Understanding the Kalman Filter. Meinhold, R. J. & Singpurwalla, N. D. The American Statistician, 37:123–127, 1983. Paper abstract bibtex This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if we use a Bayesian formulation and some well-known results in multivariate statistics. We also give a simple example illustrating the use of the Kalman filter for quality control work.
@article{meinhold_understanding_1983,
title = {Understanding the {Kalman} {Filter}},
volume = {37},
issn = {00031305},
url = {http://www.jstor.org/stable/2685871},
abstract = {This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if we use a Bayesian formulation and some well-known results in multivariate statistics. We also give a simple example illustrating the use of the Kalman filter for quality control work.},
urldate = {2008-11-17},
journal = {The American Statistician},
author = {Meinhold, R. J. and Singpurwalla, N. D.},
year = {1983},
keywords = {kalman},
pages = {123--127}
}
Downloads: 0
{"_id":"LCGqvMtzWSxz9zvZJ","bibbaseid":"meinhold-singpurwalla-understandingthekalmanfilter-1983","authorIDs":[],"author_short":["Meinhold, R. J.","Singpurwalla, N. D."],"bibdata":{"bibtype":"article","type":"article","title":"Understanding the Kalman Filter","volume":"37","issn":"00031305","url":"http://www.jstor.org/stable/2685871","abstract":"This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if we use a Bayesian formulation and some well-known results in multivariate statistics. We also give a simple example illustrating the use of the Kalman filter for quality control work.","urldate":"2008-11-17","journal":"The American Statistician","author":[{"propositions":[],"lastnames":["Meinhold"],"firstnames":["R.","J."],"suffixes":[]},{"propositions":[],"lastnames":["Singpurwalla"],"firstnames":["N.","D."],"suffixes":[]}],"year":"1983","keywords":"kalman","pages":"123–127","bibtex":"@article{meinhold_understanding_1983,\n\ttitle = {Understanding the {Kalman} {Filter}},\n\tvolume = {37},\n\tissn = {00031305},\n\turl = {http://www.jstor.org/stable/2685871},\n\tabstract = {This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if we use a Bayesian formulation and some well-known results in multivariate statistics. We also give a simple example illustrating the use of the Kalman filter for quality control work.},\n\turldate = {2008-11-17},\n\tjournal = {The American Statistician},\n\tauthor = {Meinhold, R. J. and Singpurwalla, N. D.},\n\tyear = {1983},\n\tkeywords = {kalman},\n\tpages = {123--127}\n}\n\n","author_short":["Meinhold, R. J.","Singpurwalla, N. D."],"key":"meinhold_understanding_1983","id":"meinhold_understanding_1983","bibbaseid":"meinhold-singpurwalla-understandingthekalmanfilter-1983","role":"author","urls":{"Paper":"http://www.jstor.org/stable/2685871"},"keyword":["kalman"],"downloads":0,"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/w_cools","creationDate":"2020-06-07T16:33:24.870Z","downloads":0,"keywords":["kalman"],"search_terms":["understanding","kalman","filter","meinhold","singpurwalla"],"title":"Understanding the Kalman Filter","year":1983,"dataSources":["DPzNnv8mwEoHbb7Cq"]}