Rate of Convergence in Bootstrap Approximations

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Improving Convergence Rate in the Method of Successive Approximations*

An application of the method of successive approximations for obtaining the solution of a nonlinear integral equation arising from a two-point boundary value problem is illustrated. In particular, we show sufficient conditions under which the convergence rate of the sequence can be improved.

متن کامل

Rate of Convergence of Implicit Approximations for stochastic evolution equations

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...

متن کامل

On the Convergence Rate of Vanishing Viscosity Approximations

Given a strictly hyperbolic, genuinely nonlinear system of conservation laws, we prove the a priori bound ‖u(t, · )− uε(t, · )‖L1 = O(1)(1 + t) · √ ε |ln ε| on the distance between an exact BV solution u and a viscous approximation uε , letting the viscosity coefficient ε → 0. In the proof, starting from u we construct an approximation of the viscous solution uε by taking a mollification u ∗ φ√...

متن کامل

Jackknife Approximations to Bootstrap Estimates

Let T be an estimate of the form Tn = T(F ) where F is the nn n' n sample cdf of n iid observations and T is a locally quadratic functional defined on cdf's. Then, the normalized jackknife estimates for bias, skewness, and variance of Tn approximate closely their bootstrap counterparts. Each of these estimates is consistent. Moreover, the jackknife and bootstrap estimates of variance are asympt...

متن کامل

Slow Convergence in Bootstrap Percolation

In the bootstrap percolation model, sites in an L by L square are initially infected independently with probability p. At subsequent steps, a healthy site becomes infected if it has at least 2 infected neighbours. As (L, p) → (∞, 0), the probability that the entire square is eventually infected is known to undergo a phase transition in the parameter p log L, occurring asymptotically at λ = π2/1...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The Annals of Probability

سال: 1988

ISSN: 0091-1798

DOI: 10.1214/aop/1176991590