Fonts have had trends throughout their history, not only in when they were invented but also usage and popularity. In this paper, we attempt to specifically find the font using robust regression on a large collection of text images. We utilize movie posters as source fonts for task because can represent time periods by release date. addition, are documents that carefully designed wide range fon...

Heteroskedastic regression data are modelled using a parameterized variance function. This procedure is robustified using a method with high breakdown point and high efficiency, which provides a direct link between observations and the weights used in model fitting. This feature is vital for the application, the analysis of international trade data from the European Union. Heteroskedasticity is...

It is known that when there are heavy-tailed errors or outliers in the response, the least squares methods may fail to produce a reliable estimator. In this paper, we proposed a generalized Huber criterion which is highly flexible and robust for large errors. We applied the new criterion to the bridge regression family, called robust and sparse bridge regression (RSBR). However, to get the RSBR...

Instrumental variable (IV) estimation typically requires the user to correctly specify the relationship between the regressors and the outcome to obtain a consistent estimate of the effects of the treatments. This paper proposes doubly robust IV regression estimators that only require the user to either correctly specify the relationship between the measured confounding variables (i.e., include...

This the problem maximum asymptotic bias of regression estimates over a-contamination for the joint of the response carriers. Two classes of estimates are treated: (1) Msestimates with bounded function p applied to the scaled residuals, using a very general class of scale estimates, and (2) Bounded influence function type generalized M-estimates. Estimates in the first class are oblta1rled as p...