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Methods for Finding Zeros in Polynomials
Lectures on Stochastic Flows and Applications
Educational Psychology by Edward L. Thorndike
The Last Days of Tolstoy by V. G. Chertkov
Globalization and Responsibility
Lectures on Siegel Modular Forms and Representation by Quadratic Forms
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History of the Incas by Pedro Sarmiento de Gamboa
Linear Algebra: Theorems and Applications
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A Short Biographical Dictionary of English Literature
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Dollars and Sense by William Crosbie Hunter
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Algebraic and Geometric Combinatorics (Mathematics Studies)
Posted on 2010-03-15
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More Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression analysis helps make sense of such data in application areas that include engineering, finance, medicine and public health. The book is geared towards researchers and professionals with little background in regression as well as statistically oriented scientists (biostatisticians, econometricians, quantitative social scientists, and epidemiologists) with knowledge of regression and the desire to begin using more flexible semiparametric models.
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