| Title:
|
ASYMPTOTIC THEORY OF NONLINEAR REGRESSION
|
| By: |
A. V. Ivanov |
| Format: |
Hardback |
| List price:
|
£109.99 |
|
We currently do not stock this item, please contact the publisher directly for
further information.
|
|
|
|
|
|
| ISBN 10: |
0792343352 |
| ISBN 13: |
9780792343356 |
| Publisher: |
SPRINGER |
| Pub. date: |
30 November, 1996 |
| Edition: |
1997 ed. |
| Series: |
Mathematics and Its Applications 389 |
| Pages: |
330 |
| Description: |
Presents mathematical results in asymptotic theory on nonlinear regression on the basis of various asymptotic expansions of least squares, its characteristics, and its distribution functions of functionals of Least Squares Estimator. This title indicates conditions for Least Moduli Estimator asymptotic normality. |
| Synopsis: |
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 (). |
| Illustrations: |
VI, 330 p. |
| Publication: |
Netherlands |
| Imprint: |
Springer |
| Returns: |
Returnable |
|
|