FKF.SP: Fast Kalman Filtering Through Sequential Processing

Thomas Aspinall; Adrian Gepp; Geoffrey Harris; Simone Kelly; Colette Southam; Bruce J Vanstone; David Luethi; Philipp Erb; Simon Otziger; Paul Smith

FKF.SP: Fast Kalman Filtering Through Sequential Processing

Thomas Aspinall
, Adrian Gepp
, Geoffrey Harris
, Simone Kelly
, Colette Southam
, Bruce J Vanstone
, David Luethi
, Philipp Erb
, Simon Otziger
, Paul Smith

Bond University

Research output: Other contribution

Abstract

Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. 'FKF.SP' was built upon the existing 'FKF' package and was designed to generally increase the computational efficiency of Kalman filtering when independence is assumed in the measurement error of observations. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8)

Original language	English
Publication status	Published - 18 Dec 2020
Externally published	Yes

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https://cran.r-project.org/web/packages/FKF.SP/index.html

Cite this

@misc{21729a2c618649f6915008f07e893140,

title = "FKF.SP: Fast Kalman Filtering Through Sequential Processing",

abstract = "Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. 'FKF.SP' was built upon the existing 'FKF' package and was designed to generally increase the computational efficiency of Kalman filtering when independence is assumed in the measurement error of observations. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8)",

author = "Thomas Aspinall and Adrian Gepp and Geoffrey Harris and Simone Kelly and Colette Southam and Vanstone, \{Bruce J\} and David Luethi and Philipp Erb and Simon Otziger and Paul Smith",

year = "2020",

month = dec,

day = "18",

language = "English",

type = "Other",

}

TY - GEN

T1 - FKF.SP: Fast Kalman Filtering Through Sequential Processing

AU - Aspinall, Thomas

AU - Gepp, Adrian

AU - Harris, Geoffrey

AU - Kelly, Simone

AU - Southam, Colette

AU - Vanstone, Bruce J

AU - Luethi, David

AU - Erb, Philipp

AU - Otziger, Simon

AU - Smith, Paul

PY - 2020/12/18

Y1 - 2020/12/18

N2 - Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. 'FKF.SP' was built upon the existing 'FKF' package and was designed to generally increase the computational efficiency of Kalman filtering when independence is assumed in the measurement error of observations. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8)

AB - Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. 'FKF.SP' was built upon the existing 'FKF' package and was designed to generally increase the computational efficiency of Kalman filtering when independence is assumed in the measurement error of observations. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8)

M3 - Other contribution

ER -

FKF.SP: Fast Kalman Filtering Through Sequential Processing

Abstract

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