After computing the sample autocovariance matrices, PROC STATESPACE fits a sequence of vector autoregressive models. These preliminary autoregressive models are used to estimate the autoregressive ...
Abstract: In this paper, the autocovariance least-squares (ALS) technique is proposed to estimate the Global Positioning System (GPS) pseudorange measurement noise-covariance matrix. The large GPS ...
Abstract: The technical note focuses on the estimation of the noise covariance matrices of the state space models. Stress is laid on the autocovariance least-squares method providing unbiased ...
Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 73, No. 5 (NOVEMBER 2011), pp. 711-728 (18 pages) The paper addresses a 'large p-small n' problem in a time series ...
Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain
In this talk, I will present a novel shape-constrained estimator of the autocovariance sequence resulting from a reversible Markov chain. A motivating application for studying this problem is the ...
In this study, we review the role of wearable devices in tracking our daily locomotion. We discuss types of wearable devices that can be used, methods for gait analyses, and multiple ...
1 Business School, Hohai University, Nanjing, China. 2 School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, China. Agriculture plays a crucial role in ...
Gives analytic formulas to calculate autocovariance matrix and autocorrelation matrix for averaged Wiener process with equal-distance time points. Is supplemented with Python numpy code to verify ...
Many scientific and economic applications involve the analysis of high-dimensional functional time series, which stands at the intersection between functional time series and high-dimensional ...
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