Results 31 to 40 of about 87,758 (191)
Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity [PDF]
Natural Hazards and Earth System Sciences, 2018 Landslides cause severe damage to the road network of the hit zone, in terms of both direct (partial or complete destruction of a road or blockages) and indirect (traffic restriction or the cut-off of a certain area) costs. Thus, the identification of
M. Bordoni +9 more
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Kernel Smoothing to Improve Bootstrap Confidence Intervals
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1997 Summary Some studies of the bootstrap have assessed the effect of smoothing the estimated distribution that is resampled, a process usually known as the smoothed bootstrap. Generally, the smoothed distribution for resampling is a kernel estimate and is often rescaled to retain certain characteristics of the empirical distribution ...
Polansky, Alan M., Schucany, William R.
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Alternative Smoothed Bootstraps
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1990 SUMMARY Bootstrap estimation of simple population functionals is considered. The smoothed bootstrap (Efron, 1979, 1982) is compared with an alternative estimation procedure based on resampling ideas of Kendall and Kendall (1980). Specific examples of the estimation problem are considered, showing that the competing estimators may display
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One-Step Bootstrapping for Smooth Iterative Procedures
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1991 SUMMARY Resampling techniques have the potential to provide useful information about the sampling distribution of estimators of many population characteristics. Ambitious schemes such as the bootstrap and iterated bootstrap imply a substantial increase in computational effort.
Schucany, William R., Wang, Suojin
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Bootstrap of residual processes in regression: to smooth or not to smooth? [PDF]
Biometrika, 2019 In this paper we consider a location model of the form $Y = m(X) + \varepsilon$, where $m(\cdot)$ is the unknown regression function, the error $\varepsilon$ is independent of the $p$-dimensional covariate $X$ and $E(\varepsilon)=0$. Given i.i.d. data $(X_1,Y_1),\ldots,(X_n,Y_n)$ and given an estimator $\hat m(\cdot)$ of the function $m(\cdot)$ (which ...
Neumeyer, N, Van Keilegom, I
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Unit Root Testing and Estimation in Nonlinear ESTAR Models with Normal and Non-Normal Errors. [PDF]
PLoS ONE, 2016 Exponential Smooth Transition Autoregressive (ESTAR) models can capture non-linear adjustment of the deviations from equilibrium conditions which may explain the economic behavior of many variables that appear non stationary from a linear viewpoint. Many
Umair Khalil +5 more
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Current status linear regression
, 2017 We construct $\sqrt{n}$-consistent and asymptotically normal estimates for the finite dimensional regression parameter in the current status linear regression model, which do not require any smoothing device and are based on maximum likelihood estimates (
Groeneboom, Piet, Hendrickx, Kim
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Iterated smoothed bootstrap confidence intervals for population quantiles [PDF]
, 2005 This paper investigates the effects of smoothed bootstrap iterations on coverage probabilities of smoothed bootstrap and bootstrap-t confidence intervals for population quantiles, and establishes the optimal kernel bandwidths at various stages of the ...
Ho, Yvonne H. S., Lee, Stephen M. S.
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Nonparametric Estimates of Low Bias
Revstat Statistical Journal, 2012 We consider the problem of estimating an arbitrary smooth functional of k ≥ 1 distribution functions (d.f.s) in terms of random samples from them. The natural estimate replaces the d.f.s by their empirical d.f.s. Its bias is generally ∼ n−1 , where n is
Christopher S. Withers +1 more
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Smoothed Bootstrap Methods for Hypothesis Testing
Journal of Statistical Theory and PracticeAbstractThis 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.
Asamh S. M. Al Luhayb +2 more
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