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Data Analysis Using Hierarchical Generalized Linear Models with R - Youngjo Lee 2017 EPUB CRC BOOKS PROGRAMMING
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Data Analysis Using Hierarchical Generalized Linear Models with R
Author: Youngjo Lee
Year: 2017
Pages: 334
Format: EPUB
File size: 10 MB
Language: ENG



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Book Description: Data Analysis Using Hierarchical Generalized Linear Models with R Youngjo Lee 2017 Pages: 334 CRC Summary: Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. As a result, interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes these developments within the field and uses data examples to illustrate how to analyze various types of data using R. It provides a likelihood approach to advanced statistical modeling, including generalized linear models with random effects, survival analysis, and frailty models, as well as multivariate HGLMs, factor, and structural equation models. Additionally, it covers robust modeling of random effects models, including penalty and variable selection, and hypothesis testing. Need and Possibility of Developing a Personal Paradigm for Perceiving the Technological Process of Developing Modern Knowledge: In today's fast-paced technological world, it is essential to understand the process of technology evolution to stay ahead of the curve. With the rapid advancement of modern knowledge, it is crucial to develop a personal paradigm for perceiving the technological process. By doing so, individuals can better comprehend the significance of technological advancements and adapt to the changing landscape. This personal paradigm will enable them to navigate the complexities of technology and make informed decisions that benefit humanity as a whole. The need for a personal paradigm arises from the fact that technology is constantly evolving, and its impact on society is becoming more profound. As technology continues to advance, it is imperative to understand how it affects various aspects of life, such as communication, work, entertainment, and education.
Анализ данных с использованием иерархических обобщенных линейных моделей с R Youngjo e 2017 Страницы: 334 CRC Резюме: С момента их введения иерархические обобщенные линейные модели (HGLM) оказались полезными в различных областях, позволяя случайные эффекты в регрессионных моделях. В результате интерес к теме вырос, были разработаны различные практические аналитические инструменты. В этой книге обобщаются эти разработки в этой области и используются примеры данных, чтобы проиллюстрировать, как анализировать различные типы данных с использованием R. Он обеспечивает подход правдоподобия к продвинутому статистическому моделированию, включая обобщенные линейные модели со случайными эффектами, анализ выживаемости и модели хрупкости, а также многомерные модели HGLM, факторы и структурные уравнения. Кроме того, он охватывает надежное моделирование моделей случайных эффектов, включая выбор штрафов и переменных, а также проверку гипотез. Необходимость и возможность разработки личностной парадигмы для восприятия технологического процесса развития современных знаний: в современном быстро развивающемся технологическом мире важно понимать процесс эволюции технологий, чтобы оставаться на опережение. При быстром продвижении современных знаний крайне важно выработать личностную парадигму восприятия технологического процесса. Таким образом, люди могут лучше понять значение технологических достижений и адаптироваться к изменяющемуся ландшафту. Эта личная парадигма позволит им ориентироваться в сложностях технологий и принимать обоснованные решения, которые приносят пользу человечеству в целом. Потребность в личностной парадигме возникает из-за того, что технологии постоянно развиваются, а их влияние на общество становится все более глубоким. Поскольку технологии продолжают развиваться, необходимо понимать, как они влияют на различные аспекты жизни, такие как общение, работа, развлечения и образование.
Análisis de datos utilizando modelos lineales generalizados jerárquicos con R Yungjo e 2017 Páginas: 334 CRC Resumen: Desde su introducción, los modelos lineales generalizados jerárquicos (HGLM) han demostrado ser útiles en diversas áreas, permitiendo efectos aleatorios en modelos de regresión. Como resultado, el interés por el tema ha crecido, se han desarrollado diversas herramientas analíticas prácticas. Este libro resume estos desarrollos en este campo y utiliza ejemplos de datos para ilustrar cómo analizar diferentes tipos de datos usando R. Proporciona un enfoque de plausibilidad para modelos estadísticos avanzados, incluyendo modelos lineales generalizados con efectos aleatorios, análisis de supervivencia y modelos de fragilidad, así como modelos de HGLM multidimensionales, factores y ecuaciones estructurales. Además, cubre la simulación confiable de modelos de efectos aleatorios, incluyendo la selección de penalizaciones y variables, así como la verificación de hipótesis. Necesidad y posibilidad de desarrollar un paradigma personal para percibir el proceso tecnológico del desarrollo del conocimiento moderno: en un mundo tecnológico en rápida evolución, es importante comprender el proceso de evolución de la tecnología para mantenerse a la vanguardia. Con el rápido avance del conocimiento moderno, es fundamental desarrollar un paradigma personal de percepción del proceso tecnológico. De esta manera, las personas pueden comprender mejor el significado de los avances tecnológicos y adaptarse a un paisaje cambiante. Este paradigma personal les permitirá navegar por las complejidades de la tecnología y tomar decisiones informadas que beneficien al conjunto de la humanidad. La necesidad de un paradigma personal surge porque la tecnología evoluciona constantemente y su impacto en la sociedad es cada vez más profundo. A medida que la tecnología continúa evolucionando, es necesario entender cómo afectan a diferentes aspectos de la vida, como la comunicación, el trabajo, el entretenimiento y la educación.
