Advanced Statistical Methods in Data Science
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Singapore :
Springer Singapore : Imprint: Springer,
2016.
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Σειρά: | ICSA Book Series in Statistics,
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Part I: Data Analysis Based on Latent or Dependent Variable Models
- Chapter 1: A New Method for Robust Mixture Regression and Outlier Detection
- Chapter 2: The Mixture Gatekeeping Procedure Based on Weighted Multiple Testing Correction for Correlated Tests
- Chapter 3: Regularization in Regime-switching Gaussian Autoregressive Models
- Chapter 4: Modeling Zero Inflation and Over-dispersion in the Length of Hospital Stay for Patients with Ischaemic Heart Disease
- Chapter 5: Robust Optimal Interval Design for High-Dimensional Dose Finding in Multi-Agent Combination Trials
- Part II: Life Time Data Analysis
- Chapter 6: Group Selection in Semi-parametric Accelerated Failure Time Model
- Chapter 7: A Proportional Odds Model for Regression Analysis of Case I Interval-Censored Data
- Chapter 8: Empirical Likelihood Inference under Density Ratio Models Based on Type I Censored Samples: Hypothesis Testing and Quantile Estimation
- Chapter 9: Recent Development in the Joint Modeling of Longitudinal Quality of Life Measurements and Survival Data from Cancer Clinical Trials
- Part III: Applied Data Analysis
- Chapter 10: Confidence Weighting Procedures for Multiple Choice Tests
- Chapter 11: Improving the Robustness of Parametric Imputation
- Chapter 12: Maximum Smoothed Likelihood Estimation of the Centre of a Symmetric Distribution
- Chapter 13: Dividend Pay-out Problems with the Logarithmic Utility
- Chapter 14: Modeling the Common Risk among Equities: A Multivariate Time Series Model with an Additive GARCH Structure.