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Asymptotic Theory of Nonlinear Regression - Mathematics and Its Applications 389 (Hardback)

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£109.99
Hardback 330 Pages / Published: 30/11/1996
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Let us assume that an observation Xi is a random variable (r.v.) with values in 1 1 (1R1 , 8 ) and distribution Pi (1R1 is the real line, and 8 is the cr-algebra of its Borel subsets). Let us also assume that the unknown distribution Pi belongs to a 1 certain parametric family {Pi() , () E e}. We call the triple GBPi = {1R1 , 8 , Pi(), () E e} a statistical experiment generated by the observation Xi. n We shall say that a statistical experiment GBPn = {lRn, 8 , P; ,() E e} is the product of the statistical experiments GBPi, i = 1, ... ,n if PO' = P () X ... X P () (IRn 1 n n is the n-dimensional Euclidean space, and 8 is the cr-algebra of its Borel subsets). In this manner the experiment GBPn is generated by n independent observations X = (X1, ... ,Xn). In this book we study the statistical experiments GBPn generated by observations of the form j = 1, ... ,n. (0.1) Xj = g(j, (}) + cj, c c In (0.1) g(j, (}) is a non-random function defined on e , where e is the closure in IRq of the open set e ~ IRq, and C j are independent r. v .-s with common distribution function (dJ.) P not depending on ().

Publisher: Springer
ISBN: 9780792343356
Number of pages: 330
Weight: 1440 g
Dimensions: 235 x 155 x 20 mm
Edition: 1997 ed.

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