Advanced Statistical Methods in Data Science - Softcover

Softcover

ISBN 10: 9811025959 ISBN 13: 9789811025952

Verlag: Springer, 2016

Inhaltsangabe

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2016
• ISBN 10: 9811025959
• ISBN 13: 9789811025952
• Einband: Paperback
• Sprache: Englisch
• Kontakt zum Hersteller: Nicht verfügbar