ways of using robust

Hi there, I have just started using the MASS package in R to run M-estimator robust regressions. The final output appears to only give coefficients, degrees of freedom and t-stats. Does anyone know why R doesn't compute R or R-squared and why doesn't give you any other indices of goodness of fit? Does anyone know how to compute these in R? Sophie -- View this message in context:

Dear list, I am slightly confused about how I can do the following in R. I want to perform robust multiple regression. I?ve used the Boot function in CAR package to find confidence intervals and standard errors. Inadition to these, I want to find the robust estimates for the F test and r-square. Finally, I would like to know the significance levels of bootstrap results. Below I explain

Dear R users, Usually the variance-inflation factor, which is based on R^2, is used as a measure for multicollinearity. But, in contrast to OLS regression there is no robust R^2 available for MM-regressions in R. Do you know if an equivalent or an alternative nmeasure of multicollinearity is available for MM-regression in R? With best regards, Carsten Colombier Dr. Carsten Colombier Economist

Hi All, Could any one tells me if R or S has the capacity to fit nonlinear regression with Huber's M estimation? Any suggestion is appreciated. I was aware of 'rlm' in MASS library for robust linear regression and 'nls' for nonlinear least squares regression, but did not seem to be able to find robust non-linear regression function. Thanks and regards, Ray Liu

Hi, I am working on a multivariate linear regression of the form y = Ax. I am seeing a great dispersion of y w.r.t x. For example, the correlations between y and x are very small, even after using some typical transformations like log, power. I tried with simple linear regression, robust regression and ace and avas package in R (or splus). I didn't see an improvement in the fit and

Can anyone comment or point me to a discussion of the pros and cons of robust regressions, vs. a more "manual" approach to trimming outliers and/or "normalizing" data used in regression analysis?

Hi, I've been using the Matlab robustfit function for linear regressions where I suspect some data points are outliers. Is there an equivalent function in R? Take care, Darren PS, This is the Matlab help on robustfit: >> help robustfit ROBUSTFIT Robust linear regression B = ROBUSTFIT(X,Y) returns the vector B of regression coefficients, obtained by performing robust

Dear list members, I have been doing robust regressions in R, using the MASS package for rlm and robustbase for logistic regressions. I must be doing something wrong, because my output does not include r-squares (or adjusted r-squares), or, in the case of glmrob, -2log likelihoods. Does anyone know how to get an output that includes these? Thanks so much for the help

I have a simple table of data: Result Var1 Var2 Var3 1 0.10 0.78 0.12 0.38 2 0.20 0.66 0.39 0.12 3 0.10 0.83 0.09 0.52 4 0.15 0.41 0.63 0.95 5 0.60 0.88 0.91 0.86 6 -0.02 0.14 0.69 0.94 I am trying to achieve two things: 1) Manipulate this data so that I have the "Result" data unchanged, and all the other data

Unfortunately the proposal here doesn't get rid of process creation, it just changes the process being created from a GnuWin32 one to one that we write ourselves. Happy to entertain suggestions for how to get rid of process creation entirely, but it doesn't seem simple to me. On Tue, Aug 16, 2016 at 11:20 AM Yaron Keren <yaron.keren at gmail.com> wrote: > You can use msys2

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

Dear all, i am doing linear regression with robust error to know the effect of a (x) variable on (y)other if i execute the command i found positive trend. But if i check the effect of number of (x.x1,x2,x3)variables on same (y)variable then the positive effect shwon by x variable turns to negative. so plz help me in this situation. Barjesh Kochar Research scholar

I'm working with 3 different data sets and applying this non-linear regression formula to each of them. nls(Y ~ (upper)/(1+10^(X-LOGEC50)), data=std_no_outliers, start=list(upper=max(std_no_outliers$Y),LOGEC50=-8.5)) Previously, all of the regressions were calculated in Prism, but I'd like to be able to automate the calculation process in a script, which is why I'm trying to move to

That's only if you use git bash, not cmd. On Tue, Aug 16, 2016 at 11:38 AM Reid Kleckner <rnk at google.com> wrote: > One other thing to note is that the dependency problem is going to go away > very soon just a result of moving to git. The normal Windows install of git > comes with all the utilities you need to run the LLVM tests anyway. I > haven't bothered to install

After solving a problem with a sweet little application I discovered (more on that below), I wanted to get some feedback about a potential enhancement for IMAP: standardized, MUA independant, server-side sorting. Currently, there are two basic solutions for sorting: handle it during delivery or handle it in the MUA. However, if you handle it in the MUA, you lose some of the client

lm's "predict" function offers an "interval" parameter to choose between 'confidence' and 'prediction' bands. In the package "robust" and for "lmRob", there is also a "predict" but it lacks such a parameter, and the documented "type" parameter has only "response" offerred. Is there some way of obtaining

Hello, I'm an MD working in an eye clinic. I'm learning by myself to use R for use in my research works and for implementation in a software project. There are some authors who recomends the use of Cox regression as a substitute for Logistic regression (<a href="http://www.biomedcentral.com/1471-2288/3/21.pdf"> Barros AJD, Hirakata VN. BMCMedical Research Methodology, 2003;

On Nov 7, 2011, at 2:00 PM, Bill Wendling wrote: > Good day, LLVMers! > > We are starting on our third (and hopefully last) round of testing for LLVM 3.0. Please visit: > > http://llvm.org/pre-releases/3.0/rc3/ > > for the sources. There are also binaries for Darwin up there, with more to come during the week. Please build this release candidate, test it out on your