Results 41 to 50 of about 22,043,161 (356)
An extension of the statistical bootstrap model to include strangeness. Implications on particle ratios [PDF]
, 1997 The Statistical Bootstrap Model (SBM) is extended to describe hadronic systems which carry the quantum number of strangeness. The study is conducted in the three-dimensional space of temperature, up-down and strange chemical potentials, wherein the ...
A. Kapoyannis +2 more
semanticscholar +1 more source
Model Error (or Ambiguity) and Its Estimation, with Particular Application to Loss Reserving
Risks, 2023 This paper is concerned with the estimation of forecast error, particularly in relation to insurance loss reserving. Forecast error is generally regarded as consisting of three components, namely parameter, process and model errors.
Greg Taylor, Gráinne McGuire
doaj +1 more source
Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap [PDF]
Computational Statistics & Data Analysis, 2005 In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments.
openaire +5 more sources
A BOOTSTRAP APPROACH TO TESTING FOR SYMMETRY IN THE GRANGER AND LEE ASYMMETRIC ERROR CORRECTION MODEL [PDF]
Russian Journal of Agricultural and Socio-Economic Sciences, 2012 The power of the Granger and Lee (1989) model of asymmetry is examined via bootstrap simulation. The results of the bootstrap simulation indicate that the Granger and Lee model has low power in rejecting the null hypothesis of symmetric adjustments.
Henry De-Graft Acquah
doaj
Remote Sensing, 2020 This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three machine learning (ML) models—multivariate adaptive regression splines (MARS), support vector machine (SVM), and boosted regression tree (BRT). The study utilizes
Bahareh Kalantar +5 more
doaj +1 more source
Bootstrap Inference for Hawkes and General Point Processes [PDF]
arXiv, 2021 Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihood-based estimators and tests. As an alternative, and to improve finite sample performance, this paper considers bootstrap-based inference for interval estimation and testing.
arxiv
Efficient bootstrap estimates for tail statistics [PDF]
Natural Hazards and Earth System Sciences, 2017 Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample.
Ø. Breivik, O. J. Aarnes
doaj +1 more source
The Wild Bootstrap for Multilevel Models
Communications in Statistics - Theory and Methods, 2015 In this paper we study the performance of the most popular bootstrap schemes for multilevel data. Also, we propose a modified version of the wild bootstrap procedure for hierarchical data structures. The wild bootstrap does not require homoscedasticity or assumptions on the distribution of the error processes.
MODUGNO, LUCIA, GIANNERINI, SIMONE
openaire +4 more sources
The Local Projection Residual Bootstrap for AR(1) Models [PDF]
arXiv, 2023 This paper proposes a local projection residual bootstrap method to construct confidence intervals for impulse response coefficients of AR(1) models. Our bootstrap method is based on the local projection (LP) approach and involves a residual bootstrap procedure applied to AR(1) models.
arxiv
Bootstrapping Exchangeable Random Graphs [PDF]
Electronic Journal of Statistics, vol. 16 (2022), pp. 1058--1095, 2017 We introduce two new bootstraps for exchangeable random graphs. One, the "empirical graphon bootstrap", is based purely on resampling, while the other, the "histogram bootstrap", is a model-based "sieve" bootstrap. We show that both of them accurately approximate the sampling distributions of motif densities, i.e., of the normalized counts of the ...
arxiv +1 more source