Best subsets regression using LP-norms with 1≤p<∞

Manfred Precht; H. Redinger

doi:10.1007/BF02933549

Best subsets regression using L_P-norms with 1≤p<∞

Manfred Precht, H. Redinger

Life Sciences

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

Abstract

This paper describes an algorithm for determining the best subset of k variables in regression problems using any L_P-norm with 1≤p<∞. The procedure is based on partial enumeration. It also makes a suggestion for finding the equation with least prediction error.

Originalsprache	Englisch
Seiten (von - bis)	128-134
Seitenumfang	7
Fachzeitschrift	Statistische Hefte
Jahrgang	22
Ausgabenummer	2
DOIs	https://doi.org/10.1007/BF02933549
Publikationsstatus	Veröffentlicht - Juni 1964

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10.1007/BF02933549

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abstract = "This paper describes an algorithm for determining the best subset of k variables in regression problems using any LP-norm with 1≤p<∞. The procedure is based on partial enumeration. It also makes a suggestion for finding the equation with least prediction error.",

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