jackknife/bootstrap
Jackknife And Bootstrap Techniques In The Estimation of regression Parameters
... B=10000 bootstrap samples are randomly generated to show the exact feature of the bootstrap processes and the distributions of regression parameter of bootstrap estimations ( ˆ J )which were ...
11
Investigating of Turkey Champion Clubs’ Financial Performance Using Bootstrap and Jackknife Methods
... using bootstrap and jackknife methods how accurate Turkey’s teams, being champion since super league was established, use their financial expenditure for the scores when they were consecutively in league ...
6
Estimation of bivariate linear regression data via Jackknife algorithm
... on Jackknife bootstrap and other re-sampling methods in regression analysis; motivated by a representation for the least squares estimator, they proposed a class of weighted jackknife variance ...
8
Minimization of Error in Exponential Model Estimation via Jackknife Algorithm
... on Jackknife bootstrap and other re-sampling methods in regression analysis; motivated by a representation for the least squares estimator, they proposed a class of weighted jackknife variance ...
11
A. Bootstrap and Jackknife Variance Estimation
... It follows that the equation EUAUSU = can be used to discover whether the data segment D has contributed more or less than it’s expected proportion of the overall uncertainty within the [r] ...
9
Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
... We have focused on the case where each bootstrap replicate contains exactly n samples. However, in some applications, bagging with subsamples of size m 6= n has been found to work well (e.g., Bühlmann and Yu, ...
27
On the bootstrap and confidence intervals
... d jackknife techniques, w hich axe know n to perfo rm well in sim ple problem s, have b een in v estig ated as possible solutions to m ore com plex problem s, such as th e q u an tile pro b lem , w ith m ixed ...
195
INFERENTIAL PROCEDURES BASED ON THE DOUBLE BOOTSTRAP FOR LOG LOGISTIC REGRESSION MODEL WITH CENSORED DATA
... the jackknife and bootstrap percentile allow us to construct the interval estimates without relying on any classical ...double bootstrap became preferable as it is not only free from any classical ...
9
Molecular Dynamics Simulations Towards The Understanding of the Cis Trans Isomerization of Proline As A Conformational Switch For The Regulation of Biological Processes
... using jackknife empirical likelihood (JEL), adjusted JEL, extended JEL, traditional boot- strap, percentile bootstrap, and BCa bootstrap ...different bootstrap methods with three real data ...
36
Auxiliary Bootstrap Methods.
... nonparametric bootstrap, the proposed methodol- ogy applies directly to other resampling schemes including the parametric bootstrap, jackknife, subsampling, and Monte Carlo studies in which data sets ...
89
Bootstrap Confidence Intervals of the Difference between Two Process Capability Indices for Half Logistic Distribution
... )100% bootstrap confidence interval, which is called the “coverage probability”, can be ...the bootstrap confidence interval is calculated based on the M 5,000 different trials ...
16
Perturbation Bootstrap in Regression.
... perturbation bootstrap was introduced by Jin, Ying, and Wei (2001) as a resampling procedure where the objective function has a U-process ...perturbation bootstrap in the linear regression setup is ...
163
Jackknife bias reduction in autoregressive models with a unit root
... ‘optimal’ jackknife weights that remove fully the first-order bias under a unit root as ...the jackknife estimator can still eliminate a substantial amount of this ...the jackknife estimator provide ...
30
Doubly-robust Estimators in Observational Studies with and without a Stratified Sub-sample.
... For the interest of smaller sample size performance, a simulation study with sample size N = 200 is conducted. The data generating mechanism and parameter values remain the same. The AIPWCC estimator is computed in all ...
72
Introduction to the bootstrap world
... thing can be computed, at least up to Monte Carlo error. Those true quantities calculated in the bootstrap world are estimates of the parallel quantities in the real world. In effect [r] ...
8
Bootstrap Estimation of the Predictive Distributions of Reserves Using Paid and Incurred Claims
... Bootstrapping has become very popular in stochastic claims reserving because of the simplicity and flexibility of the approach. One of the main reasons for this is the ease with which it can be implemented in a ...
25
Randomized Significance Tests in Machine Translation
... two-sided bootstrap algo- rithm in Figure 1, and report on the results of our own experiments in Section ...paired bootstrap resampling (Koehn, 2004), which is widely used in MT ...
9
Bootstrap T Technique for Minimax Multivariate Control Chart
... Bootstrap methods are considered in the application of statistical process control because they can deal with unknown distributions and are easy to calculate using a personal computer. In this study we propose the ...
5
Bootstrapping realized multivariate volatility measures
... Contrary to our expectations based on the existing theory for the pairs bootstrap in the statistics literature, we show that the pairs bootstrap does not provide an asymptotic refinement[r] ...
39
Bootstrap Estimation of the Predictive Distributions of Reserves using Paid and Incurred Claims
... a bootstrap approach to estimate the prediction distributions of reserves produced by the Munich chain ladder (MCL) ...produce bootstrap distributions, this paper addresses the application of bootstrapping ...
25