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This book presents a practical approach for researchers seeking to analyse patient data over time, serving... Læs mere
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Whether you're new to statistical analysis or looking to enhance your analytical skills with the R programming language, this textbook provides comprehensive and practical guidance for understanding fundamental statistical concepts through healthcare examples in R.
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This book provides a comprehensive and practical guide to fitting complex Bayesian survival, longitudinal and joint models using the Integrated Nested Laplace Approximations (INLA) methodology, a powerful and computationally efficient alternative to traditional MCMC methods.
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The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. For... Læs mere
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This book presents an in-depth guide designed for students, researchers and professionals seeking to harness the power of LaTeX, which is a high-quality typesetting tool widely... Læs mere
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This book presents an in-depth guide designed for students, researchers and professionals seeking to harness the power of LaTeX, which is a high-quality typesetting tool widely used in... Læs mere
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mso-bidi-language: AR-SA;">This book uses R package, iForecast, to conduct financial economic time series forecasting with machine learning methods, especially the generation of dynamic forecasts out-of-sample.
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Extensions of the robust multiple regression model include Bayesian, heteroskedastic, time series and compositional regression, together with the clustering of regression models.
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Das Symbolische Rechnen zur Losung mathematischer Probleme erlebt einen neuen Aufschwung durch den Einsatz speziell dafur entwikckelter Softwaresysteme. Nach dem Erfolg von... Læs mere
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This volume in the NATO Special Programme on Advanced Educational Technology looks at how the computer can support the use of visual images in mathematical problem solving. The authors are from computer science, mathematics, mathematics education, psychology, and design.
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Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning.