Tag: Likelihood

Likelihood Methods in Survival Analysis With R Examples


Free Download Likelihood Methods in Survival Analysis: With R Examples
English | 2025 | ISBN: 0815362846 | 401 Pages | PDF (True) | 6 MB
Many conventional survival analysis methods, such as the Kaplan-Meier method for survival function estimation and the partial likelihood method for Cox model regression coefficients estimation, were developed under the assumption that survival times are subject to right censoring only. However, in practice, survival time observations may include interval-censored data, especially when the exact time of the event of interest cannot be observed. When interval-censored observations are present in a survival dataset, one generally needs to consider likelihood-based methods for inference. If the survival model under consideration is fully parametric, then likelihood-based methods impose neither theoretical nor computational challenges. However, if the model is semi-parametric, there will be difficulties in both theoretical and computational aspects.

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Local Regression and Likelihood


Free Download Local Regression and Likelihood by Clive Loader
English | PDF(True) | 1999 | 297 Pages | ISBN : 0387987754 | 3.2 MB
Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.

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