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Three-fold Fay–Herriot model for small area estimation and its diagnostics
This paper introduces a three-fold Fay–Herriot model with random effects at three hierarchical levels. Small area best linear unbiased predictors of...
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Estimation of poverty and inequality in small areas: review and discussion
Never better said, a correct diagnosis is crucial for patient recovery. In the eradication of poverty, which is the first of the sustainable...
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Random Regression Coefficient Models
This chapter describes a modification of the nested error regression model having random regression coefficients. We can intuitively expect that the...
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Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses
When surveys are not originally designed to produce estimates for small geographical areas, some of these domains can be poorly represented in the...
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Area-Level Bivariate Linear Mixed Models
This chapter describes the bivariate Fay–Herriot model under complete parametrization, and it gives the Fisher-scoring algorithms to calculate the...
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ECM Algorithm for Auto-Regressive Multivariate Skewed Variance Gamma Model with Unbounded Density
The multivariate skewed variance gamma (MSVG) distribution is useful in modelling data with high density around the location parameter along with...
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Linear Mixed Models
This chapter introduces linear mixed models, which have wide applicability in small area estimation due to their flexibility to combining different...
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Controlling Bias in Randomized Clinical Trials
Clinical trials are considered to be the gold standard of research designs at the top of the evidence chain. This reputation is due to the ability to...
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Traffic Networks via Neural Networks: Description and Evolution
Sopasakis, AlexandrosWe optimize traffic signal timing sequences for a section of a traffic network in order to reduce congestion based on...
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Overview and Descriptive Statistics
Statistical concepts and methods are not only useful but indeed often indispensable in understanding the world around us. They provide ways of...
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Generalized Linear Mixed Models: Part I
For the most part, linear mixed models have been used in situations where the observations are continuous. However, oftentimes in practice the...
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Estimation of sample quantiles: challenges and issues in the context of income and wealth distributions
Means, quantiles and extreme values are common statistics for the description of distributions. However, estimating sample quantiles with the default...
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Controlling Bias in Randomized Clinical Trials
Clinical trials are considered to be the gold standard of research designs at the top of the evidence chain. This reputation is due to the ability to...
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Big Data, Real-World Data, and Machine Learning
Complex human diseases result from the cumulative effect of multiple genomic components and environmental factors. The impact of any individual...
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Linear Mixed Models: Part I
The best way to understand a linear mixed modelLinear mixed model , or mixed linear model in some earlier literature, is to first recall a linear...
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Model selection in linear mixed-effect models
Linear mixed-effects models are a class of models widely used for analyzing different types of data: longitudinal, clustered and panel data. Many...
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Robust Ergonomic Virtual Design
From the early development phases of a new industrial product, realistic simulations can be performed in a virtual environment to study the...
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Two-Way Crossed Classification without Interaction
The one-way classification discussed in Chapter 2 involved the levels of only a single factor. It is the simplest model in terms of experimental...