Questions tagged [robust]

Robustness in general refers to a statistic's insensitivity to deviations from its underlying assumptions (Huber and Ronchetti, 2009).

408 questions
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Inference using robust statistics

I'm simulating the overall usage of a cluster using historic deployment data. Due to the nature of the simulation, there are some heavy points (i.e. very low overall usage). As a result, the variance ...
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Looking for a Regression Method with way to enfornce a reflection/ flip consistency for input [closed]

I have a set of $N$ dimensional 1D features using which I build a linear a regression model to predict a single scalar value. Say, $\hat{y}(w, x) = w_0 + w_1 x_1 + ... + w_p x_p$ with the regression ...
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Centering input data for Robust PCA (RPCA)?

I know that before running Principal component analys, the input data needs to be centered around its mean (subtract the mean from each keypoint) before running the algorithm. Do I need to center my ...
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Median point vs. number of points

I am trying to assign a binary label to a group of 2D points. Essentially I want to know whether or not the group lies mainly within a certain region in 2D space, such as above a line. I've been ...
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Is there a standard approach for estimating robust multinomial logit models?

I have been reading the "Robust Statistics" book by Morona, Martin and Yohai. To estimate a robust version of logistic regression, they recommend using redescending weighted $M$-estimator. For more ...
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Robust two-sample test with triplicate measurements?

When testing for a difference in mean between two conditions, biologists typically use a $t$-test, and wring their hands endlessly about how to justify removing outliers. Whereas I typically use a ...
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“Forward search” methods for outlier detection etc. in regression

I am reading Robust Diagnostic Regression Analysis by Anthony Atkinson and Marco Riani. They propose a robust "forward search" method for detecting outliers and other problematic data in regression (...
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Using robust regression to detect outliers

Rousseeuw and van Zomeren (1990) propose using robust regression to detect multivariate outliers, particularly in OLS regression. This approach seems to make sense (although I have not studied it in ...
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Placebo Thresholds in a Fuzzy Regression Discontinuity Design

Matsudaira (2008) used test scores to evaluate the impact of summer school attendance on students' performance. In this system, a student that scored less than an arbitrary grade was more likely to be ...
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SPSS ANCOVA with robust standard errors estimates

I am using SPSS version 25 to run an ANCOVA with heteroskedastic-consistent standard errors estimators (HC3 procedure) and I am puzzled by some of the output I get. I am fine with the robust standard ...
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Numerically Distinguish Between Real Correlation and Artifact

I'm looking at correlation for a large number of vectors, and many (about 3000) of these pairwise comparisons appear to have a significant correlation even after Bonferroni correction. Plotting these ...
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Discussion of Robustness

I have to include a discussion of robustness in my report. What are ways to discuss the robustness of my models? I run several logit models. But I don't know how to include something about the ...
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How do I weigh values by their relative frequency and then get an average?

Suppose I have three values that were measured repeatedly in a study. The conditions imply that the values should be close to each other, i.e. ideally three times the same value. The measured ...
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How to calculate the standard average of a set excluding outliers? [closed]

I have a set of numbers, and I need to calculate their average excluding outlier values (which I don't know a priori). It came to mind that many years ago I studied Standard Deviation. Could I apply ...
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Robust analogues of Mean, CV and Skewness

I need to characterize the mean, CV and skewness of my observed data (it is gamma-like distributed). This data is an artifact (outliers) enriched, so I decide to use robust statistics: median, ...
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If we change only one value of a data set, will the mean absolute deviation behave in the same way as standard deviation?

I took the new data as b and the data removed as a and calculated the new mean and used that to find the new mean and deviation in terms of the old. But it gets too complicated and there is no way to ...
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Why robust PCA results change with each run?

According to Filzmoser et al. 2009, the best way to conduct a principal component analysis for compositional data with outliers is: using a robust PCA method and using the isometric log ratio ...
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How to model which fixed effect is most responsible for variation in the DV?

Let's say I have data on firm revenue among multinational firms. I want to test the question of what explains more variation in revenue: firm culture or country-culture. A bit confused as to the ...
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Understanding MCD

I have recently stumpled upon the robust MCD (Minimal Covariance Determinant) Estimator. If I have $n$ datapoints of dimension $p$. Let`s say we want to obtain a robust estimate for the Covariance ...
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Tradeoffs of robust mean measures (trimmed, Huber, cosh, etc)

After recently having delved into the world of robust measures (for location, mean being the classical case), I have had difficulty understanding robust measures' core dynamic. Basically, what are ...
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Robust Regression in MATLAB's robustfit: what is the optimal weight function to tackle heteroskedasticity?

I'm currently performing a linear regression analysis and encountered a fair amount of heteroskedasticity. Increases in predicted values go along with decreases in residual variance. Otherwise, the ...
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Robust distance measure for correlated data

I read a paper in which the authors want to compare the overall predictive accuracy of various predictors on a set of variables by using the Mahalanobis-Distance. However the data is not even ...
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Deconvoluting an ECDF via mixed modeling

I have data with measurement error, $W_i$, with the following structure: $$W_i = \mu + \gamma_i + U_i$$ where $U_i \sim N(0, \sigma^2_i)$, with known $\sigma^2_i$, and $U_i \; \amalg \; \gamma_i$. I ...
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Robust covariance and OGK outlier detection

I'm calculating the robust covariance of a data set in order to use mahalanobis distance for outlier detection. There are few methods to calculate the covariance in the equation. Using the Fast-MCD ...
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Multiple comparison tests after using Robust method (lmrob)

I have some violation of assumptions (normality and equality of variances) is my analysis and I decided to a use robust technique (lmrob function in R). I have a continuous response, one categorical ...
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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. ...