Results 11 to 20 of about 719,228 (391)
A subsampled double bootstrap for massive data [PDF]
arXiv, 2015 The bootstrap is a popular and powerful method for assessing precision of estimators and inferential methods. However, for massive datasets which are increasingly prevalent, the bootstrap becomes prohibitively costly in computation and its feasibility is questionable even with modern parallel computing platforms.
Sengupta, Srijan +2 more
arxiv +6 more sources
How to Bootstrap Aalen-Johansen Processes for Competing Risks? Handicaps, Solutions and Limitations [PDF]
arXiv, 2014 Statistical inference in competing risks models is often based on the famous Aalen-Johansen estimator. Since the corresponding limit process lacks independent increments, it is typically applied together with Lin's (1997) resampling technique involving standard normal multipliers.
Dobler, Dennis, Pauly, Markus
arxiv +4 more sources
Smoothed and Iterated Bootstrap Confidence Regions for Parameter Vectors [PDF]
arXiv, 2013 The construction of confidence regions for parameter vectors is a difficult problem in the nonparametric setting, particularly when the sample size is not large. The bootstrap has shown promise in solving this problem, but empirical evidence often indicates that some bootstrap methods have difficulty in maintaining the correct coverage probability ...
Ghosh, Santu, Polansky, Alan M.
arxiv +3 more sources
Evaluating the Effectiveness of Personalized Medicine With Software
Frontiers in Big Data, 2021 We present methodological advances in understanding the effectiveness of personalized medicine models and supply easy-to-use open-source software. Personalized medicine involves the systematic use of individual patient characteristics to determine which ...
Adam Kapelner +5 more
doaj +1 more source
SSRN Electronic Journal, 2011 We propose a methodology for constructing confidence regions with partially identified models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap methodology to deal with sampling uncertainty without reference to the hypothesized economic structure.
Alfred Galichon, Marc Henry
openaire +2 more sources
Analysis of Microbiome Data in the Presence of Excess Zeros
Frontiers in Microbiology, 2017 Motivation: An important feature of microbiome count data is the presence of a large number of zeros. A common strategy to handle these excess zeros is to add a small number called pseudo-count (e.g., 1).
Abhishek Kaul +3 more
doaj +1 more source
UFBoot2: Improving the Ultrafast Bootstrap Approximation
bioRxiv, 2017 The standard bootstrap (SBS), despite being computationally intensive, is widely used in maximum likelihood phylogenetic analyses. We recently proposed the ultrafast bootstrap approximation (UFBoot) to reduce computing time while achieving more unbiased ...
D. T. Hoang +4 more
semanticscholar +1 more source
The Cosmological Bootstrap: Spinning correlators from symmetries and factorization [PDF]
SciPost Physics, 2020 We extend the cosmological bootstrap to correlators involving massless spinning particles, focusing on spin-1 and spin-2. In de Sitter space, these correlators are constrained both by symmetries and by locality.
D. Baumann +4 more
semanticscholar +1 more source
The Bootstrapping Service [PDF]
26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06), 2006 We outline a lightweight architecture to support novel application scenarios for P2P systems. These scenarios include merging and splitting of large networks, or multiplexing relatively short-lived applications over a pool of shared resources. In such scenarios, the architecture needs to be quickly and efficiently (re)generated frequently, often from ...
BABAOGLU, OZALP +2 more
openaire +5 more sources
A comparison of block and semi-parametric bootstrap methods for variance estimation in spatial statistics [PDF]
, 2011 Efron (1979) introduced the bootstrap method for independent data but it cannot be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block ...
Bose +29 more
core +1 more source