ON THE COMPARISON OF BAYESIAN INFORMATION CRITERION AND DRAPER'S INFORMATION CRITERION IN SELECTION OF AN ASYMMETRIC PRICE RELATIONSHIP: BOOTSTRAP SIMULATION RESULTS [PDF]
Alternative formulations of the Bayesian Information Criteria provide a basis for choosing between competing methods for detecting price asymmetry. However, very little is understood about their performance in the asymmetric price transmission modelling ...
Henry de-Graft Acquah, Joseph Acquah
doaj
Parametric and nonparametric bootstrap: an analysis of indoor air data from Kuwait
This paper discusses the performance of parametric and nonparametric bootstrap for confidence interval (CI) estimation applied to fine particulate matter (PM2.5) data.
Sana BuHamra +2 more
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Seasonal Anomalies in TEHRAN Stock Exchange Returns Non Parametric Bootstrap Approach [PDF]
Because of the heterogeneity in behavior, in the real world prices may deviate substantially and persistently from their fundamental values. Of course, if these heterogeneous elements play a rather minor role then asset prices and rates of return will be
Mohsen Nazari, Elham Farzanegan
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MANOVA for Nested Designs with Unequal Cell Sizes and Unequal Cell Covariance Matrices
We propose and study parametric bootstrap (PB) tests for heteroscedastic two-factor MANOVA with nested designs. For the problem of testing “main effects” of both factors, we develop a flexible test based on a parametric bootstrap approach. The PB test is
Li-Wen Xu
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A Joint Specification Test for Response Probabilities in Unordered Multinomial Choice Models
Estimation results obtained by parametric models may be seriously misleading when the model is misspecified or poorly approximates the true model. This study proposes a test that jointly tests the specifications of multiple response probabilities in ...
Masamune Iwasawa
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A Non-parametric Bootstrap Method for Kinetic Monte Carlo Variance Reduction [PDF]
A new variance reduction technique for Monte Carlo transport methods is investigated. This approach is based on non-parametric bootstrapping, a statistical inference and resampling method which is used to generate simulated samples of Monte Carlo scores ...
Skretteberg Martin +2 more
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THE RESEARCH OF BOOTSTRAP ADAPTATION DURING INITIAL GAS TURBINE ENGINE PARAMETERS PROCESSING
This article is dealing with the research of bootstrap adaptation during initial air-jet engine parameters processing in trend analysis. Types of bootstrap and its adaptation are shown. Optimal bootstrap variation length is chosen.
K. A. Sorokin
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Assessing Variable Importance for Best Subset Selection
One of the primary issues that arises in statistical modeling pertains to the assessment of the relative importance of each variable in the model. A variety of techniques have been proposed to quantify variable importance for regression models.
Jacob Seedorff, Joseph E. Cavanaugh
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Maximum likelihood estimation (MLE) in infinite mixture distributions often lacks closed-form solutions, requiring numerical methods such as the Newton–Raphson algorithm.
Aceng Komarudin Mutaqin
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