Results 1 - 10 of 62

Sieve inference on . . .

by Xiaohong Chen , Zhipeng Liao , Yixiao Sun , 2012
"... The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we establish a ..."
Abstract - Add to MetaCart
The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we establish

Large Sample Sieve Estimation of Semi-Nonparametric Models

by Xiaohong Chen - Handbook of Econometrics , 2007
"... Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite dimensional parameter spaces that may not be compact. The method o ..."
Abstract - Cited by 185 (19 self) - Add to MetaCart
extremum estimates, convergence rates of the sieve M-estimates, pointwise normality of series estimates of regression functions, root-n asymptotic normality and efficiency of sieve estimates of smooth functionals of infinite dimensional parameters. Examples are used to illustrate the general results.

On the Small Sieve. I. Sifting by Primes

by P Erdős, I Z. Ruzsa, Communicated H. Zassenhaus , 1978
"... The main object of the paper is to prove that if P is a set of primes with sum of reciprocals _<K, then the number of natural numbers up to x, divisible by no element of P, is _>cx, where c is a positive constant depending only on K. A lower estimate is given for c and a similar result is achi ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
The main object of the paper is to prove that if P is a set of primes with sum of reciprocals _<K, then the number of natural numbers up to x, divisible by no element of P, is _>cx, where c is a positive constant depending only on K. A lower estimate is given for c and a similar result

An Evaluation of the Sieving Device YASD for 1024-bit Integers?

by Naoyuki Hirota, Tetsuya Izu, Noboru Kunihiro, Kazuo Ohta
"... Abstract. In 2004, Geiselmann and Steinwandt proposed a hardware design “YASD ” for the sieving step in the number field sieve (NFS) method of integer factorization. This design is very attractive since its regular structure is suitable for implementation, however, its perfor-mance evaluation for 10 ..."
Abstract - Add to MetaCart
for 1024-bit integers was not studied. This paper at-tempts to evaluate the performance of YASD for 1024-bit integers based on the same assumptions of the orginal YASD. In our estimation, YASD for 1024-bit integers requires at least 16 years with cost 10M dollars. 1

A SIEVE M-THEOREM FOR BUNDLED PARAMETERS IN SEMIPARAMETRIC MODELS, WITH APPLICATION TO THE EFFICIENT ESTIMATION IN A LINEAR MODEL FOR CENSORED DATA

by Ding, Bin Nan
"... In many semiparametric models that are parameterized by two types of parameters—a Euclidean parameter of interest and an infinite-dimensional nuisance parameter—the two parameters are bundled together, that is, the nuisance parameter is an unknown function that contains the parameter of interest as ..."
Abstract - Cited by 6 (3 self) - Add to MetaCart
as part of its argument. For example, in a linear regression model for censored survival data, the unspecified error distribution function involves the regression coefficients. Motivated by developing an efficient estimating method for the regression parameters, we propose a general sieve M

Abstract. We solve Landau’s four unattackable problems, including Goldbach Conjecture and Twin Prime Conjecture through sieve method. At the 1912 Fifth International Congress of Mathematicians (Cambridge),

by Chengyan Liu , 1999
"... Prime Conjecture; for each n, there is a prime p such that n 2 < p < (n+1) 2; there are infinitely many primes p of the form p = n 2 +1. As Erdős [6, preface] maintained five years ago, we still do not have a satisfactory solution for each of them. For large N, let A = {m | m ∈ Z,m ≤ N}, P = { ..."
Abstract - Add to MetaCart
= {p | p ∈ A,p prime}, and m = g(p) , (1) such that m ∈ A, m ̸ ∈ P0, p ∈ Pz = {p | p ∈ P,2 < p ≤ z < N}, P0 a desired set. A rudimentary sieve associated with Eratosthenes employs Feature M. Screening out m ̸ ∈ P through (1) by p ∈ P √ N. However, since its residue term is proportionate to card

Critical Evaluation of the Use of Laser Diffraction for Particle-Size Distribution Analysis

by G. Eshel, G. J. Levy, U. Mingelgrin, M. J. Singer
"... ABSTRACT �m) by wet sieving from the clay and silt (particles �50 Determination of soil particle-size distribution (PSD) by sieving, hydrometer, and pipette methods as well as by laser diffraction (LD) �m). The sand fraction is determined by drying and weighing the material remaining on the sieve. T ..."
Abstract - Cited by 20 (2 self) - Add to MetaCart
ABSTRACT �m) by wet sieving from the clay and silt (particles �50 Determination of soil particle-size distribution (PSD) by sieving, hydrometer, and pipette methods as well as by laser diffraction (LD) �m). The sand fraction is determined by drying and weighing the material remaining on the sieve

Semi-Nonparametric Interval-Censored Mixed Proportional Hazard Models: Identification and Consistency Results”, Econometric Theory 24

by Herman J. Bierens, Comments Of Aleks, R Vashchilko, Yuichi Kitamura , 2008
"... In this paper I propose to estimate distributions on the unit interval semi-nonparametrically using orthonormal Legendre polynomials. This approach will be applied to the interval censored mixed proportional hazard (ICMPH) model, where the distribution of the unobserved heterogeneity is modeled semi ..."
Abstract - Cited by 12 (6 self) - Add to MetaCart
semi-nonparametrically. Various conditions for the nonparametric identification of the ICMPH model are derived. I will prove general consistency results for M estimators of (partly) non-Euclidean parameters under weak and easy-to-verify conditions, and specialize these results to sieve estimators

Lectures on Statistical Learning Theory

by Gábor Lugosi, J. Shawe-taylor, P. L. Bartlett, R. C. Williamson, M. Anthony Structural , 2000
"... art. From model selection to adaptive estimation. In E. Torgersen D. Pollard and G. Yang, editors, Festschrift for Lucien Le Cam: Research papers in Probability and Statistics, pages 5587. Springer, New York, 1997. [78] L. Birg and P. Massart. Minimum contrast estimators on sieves: exponential bound ..."
Abstract - Add to MetaCart
and C.R. Hwang. Nonparametric maximum likelihood estimation by the method of sieves. Annals of Statistics, 10:401414, 1982. [82] M. Kearns, Y. Mansour, A.Y. Ng, and D. Ron. An experimental and theoretical comparison of model selection methods. In Proceedings of the Eighth Annual ACM Workshop

Low Density Lipoproteins of Chicken, Turkey and Quail Egg Yolk

by Wayne L. Bacon, Keith I. Brown, Margery, A. Musser , 1972
"... ABSTRACT The major low density lipoprotein fraction (LDF) of chicken, turkey, and quail egg yolk has been isolated by preparative centrifugation and the molecular weight estimated by molecular sieve chromatography. In addition, rate zonal density gradient centrifugation has been used to examine the ..."
Abstract - Add to MetaCart
ABSTRACT The major low density lipoprotein fraction (LDF) of chicken, turkey, and quail egg yolk has been isolated by preparative centrifugation and the molecular weight estimated by molecular sieve chromatography. In addition, rate zonal density gradient centrifugation has been used to examine
Results 1 - 10 of 62