TY - JOUR
T1 - Understanding the kalman filter
AU - Meinhold, Richard J.
AU - Singpurwalla, Nozer D.
PY - 1983/5
Y1 - 1983/5
N2 - 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. © 1983 Taylor & Francis Group, LLC.
AB - 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. © 1983 Taylor & Francis Group, LLC.
KW - Bayesian inference
KW - Box-Jenkins models
KW - Exponential smoothing
KW - Forecasting
KW - Multivariate normal distribution
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=84950957313&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84950957313&origin=recordpage
U2 - 10.1080/00031305.1983.10482723
DO - 10.1080/00031305.1983.10482723
M3 - RGC 21 - Publication in refereed journal
SN - 0003-1305
VL - 37
SP - 123
EP - 127
JO - American Statistician
JF - American Statistician
IS - 2
ER -