RT Journal Article
T1 An algorithm for robust linear estimation with grouped data
A1 Rivero, Carlos
A1 Valdés Sánchez, Teófilo
AB 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 class of the strongly unimodal distributions, either symmetrical or non-symmetrical. Finally, the variance of the errors is unknown. Under these circumstances the algorithm is not only capable of estimating the parameters (slopes and error variance) of the linear model, but also the asymptotic covariance matrix of the linear parameters. This opens the possibility of making inferences in terms of either multiple confidence regions or hypothesis testing
PB Elsevier Science
SN 0167-9473
YR 2008
FD 2008-12-15
LK https://hdl.handle.net/20.500.14352/50484
UL https://hdl.handle.net/20.500.14352/50484
LA eng
NO MEC
DS Docta Complutense
RD 27 abr 2024