Results 11 to 20 of about 82,111 (284)
A new biased regression estimator: Theory, simulation and application
Scientific African, 2022 The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud +2 more
doaj +1 more source
Finite-time Identification of Stable Linear Systems Optimality of the Least-Squares Estimator [PDF]
IEEE Conference on Decision and Control, 2020 We present a new finite-time analysis of the estimation error of the Ordinary Least Squares (OLS) estimator for stable linear time-invariant systems. We characterize the number of observed samples (the length of the observed trajectory) sufficient for ...
Yassir Jedra, Alexandre Proutière
semanticscholar +1 more source
A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
Stats, 2020 In a multiple linear regression model, the ordinary least squares estimator is inefficient when the multicollinearity problem exists. Many authors have proposed different estimators to overcome the multicollinearity problem for linear regression models ...
Issam Dawoud, B. M. Golam Kibria
doaj +1 more source
Inference in Linear Models with Nonstochastic Biased Factors [PDF]
The Egyptian Statistical Journal, 1996 Obenchain (1977) claimed that ridge techniques with nonstochastic of biased factors don't generally yield "new" normal theory statistical inference than that used in least squares technique, and that the t and F statistics are identical under both ...
Abdul-Mordy Azzam
doaj +1 more source
Lietuvos Matematikos Rinkinys, 2023 In this paper we present estimated generalized least squares (EGLS) estimator for the coefficient vector β in the linear regression model y = βX + ε, where disturbance term can be heteroskedastic.
Alfredas Račkauskas, Danas Zuokas
doaj +3 more sources
Scientific African, 2023 Scholars usually adopt the method of least squared to model the relationship between a response variable and two or more explanatory variables. Ordinary least squares estimator's performance is good when there is no outliers and multicollinearity in the ...
K.C. Arum +5 more
doaj +1 more source
Shiller's Distributed Lag Estimator: Exact Finite Sample Results [PDF]
The Egyptian Statistical Journal, 1988 This paper is concerned with Shiner's estimator of papameters in a polynomial distributed lag models. The purpose here is to derive the exact moments of Shiller's estimator analytically, and compare its mean square error (MSE) with (1) MSE of ordinary ...
G.A. Ghazal, A.H. Harroun
doaj +1 more source
Effect of Multicollinearity on Power Rates of the Ordinary Least Squares Estimators [PDF]
Journal of Mathematics and Statistics, 2008 Summary: Inferences on the parameter estimates of the Ordinary Least Square (OLS) estimator in regression models when regressors exhibit multicollinearity is a problem in that large standard errors of the regression coefficients which cause low t-statistic values often result into the acceptance of the null hypothesis.
Alabi, O. O. +2 more
openaire +2 more sources
Dynamic system multivariate calibration by system identification methods [PDF]
Modeling, Identification and Control, 1998 In the first part of the paper, the optimal estimator for normally nonmeasured primary outputs from a linear and time invariant dynamic system is developed.
Rolf Ergon
doaj +1 more source
Superiority of the MCRR Estimator Over Some Estimators In A Linear Model [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 Modified (r, k) class ridge regression (MCRR) which includes unbiased ridge regression (URR), (r, k) class, principal components regression (PCR) and the ordinary least squares (OLS) estimators is proposed in regression analysis, to overcome the problem ...
Feras Sh. M. Batah
doaj +1 more source