@article {Landaburu:2006:0368-492X:713,
	author = "Landaburu, E. and Pardo, L.",
	title = "Weighted (h,?)-divergences in goodness-of-fit with composite null hypotheses",
	journal = "Kybernetes: The International Journal of Systems & Cybernetics",
	volume = "35",
	number = "5",
	year = "2006",
	abstract = "<B>Purpose</B> ? Proposes a test of goodness-of-fit with composite null hypotheses and weights in the classes based on weighted (&#60;IT&#62;h&#60;/IT&#62;,&#60;IT&#62;?&#60;/IT&#62;)-divergences. <B>Design/methodology/approach</B> ? The weighted (&#60;IT&#62;h&#60;/IT&#62;,&#60;IT&#62;?&#60;/IT&#62;)-divergence between an empirical distribution and the probability of the estimated model is here investigated for large simple random samples. <B>Findings</B> ? The unknown parameters of the model are estimated using minimum (&#60;IT&#62;h&#60;/IT&#62;,&#60;IT&#62;?&#60;/IT&#62;)-divergences estimators with weights as studied in previous works by the authors. <B>Originality/value</B> ? Research makes an important contribution to (&#60;IT&#62;h&#60;/IT&#62;,&#60;IT&#62;?&#60;/IT&#62;)-divergences and their applications in statistical and other areas.",
	pages = "713-725",
	url = "http://www.ingentaconnect.com/content/mcb/067/2006/00000035/00000005/art00009",
	doi = "doi:10.1108/03684920610662467",
	keyword = "Cybernetics, Modelling"
}