Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics
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Published By Springer Singapore

9789811033063, 9789811033070

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Bootstrap-Based LASSO-Type Selection to Build Generalized Additive Partially Linear Models for High-Dimensional Data

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_18 ◽

2017 ◽

pp. 405-424

Author(s):

Xiang Liu ◽

Tian Chen ◽

Yuanzhang Li ◽

Hua Liang

Keyword(s):

Linear Models ◽

High Dimensional Data ◽

High Dimensional ◽

Partially Linear Models ◽

Partially Linear ◽

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Monte-Carlo Simulation in Modeling for Hierarchical Generalized Linear Mixed Models

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_13 ◽

2017 ◽

pp. 255-283

Author(s):

Kyle M. Irimata ◽

Jeffrey R. Wilson

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Mixed Models ◽

Generalized Linear Mixed Models ◽

Linear Mixed Models

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Joint Generation of Binary, Ordinal, Count, and Normal Data with Specified Marginal and Association Structures in Monte-Carlo Simulations

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_1 ◽

2017 ◽

pp. 3-15 ◽

Author(s):

Hakan Demirtas ◽

Rawan Allozi ◽

Yiran Hu ◽

Gul Inan ◽

Levent Ozbek

Keyword(s):

Monte Carlo ◽

Monte Carlo Simulations

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Improving the Efficiency of the Monte-Carlo Methods Using Ranked Simulated Approach

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_2 ◽

2017 ◽

pp. 17-40

Author(s):

Hani Michel Samawi

Keyword(s):

Monte Carlo ◽

Monte Carlo Methods ◽

Simulated Approach

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Anatomy of Correlational Magnitude Transformations in Latency and Discretization Contexts in Monte-Carlo Studies

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_4 ◽

2017 ◽

pp. 59-84 ◽

Author(s):

Hakan Demirtas ◽

Ceren Vardar-Acar

Keyword(s):

Monte Carlo ◽

Monte Carlo Studies

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Erratum to: Monte-Carlo Simulation-Based Statistical Modeling

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_19 ◽

2017 ◽

pp. E1-E1

Author(s):

Ding-Geng Chen ◽

John Dean Chen

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Statistical Modeling ◽

Simulation Based

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A Multiple Imputation Framework for Massive Multivariate Data of Different Variable Types: A Monte-Carlo Technique

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_8 ◽

2017 ◽

pp. 143-162

Author(s):

Hakan Demirtas

Keyword(s):

Monte Carlo ◽

Multiple Imputation ◽

Multivariate Data ◽

Monte Carlo Technique

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Markov Chain Monte-Carlo Methods for Missing Data Under Ignorability Assumptions

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_7 ◽

2017 ◽

pp. 129-142 ◽

Author(s):

Haresh Rochani ◽

Daniel F. Linder

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Missing Data ◽

Monte Carlo Methods

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Statistical Methodologies for Dealing with Incomplete Longitudinal Outcomes Due to Dropout Missing at Random

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_10 ◽

2017 ◽

pp. 179-209

Author(s):

A. Satty ◽

H. Mwambi ◽

G. Molenberghs

Keyword(s):

Missing At Random ◽

Longitudinal Outcomes

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Quantifying the Uncertainty in Optimal Experiment Schemes via Monte-Carlo Simulations

Monte-Carlo Simulation-Based Statistical Modeling - ICSA Book Series in Statistics ◽

10.1007/978-981-10-3307-0_6 ◽

2017 ◽

pp. 107-126 ◽

Author(s):

H. K. T. Ng ◽

Y.-J. Lin ◽

T.-R. Tsai ◽

Y. L. Lio ◽

N. Jiang

Keyword(s):

Monte Carlo ◽

Monte Carlo Simulations ◽

Optimal Experiment

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