Bootstrap Algorithms for Risk Models With Auxiliary Variable and Complex Samples

Methodology and Computing in Applied Probability - Netherlands
doi 10.1007/s11009-008-9072-8
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

Regression Models for Choice-Based Samples With Misclassification in the Response Variable

Journal of Econometrics
Philosophy of ScienceApplied MathematicsEconomicsEconometricsHistory
2002English

The Extended Auxiliary Equation Method for the KdV Equation With Variable Coefficients

Chinese Physics B
AstronomyPhysics
2011English

Using Distance Covariance for Improved Variable Selection With Application to Learning Genetic Risk Models

Statistics in Medicine
EpidemiologyStatisticsProbability
2015English

Use of Round Shape Bootstrap Samples for a Classifier Design

International Journal of Engineering and Technology
2017English

Bootstrap Approximation to Prediction MSE for State-Space Models With Estimated Parameters

Journal of Time Series Analysis
UncertaintyApplied MathematicsStatisticsProbability
2005English

Developing and Improving Risk Models Using Machine-Learning Based Algorithms

2019English

Identification of ARMA Models Using Bootstrap

Revista Ciencias Exatas e Naturais
2014English

Variable Frame Based Max-Weight Algorithms for Networks With Switchover Delay

2011English

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis

Entropy
Electronic EngineeringInformation SystemsMathematical PhysicsElectricalAstronomyPhysics
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy