General Weak Laws of Large Numbers for Bootstrap Sample Means

Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Nonparametric statistical resampling methods (62G09)

Related Items (1)

A central limit theorem for bootstrap sample sums from non-i.i.d. models

Cites Work

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Laws of large numbers for bootstrapped U-statistics
Strong law for the bootstrap
Necessary conditions for the bootstrap of the mean
Some asymptotic theory for the bootstrap
On the asymptotic accuracy of Efron's bootstrap
On the law of large numbers for the bootstrap mean
Bootstrap methods: another look at the jackknife
Almost sure convergence of bootstrapped means and \(U\)-statistics
On the strong law for arrays and for the bootstrap mean and variance
A survey of limit laws for bootstrapped sums
Rates in the complete convergence of bootstrap means.
The jackknife and the bootstrap for general stationary observations
Unconditional Glivenko-Cantelli-type theorems and weak laws of large numbers for bootstrap
On the unconditional strong law of large numbers for the bootstrap mean
A zero-one law approach to the central limit theorem for the weighted bootstrap mean
Random Graphs and the Strong Convergence of Bootstrap Means
A large deviation principle for bootstrapped sample means
Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
Limit theorems for the ratio of the empirical distribution function to the true distribution function
Chung type strong laws for arrays of random elements and bootstrapping
Complete convergence of bootstrapped means and moments of the supremum of normed bootstrapped sums
On the maximal inequalities for the average of pairwise i.i.d. random variables
On the rate of convergence of bootstrapped means in a Banach space
Almost sure lim sup behavior of bootstrapped means with applications to pairwise i. i. d. sequences and stationary ergodic sequences
The impact of bootstrap methods on time series analysis

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