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Linear Statistical Inference and its Applications


Linear Statistical Inference and its Applications


Wiley Series in Probability and Statistics, Band 22 2. Aufl.

von: C. Radhakrishna Rao

156,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 25.09.2009
ISBN/EAN: 9780470317143
Sprache: englisch
Anzahl Seiten: 656

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Beschreibungen

"C. R. Rao would be found in almost any statistician's list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory."<br /> -W. G. Cochran<br /> <br /> "[C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science."<br /> -B. Efrom<br /> <br /> Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost works in statistical inference in the literature. Incorporating the important developments in the subject that have taken place in the last three decades, this paperback reprint of his classic work on statistical inference remains highly applicable to statistical analysis. Presenting the theory and techniques of statistical inference in a logically integrated and practical form, it covers:<br /> * The algebra of vectors and matrices<br /> * Probability theory, tools, and techniques<br /> * Continuous probability models<br /> * The theory of least squares and the analysis of variance<br /> * Criteria and methods of estimation<br /> * Large sample theory and methods<br /> * The theory of statistical inference<br /> * Multivariate normal distribution<br /> <br /> <br /> Written for the student and professional with a basic knowledge of statistics, this practical paperback edition gives this industry standard new life as a key resource for practicing statisticians and statisticians-in-training.
Algebra of Vectors and Matrices.<br /> <br /> Probability Theory, Tools and Techniques.<br /> <br /> Continuous Probability Models.<br /> <br /> The Theory of Least Squares and Analysis of Variance.<br /> <br /> Criteria and Methods of Estimation.<br /> <br /> Large Sample Theory and Methods.<br /> <br /> Theory of Statistical Inference.<br /> <br /> Multivariate Analysis.<br /> <br /> Publications of the Author.<br /> <br /> Author Index.<br /> <br /> Subject Index.
<b>C. RADHAKRISHNA RAO</b> is a former director at the Indian Statistical Institute and a Professor Emeritus in the Department of Statistics at Pennsylvania State University. For his academic achievements, Dr. Rao has received numerous awards. A past president of the International Statistical Institute and other leading statistical organizations, Dr. Rao has been made a Fellow of the Royal Society (U.K. Academy of Sciences), a Member of the U.S. National Academy of Sciences, a Fellow of the American Academy of Arts and Sciences, the Indian National Science Academy, and the Third World Academy of Sciences, and a Foreign Member of the Lithuanian Academy of Sciences.
"C. R. Rao would be found in almost any statistician’s list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory."<br />—<b>W. G. Cochran</b> <p>"[C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science."<br />—<b>B. Efrom</b></p> <p>Translated into six major languages of the world, C. R. Rao’s Linear Statistical Inference and Its Applications is one of the foremost works in statistical inference in the literature. Incorporating the important developments in the subject that have taken place in the last three decades, this paperback reprint of his classic work on statistical inference remains highly applicable to statistical analysis. Presenting the theory and techniques of statistical inference in a logically integrated and practical form, it covers:</p> <ul> <li>The algebra of vectors and matrices</li> <li>Probability theory, tools, and techniques</li> <li>Continuous probability models</li> <li>The theory of least squares and the analysis of variance</li> <li>Criteria and methods of estimation</li> <li>Large sample theory and methods</li> <li>The theory of statistical inference</li> <li>Multivariate normal distribution</li> </ul> <p>Written for the student and professional with a basic knowledge of statistics, this practical paperback edition gives this industry standard new life as a key resource for practicing statisticians and statisticians-in-training.</p>

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