In this paper we consider some iterative estimation algorithms, which are valid to analyse the variance of data, which may be either non-grouped or grouped with different classification intervals. This situation appears, for instance, when data is collected from different sources and the...

type="main" xml:id="sjos12032-abs-0001" <title type="main">ABSTRACT</title>It has been shown in literature that the Lasso estimator, or ℓ₁-penalized least squares estimator, enjoys good oracle properties. This paper examines which special properties of the ℓ₁-penalty allow for sharp oracle results, and then extends...

An algorithm which is valid to estimate the parameters of linear models under several robust conditions is presented. With respect to the robust conditions, firstly, the dependent variables may be either non-grouped or grouped. Secondly, the distribution of the errors may vary within the wide...