A recent review (Horton 2008) of the second edition of Multilevel and Longitudinal Modeling Using Stata (Rabe-Hesketh and Skrondal 2008) decried the lack of support in previous versions of Stata for models within the xtmixed command that directly estimate the variance-covariance matrix (akin to...
The classical Riccati equation for the prediction error covariance arises in linear estimation and is derived by the discrete time Kalman filter equations. New Riccati equations for the estimation error covariance as well as for the smoothing error covariance are presented. These equations have the sam...
Error covariance matrix estimationDynamical couplingLocal projection methodsWe estimate the covariance matrix of the errors in several dynamically coupled time series corrupted by measurement errors. We say that several scalar time series are dynamically coupled if they record the values of measurements of...
Finally, asymptotic boundedness of estimation error covariance is analyzed. The focus of this paper is on the event-triggered transmission scheme design and performance analysis of event-based distributed state estimation subject to both unknown input and false data injection attack. Main contributions ...
estatsummarize summary statistics for the estimation sampleestatvce variance–covariance matrix of the estimators (VCE)estimatescataloging estimation resultsforecastdynamic forecasts and simulations lincompoint estimates, standard errors, testing, and inference for linear combinationsofcoefficients ...
Without knowledge on prior information about the state during the filtering process, it will be difficult to propagate the estimation-error covariance. Thus the filtering process needs to utilize the inverse of estimation-error covariance rather than estimation-error covariance, and the corresponding ...
步骤一: Initialize the parameter and covariance estimates: 如果测量之前对 一无所知, ,如果对 有充分的了解, . 步骤二: 假设 其中 是均值为 0,协方差为 的随机变量,每一时刻 k 的测量噪声 相互独立。 更新Estimation 的值 和estimation Error 的值 ...
1. Initialize the mean \(\overline{x}_{0}\) of the battery state vector X0 and the state estimation error covariance matrix P0. $$\left\{ \begin{gathered} \overline{x}_{0} = E(x_{0} ) \hfill \\ P_{0} = E[(x_{0} - \overline{x}_{0} )(x_{0} - \overline{x}_...
A two-step generalized least-squares (GLS) estimator proposed by Zellner for seemingly unrelated regression (SUR) models is implementable when the estimated covariance matrix of the errors in the SUR system is non-singular. Violating the premise of non-singularity is a common problem among many ap...
步骤一: Initialize the parameter and covariance estimates: \hat{x}_0=E(x) P_0 = E[(x-\hat{x}_0)(x-\hat{x}_0)^T] 如果测量之前对 x 一无所知,P_0=\infty I ,如果对 x 有充分的了解, P_0=0。步骤二: 假设 y_k=H_kx + v_k 其中v_k 是均值为0,协方差为 R_k 的随机...