Results 271 to 280 of about 40,800 (302)

Non-parametric bootstrap tests for parametric distribution families

Acta Scientiarum Mathematicarum, 2011
This paper considers the test on whether the underlying distribution of an independent and identically distributed sample is a specific member of parametric distribution family. A functional of the difference between the empirical distribution of the sample and estimated parametric distribution can be used as the test statistic but its critical value ...
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Bootstrap confidence intervals for a class of parametric problems

Biometrika, 1985
The paper considers an application of the bootstrap method to obtain confidence intervals for \(\theta =t(\eta)\) on the basis of data y coming from a multivariate normal with mean \(\eta\) and variance-covariance matrix identity. The usual approximate solution based on the MLE \({\hat \theta}=t({\hat \eta})\) using asymptotic variance \({\hat \sigma}\)
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Bootstrap non-parametric significance test

Journal of Nonparametric Statistics, 2007
In this paper, we consider the problem of testing the significance of covariates in a nonparametric regression model. We propose to use some bootstrap procedures to better approximate the finite sample distribution of the test statistics. We establish the asymptotic validity of the proposed bootstrap procedures.
Jingping Gu, Dingding Li, Dandan Liu
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Portfolio management with semi-parametric bootstrapping

Journal of Risk Management in Financial Institutions, 2010
Estimation risk is an important topic within the area of risk management. Uncertainties regarding parameter estimates carry on to the final statistical product, such as investment strategies, and need to be estimated and accounted for. Unless the exact expressions for the estimators’ variances are known, the product’s variability will be assessed ...
Beatriz Vaz De Melo Mendes, Ricardo Pereira Câmara Leal   +1 more
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Parametric bootstrap inference in bilinear models.

1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LA ROCCA, Michele, VITALE, Cosimo Damiano   +1 more
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Parametric polyspectrum density estimation using the bootstrap method

Signal Processing, 2007
A method for obtaining the statistical distribution of parametric polyspectra when applied to a single set of short data record is presented. The method applies model-based bootstrap to a time-series data to obtain the statistical distribution of the coefficients of the approximating process of autoregressive moving average (ARMA) type with known order
Shahnoor Shanta, Visakan Kadirkamanathan
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Non‐parametric bootstrapping of partitioned datasets

TAXON, 2009
AbstractNon‐parametric bootstrapping is one of the most commonly used methods for branch support assessment. Unlike Bayesian posterior probability values, which are influenced by a priori data partitioning, non‐parametric bootstrapping is usually applied to unpartitioned (combined) datasets. The resulting bootstrap support values are misleading in that
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Optimal choice between parametric and non-parametric bootstrap estimates

Mathematical Proceedings of the Cambridge Philosophical Society, 1994
AbstractA parametric bootstrap estimate (PB) may be more accurate than its non-parametric version (NB) if the parametric model upon which it is based is, at least approximately, correct. Construction of an optimal estimator based on both PB and NB is pursued with the aim of minimizing the mean squared error.
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An application of weighted bootstrap method in semi-parametric model

Information Sciences, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Parametric bootstrap for reliability assessment

2010
The article concerns the evaluation of reliability for stress-strength models. A parametric bootstrap approach is suggested for the interval estimation of reliability, and its performance is checked and compared to other procedures available from literature through a simulation study performed on artificial data.
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