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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Journal of Sciences, Islamic Republic of Iran</JournalTitle>
				<Issn>1016-1104</Issn>
				<Volume>17</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2006</Year>
					<Month>03</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Wavelet Based Estimation of the Derivatives of a Density for a Discrete-Time Stochastic Process: Lp-Losses</ArticleTitle>
<VernacularTitle>-</VernacularTitle>
			<FirstPage></FirstPage>
			<LastPage></LastPage>
			<ELocationID EIdType="pii">31695</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
		    <Abstract>We propose a method of estimation of the derivatives of probability density based on wavelets methods for a sequence of random variables with a common one-dimensional probability density function and obtain an upper bound on Lp-losses for such estimators. We suppose that the process is strongly mixing and we show that the rate of convergence essentially depends on the behavior of a special quadratic characteristic.</Abstract>
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</Article>
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