Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [rlm]

rlm is an `R` function for robust fitting of linear models in package MASS.

rlm is a function in the MASS package for the R project for statistical computing. "rlm" stands for robust linear model.

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Is a weighted $R^2$ in robust linear model meaningful for goodness of fit analysis?

I estimated a robust linear model in R with MM weights using the rlm() in the MASS package. `R`` does not provide an $R^2$ value for the model, but I would like to have one if it is a meaningful quantity. I am also interested to know if there is any…
CraigMilligan
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Simultaneous heteroscedasticity and heavy tails in a regression model

I'm trying to create a prediction model using regression. This is the diagnostic plot for the model that I get from using lm() in R: What I read from the Q-Q plot is that the residuals have a heavy-tailed distribution, and the Residuals vs Fitted…
user765195
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Prediction interval for robust regression with MM-estimator

In their book "Robust Statistics", Maronna et al. consider the following model for robust regression: $y_i = \beta x_i + u_i$, where $u_i$ are independent of the $x_i$, and are i.i.d, with finite variance. They go on to provide a robust estimate…
user765195
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How does "rlm" in R decide its "w" weights?

Following user603's advice, I opened a new question thread for this question. For your reference, the original question is here: Pointers to understand "rlm" in R better? My question is: How does "rlm" decide its "w" for each IRLS iteration then?…
Luna
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Can we report an F statistic on a Robust Linear Model with only Fixed Effects?

I'm estimating a fixed effects model using Linear Regression with the Huber weighting function. I included a boxplot of the data. How do we report an F-value and significance for the entire model like I would with the built in OLS Regression (lm)…
myfatson
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Robust regression - differences in approach (rlm and lmrob)?

I am looking to implement robust regression in R for large data (n=~500,000). The two options that come up are lmrob and rlm. When I used lmrob, it gave me the following error: Error in lmrob.S(x, y, control = control) : Fast S large n strategy…
SanMelkote
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Robust regression with Sandwich estimator

I understand that rlm (robust regression) addresses issues of outliers and influential observations, but does not address heteroskedasticity. I have come to learn that heterogenity of variance can be addressed by using functions in the sandwich…
SanMelkote
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What is the default psi function for the rlm (robust regression) function?

What is the default psi function for the rlm (robust regression) function from MASS package? Is it a bisquare function? If not, may I know what psi function it gives out by default if I do not specify anything except the y~x formula in it?
Eric
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When is rlm preferred over lm and vice versa? Why R Square should not be considered for models built using rlm?

Both lm and rlm are used for multiple linear regression. rlm stands for robust multiple linear regression and so is considered to treat outliers in a better way. How exactly does rlm and lm work? Which is better? In what circumstances rlm is…
Selvam
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how to assess importance of each predictor in robust linear regression

I have been using rlm() in the MASS library in R with the redescending weights (using MM or Tukey's biweight function). I wanted to find the importance of each predictor in the fitted model. Can someone please point me to a resource on how to go…
user122870
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How to calculate R squared and multiple R squared from rlm output?

I have a question that requires me to find and report the adjusted R^2 and multiple R^2 values from a linear regression model. The problem is that the question only tells me to use rlm() from MASS and nothing about the inbuilt lm() function. The…
XDPlatypus
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How to deal with positive slope vs. deteriorating present data when using rlm in R?

I have a data frame "customers" build of customer id, month and total purchases that month. I have calculated a running slope of total purchases (window of 12 months) for each customer. The thing is, there are customers that the trend of the slope…
Alex
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