Analisi dei dati con modelli di linea generici gerarchici con R Young e 2017 Pagine: 334 CRC Curriculum: da quando sono stati introdotti, i modelli di linea gerarchici (HGLM) sono stati utili in diverse aree, consentendo effetti casuali nei modelli di regressione. Di conseguenza, l'interesse per il tema è cresciuto, sono stati sviluppati diversi strumenti analitici pratici. Questo libro riassume questi sviluppi in questo campo e utilizza esempi di dati per illustrare come analizzare i diversi tipi di dati utilizzando R. Fornisce un approccio credibile alle simulazioni statistiche avanzate, inclusi modelli lineari generalizzati con effetti casuali, analisi della sopravvivenza e modelli di fragilità, e modelli HGLM multidimensionali, fattori e equazioni strutturali. Inoltre, include la simulazione affidabile di modelli di effetti casuali, inclusa la scelta di multe e variabili e la verifica delle ipotesi. La necessità e la possibilità di sviluppare un paradigma personalistico per la percezione del processo tecnologico dello sviluppo delle conoscenze moderne, in un mondo tecnologico in continua evoluzione, è importante comprendere l'evoluzione della tecnologia per rimanere in anticipo. Quando le conoscenze moderne avanzano rapidamente, è fondamentale sviluppare un paradigma personale per la percezione del processo tecnologico. In questo modo, le persone possono comprendere meglio l'importanza dei progressi tecnologici e adattarsi al panorama che cambia. Questo paradigma personale consentirà loro di orientarsi nella complessità della tecnologia e di prendere decisioni ragionevoli che fanno bene all'umanità in generale. La necessità di un paradigma personale nasce dal fatto che la tecnologia è in continua evoluzione e il loro impatto sulla società sta diventando sempre più profondo. Poiché la tecnologia continua a svilupparsi, è necessario capire come influiscono su diversi aspetti della vita, come la comunicazione, il lavoro, l'intrattenimento e l'istruzione.
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R Youngjo e 2017 Pages: 334 CRC概要:導入以来、HGLM (Hierarchical Generalized Linear Model)は様々な分野で有用であることが証明されており、回帰モデルにおけるランダムな効果を可能にしている。その結果、トピックへの関心が高まり、さまざまな実用的な分析ツールが開発されました。本書では、この分野におけるこれらの展開を要約し、サンプルデータを用いて、Rを用いてさまざまな種類のデータを分析する方法を説明している。さらに、ペナルティや変数選択、仮説テストなどのランダム効果モデルの堅牢なモデリングもカバーしています。近代的な知識の発展の技術プロセスの認識のための個人的なパラダイムを開発する必要性と可能性:現代の急速に発展している技術の世界では、曲線の先に滞在するために、技術の進化のプロセスを理解することが重要です。現代の知識の急速な進歩に伴い、技術プロセスの認識のための個人的なパラダイムを開発することは非常に重要です。したがって、人々は技術の進歩の重要性をよりよく理解し、変化する風景に適応することができます。この個人的なパラダイムは、テクノロジーの複雑さをナビゲートし、人類全体に利益をもたらす情報に基づいた意思決定を行うことを可能にします。人格パラダイムの必要性は、技術が絶えず進化しており、社会への影響が深まっていることから生じています。テクノロジーが進化し続ける中で、コミュニケーション、仕事、娯楽、教育など、生活のさまざまな側面にどのように影響するかを理解する必要があります。

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