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FKF.SP: Fast Kalman Filtering Through Sequential Processing

Research output: Other contribution

Standard Standard

FKF.SP: Fast Kalman Filtering Through Sequential Processing. / Aspinall, Thomas; Gepp, Adrian; Harris, Geoffrey et al.
2020.

Research output: Other contribution

HarvardHarvard

Aspinall, T, Gepp, A, Harris, G, Kelly, S, Southam, C, Vanstone, BJ, Luethi, D, Erb, P, Otziger, S & Smith, P 2020, FKF.SP: Fast Kalman Filtering Through Sequential Processing.. <https://cran.r-project.org/web/packages/FKF.SP/index.html>

APA

Aspinall, T., Gepp, A., Harris, G., Kelly, S., Southam, C., Vanstone, B. J., Luethi, D., Erb, P., Otziger, S., & Smith, P. (2020, Dec 18). FKF.SP: Fast Kalman Filtering Through Sequential Processing. https://cran.r-project.org/web/packages/FKF.SP/index.html

CBE

Aspinall T, Gepp A, Harris G, Kelly S, Southam C, Vanstone BJ, Luethi D, Erb P, Otziger S, Smith P. 2020. FKF.SP: Fast Kalman Filtering Through Sequential Processing.

MLA

Aspinall, Thomas et al., FKF.SP: Fast Kalman Filtering Through Sequential Processing, 2020.

VancouverVancouver

Aspinall T, Gepp A, Harris G, Kelly S, Southam C, Vanstone BJ et al. FKF.SP: Fast Kalman Filtering Through Sequential Processing. 2020.

Author

Aspinall, Thomas ; Gepp, Adrian ; Harris, Geoffrey et al. / FKF.SP: Fast Kalman Filtering Through Sequential Processing. 2020.

RIS

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 -