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- W2716916363 abstract "Abstract The Kaiman filtering algorithm and the least-mean-squres (LMS) algorithm are two standard methods for estimating time-varying parameters in a linear regression model. This paper establishes the upper bounds for parameter tarcking errors produced by these two algorithms, without resorting to stationary or independency assumptions on the regressors." @default.
- W2716916363 created "2017-06-30" @default.
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- W2716916363 date "1992-07-01" @default.
- W2716916363 modified "2023-09-25" @default.
- W2716916363 title "Estimating Time-Varying Parameters in Regression Models" @default.
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- W2716916363 doi "https://doi.org/10.1016/s1474-6670(17)50620-5" @default.
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