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Term Structure Modeling and Estimation in a State Space Framework

Department at the University of Bielefeld, Germany. It was accepted as a Ph.D. thesis titled Term Structure Modeling and Estimation in a State Space;

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Introduction to Time Series Modeling with Applications in R

and non-Gaussian modeling. ... [It] is a valuable book, especially with its broad and accessible introduction of models in the state-space;

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State-Space Models with Regime Switching

distributions from data. The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a;

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Reduced Order Methods for Modeling and Computational Reduction

reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and;

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Analysis and Management of Animal Populations

modeling, parameter estimation and decision-theoretic approaches to management in a single, cohesive framework Provides authoritative;

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Introduction to Time Series Modeling

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates;

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Advances in State Estimation, Diagnosis and Control of Complex Systems

of uncertainties stemming from modeling errors and component malfunctions. Accordingly, the book first introduces a complete set-based framework for;

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Advances in State Estimation, Diagnosis and Control of Complex Systems

of uncertainties stemming from modeling errors and component malfunctions. Accordingly, the book first introduces a complete set-based framework for;

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Battery System Modeling

prediction, power evaluation and health estimation Provides a dedicated chapter on active control strategies;

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Traffic Measurement for Big Network Data

, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range;

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Actuarial Models for Disability Insurance

, providing a vigorous and sound framework for analyzing personal insurances.;

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Two Essays on Maximum Likelihood Estimation

maximum likelihood estimation of DSGE models. The first essay focuses on a monetary DSGE model of term structure, and the estimation of its;

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Cyber-Physical Power Systems State Estimation

model state estimation and non-synchronized measurements system modelsPresents a novel, extended optimization, physics-based model;

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Modeling and Estimation of Structural Damage

Modelling and Estimation of Damage in Structures is a comprehensiveguide to solving the type of modelling and estimation problems;

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Filtering and System Identification

Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background;

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Filtering and System Identification

Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background;

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Predictive Filtering for Microsatellite Control System

filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically;

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Road Traffic Modeling and Management

traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical;

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State Estimation in Chemometrics

-from a new perspective. It succinctly reviews the history of state estimation and chemometrics and provides examples of its many applications;

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Pricing Analytics

the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly;

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Pricing Analytics

get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory;

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Zero Lower Bound Term Structure Modeling

Nominal yields on government debt in several countries have fallen very near their zero lower bound (ZLB), causing a liquidity trap and;

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Measuring Precipitation from Space

products and to have a glimpse of the near future missions and instruments. This book features state-of-the-art rainfall estimation algorithms;

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State-Space Methods for Time Series Analysis

The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to;

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State-Space Methods for Time Series Analysis

The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to;

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Modeling, Control, State Estimation and Path Planning Methods for Autonomous Multirotor Aerial Robots

researchers, engineers and students with a comprehensive overview of core modeling, control, estimation, and planning concepts and approaches for;

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Nonlinear Kalman Filtering for Force-Controlled Robot Tasks

-Controlled Robot Tasks discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan;

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