Functional Form and Heterogeneity in Models for Count Data

The Functional Approach to Data Manageme

📁 The Functional Approach to Data Management: Modeling, Analyzing and Integrating Heterogeneous Data

✍ Peter M. D. Gray, Peter J. H. King, Alexandra Poulovassilis (auth.), Peter M. D. 📂 Library 📅 2004 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

It is over 20 years since the functional data model and functional programming languages were first introduced to the computing community. Although developed by separate research communities, recent work, presented in this book, suggests there is powerful synergy in their integration. A

The Functional Approach to Data Manageme

📁 The Functional Approach to Data Management: Modeling, Analyzing and Integrating Heterogeneous Data

✍ Peter M. D. Gray, Peter J. H. King, Alexandra Poulovassilis (auth.), Peter M. D. 📂 Library 📅 2004 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

It is over 20 years since the functional data model and functional programming languages were first introduced to the computing community. Although developed by separate research communities, recent work, presented in this book, suggests there is powerful synergy in their integration. A

Heterogenous spatial data. Fusion, model

📁 Heterogenous spatial data. Fusion, modeling, and analysis for GIS

✍ Patane G., Spagnuolo M 📂 Library 📅 2016 🏛 Morgan 🌐 English

Regression Models for Categorical and Co

📁 Regression Models for Categorical and Count Data

✍ Peter Martin 📂 Library 📅 2022 🏛 SAGE Publications 🌐 English

This text provides practical guidance on conducting regression analysis on categorical and count data. Step by step and supported by lots of helpful graphs, it covers both the theoretical underpinnings of these methods as well as their application, giving you the skills needed to apply them

Regression Models for Count Data in R +

📁 Regression Models for Count Data in R + Code

✍ Zeileis A., Kleiber C., Jackman S. 📂 Library 🌐 English

The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of th

Heterogenous Spatial Data: Fusion, Model

📁 Heterogenous Spatial Data: Fusion, Modeling, and Analysis for GIS Applications

✍ Giuseppe Patanè, Michela Spagnuolo 📂 Library 📅 2016 🏛 Morgan & Claypool Publishers 🌐 English

New data acquisition techniques are emerging and are providing fast and efficient means for multidimensional spatial data collection. Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and mobile mapping systems are increasingly used for the digital reconstruction of the environment. A