Results 11 to 20 of about 9,169 (255)

Differentiable Functionals and Smoothed Bootstrap [PDF]

Annals of the Institute of Statistical Mathematics, 1997
The differentiability properties of statistical functionals have several interesting applications. We are concerned with two of them. First, we prove a result on asymptotic validity for the so-called smoothed bootstrap (where the artificial samples are drawn from a density estimator instead of being resampled from the original data).
Antonio Cuevas, Juan Romo, Cuevas Antonio   +2 more
exaly   +4 more sources

The Missing Censoring Indicator Model and the Smoothed Bootstrap. [PDF]

Comput Stat Data Anal, 2008
For right censored data with missing censoring indicators, sub-density function kernel estimators play a significant role for estimating a survival function. Data-driven bandwidths for computing these kernel estimators are proposed. The bandwidths are obtained as minimizers of certain estimates of the mean integrated squared error (MISE).
Subramanian S, Bean D.
europepmc   +6 more sources

Smoothed Bootstrap Methods for Hypothesis Testing [PDF]

Journal of Statistical Theory and Practice
AbstractThis paper demonstrates the application of smoothed bootstrap methods and Efron’s methods for hypothesis testing on real-valued data, right-censored data and bivariate data. The tests include quartile hypothesis tests, two sample medians and Pearson and Kendall correlation tests.
Tahani Coolen-Maturi, Frank P A Coolen, Coolen-Maturi Tahani   +2 more
exaly   +4 more sources

High-order Coverage of Smoothed Bayesian Bootstrap Intervals for Population Quantiles

Austrian Journal of Statistics, 2023
We characterize the high-order coverage accuracy of smoothed and unsmoothed Bayesian bootstrap confidence intervals for population quantiles. Although the original (Rubin 1981) unsmoothed intervals have the same O(n−1/2) coverage error as the standard ...
David Kaplan, Lonnie Hofmann
doaj   +3 more sources

Smoothed estimator of the periodic hazard function [PDF]

Opuscula Mathematica, 2009
A smoothed estimator of the periodic hazard function is considered and its asymptotic probability distribution and bootstrap simultaneous confidence intervals are derived.
Anna Dudek
doaj   +2 more sources

The Smoothed Bootstrap Fine-Tuning [PDF]

System Safety: Human - Technical Facility - Environment, 2019
Abstract The bootstrap method is a well-known method to gather a full probability distribution from the dataset of a small sample. The simple bootstrap i.e. resampling from the raw dataset often leads to a significant irregularities in a shape of resulting empirical distribution due to the discontinuity of a support.
Renata Dwornicka, Andrii Goroshko, Jacek Pietraszek   +2 more
openaire   +2 more sources

Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation [PDF]

Mathematics, 2022
For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b.
Rebeca Peláez, Ricardo Cao, Juan M. Vilar   +2 more
doaj   +2 more sources

A smoothing and bootstrap-based framework for early outbreak detection. [PDF]

PLoS ONE
Timely detection of infectious disease outbreaks is critical for effective public health response. The effective reproduction number (Rt) is a key metric that captures transmission dynamics and signals the potential onset of outbreaks when it rises above
Lengyang Wang, Yingcun Xia, Ee Hui Goh, Mark Chen   +3 more
doaj   +2 more sources

On confidence intervals centred on bootstrap smoothed estimators [PDF]

Stat, 2019
Bootstrap smoothed (bagged) estimators have been proposed as an improvement on estimators found after preliminary data‐based model selection. Efron derived a widely applicable formula for a delta method approximation to the standard deviation of the bootstrap smoothed estimator. He also considered a confidence interval centred on the bootstrap smoothed
Paul Kabaila, Christeen Wijethunga
exaly   +6 more sources

Avoiding Overfitting dan Overlapping in Handling Class Imbalanced Using Hybrid Approach with Smoothed Bootstrap Resampling and Feature Selection

JOIV: International Journal on Informatics Visualization, 2022
The dataset tends to have the possibility to experience imbalance as indicated by the presence of a class with a much larger number (majority) compared to other classes(minority).
Hartono Hartono, Erianto Ongko
doaj   +3 more sources