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The purpose of this book is to present some uses of the Kalman filter (KF) in engineering activities that can produce a robust and technically acceptable result while keeping as close as possible to the optimal (most accurate) solution. KF sub-optimization is often required, due to the realities of implementation and real-life operational conditions. The book brings together the experiences of specialists from different engineering areas using the KF in their practice.

Kalman filtering. --- Kalman filtering

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The purpose of this book is to present some uses of the Kalman filter (KF) in engineering activities that can produce a robust and technically acceptable result while keeping as close as possible to the optimal (most accurate) solution. KF sub-optimization is often required, due to the realities of implementation and real-life operational conditions. The book brings together the experiences of specialists from different engineering areas using the KF in their practice.

Kalman filtering. --- Kalman filtering

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We establish that the recursive, state-space methods of Kalman filtering and smoothing can be used to implement the Doan, Litterman, and Sims (1983) approach to econometric forecast and policy evaluation. Compared with the methods outlined in Doan, Litterman, and Sims, the Kalman algorithms are more easily programmed and modified to incorporate different linear constraints, avoid cumbersome matrix inversions, and provide estimates of the full variance covariance matrix of the constrained projection errors which can be used directly, under standard normality assumptions, to test statistically the likelihood and internal consistency of the forecast under study.

Kalman filtering.

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The purpose of this book is to present some uses of the Kalman filter (KF) in engineering activities that can produce a robust and technically acceptable result while keeping as close as possible to the optimal (most accurate) solution. KF sub-optimization is often required, due to the realities of implementation and real-life operational conditions. The book brings together the experiences of specialists from different engineering areas using the KF in their practice.

Kalman filtering.

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• Reference Manager
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Kalman filtering.