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Robust Statistics Robust statistics is a scientific field, mostly devoted to analyse data with methods which are said robust, so that results are not affected by atypical or influential values, often referred to as outliers.

Does robust mean outlier resistant only?

Applications The Mission of the Center is to develop new methods and disseminate propertied of robust statistics in many applied fields. Robust Analysis of Big Data Data are a new fuel; their collection into growing databases is becoming an endless source of information for many brands. Forward Search The Forward Search is a novel yet powerful method whose development dates back of about 20 years from Ro.

The Robust Statistics Academy Ro. It has been built by a group of statisticians with long-term experience in the robust analysis of big data. Their scientific work is based on the modern usage of statistical models, finely tuned to be robust. The Robust Statistics Academy has the aim of disseminating the properties of robust statistical methods and share their results with other Research Centres and private companies.

Robust statistics

We review the assumptions of one of the most commonly applied models in this journal the general linear model, GLM and the effects of violating them. We then present evidence that psychological data are more likely than not to violate these assumptions. Next, w….


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Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery. Links to this project.

Learning Activities and Teaching Methods

Title Authors. Link other OSF projects. Search all projects Search my projects. This method smooths out additive noise while preserving edge-like features in images.

What Is Robustness in Statistics?

We demonstrate the feasibility of our methods on topography images and microwave S 11 images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion.

Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Download Paper Local Download.