Explore the comprehensive process of system identification using MATLAB, specifically tailored for linear models. This guide delves into essential techniques such as ARMAX models, state-space representations, and transfer function identification, providing a foundational understanding for engineers and researchers seeking to accurately model dynamic systems with practical examples.
Explore richly parameterized linear models, including advanced applications in additive time series and spatial data analysis. These powerful statistical tools leverage random effects to effectively capture intricate dependencies and variability in complex datasets.
This document delves into the critical area of estimation theory specifically applied to contrasts within linear models. It explores various methodologies for accurately determining the values of these contrasts, which are fundamental for conducting targeted hypothesis testing and making robust statistical inferences. Understanding the precise estimation of contrasts is crucial for researchers in fields utilizing ANOVA and regression, ensuring reliable interpretation of group differences and treatment effects in experimental designs.
This resource delves into Generalized Linear Insurance Pricing Models (GLMs), focusing specifically on their application within non-life insurance sectors. It explains how these advanced actuarial pricing models are utilized to accurately assess risk and determine rates for various insurance products, excluding those related to life coverage, offering insights into effective risk management and rate-making strategies.
Explore the principles of optimal experimental design specifically tailored for non-linear models. This resource delves into the essential theory and practical applications, providing a concise yet comprehensive understanding for researchers and practitioners in statistical experimental design.
Explore the foundational principles of Gauss Markov Estimation through its elegant Coordinate Free Approach, now available as a faithful reprint of the original 1st edition. This essential text provides deep insights into statistical estimation and linear models, presented with the clarity and rigor that defined its initial release, making it a timeless resource for academics and practitioners alike.
Explore comprehensive applications of linear and nonlinear models, delving into advanced statistical techniques like fixed effects and random effects for robust data analysis. This resource also examines the methodology and practical uses of total least squares, offering insights into their utility within geophysics and broader scientific domains.