Results 31 to 40 of about 75,728 (293)
On the biased Two-Parameter Estimator to Combat Multicollinearity in Linear Regression Model
African Scientific Reports, 2022 The most popularly used estimator to estimate the regression parameters in the linear regression model is the ordinary least-squares (OLS). The existence of multicollinearity in the model renders OLS inefficient.
Janet Iyabo Idowu +3 more
doaj +1 more source
The Effect of Microaggregation Procedures on the Estimation of Linear Models: A Simulation Study [PDF]
, 2005 Microaggregation is a set of procedures that distort empirical data in order to guarantee the factual anonymity of the data. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific ...
Schmid, Matthias, Schneeweiß, Hans
core +2 more sources
Robust linear least squares regression [PDF]
, 2011 We consider the problem of robustly predicting as well as the best linear combination of $d$ given functions in least squares regression, and variants of this problem including constraints on the parameters of the linear combination.
Audibert, Jean-Yves, Catoni, Olivier
core +6 more sources
Pemodelan Regresi Nonparametrik dengan Estimator Spline Truncated vs Deret Fourier
Jambura Journal of Mathematics, 2021 ABSTRAK Pendekatan regresi nonparametrik digunakan apabila hubungan antara variabel prediktor dan variabel respon tidak diketahui polanya. Spline truncated dan deret Fourier merupakan estimator dalam pendekatan nonparametrik yang terkenal, karena ...
Andrea Tri Rian Dani +1 more
doaj +1 more source
African Scientific Reports, 2022 Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated.
Abiola T. Owolabi +2 more
doaj +1 more source
Effects of a single outlier on the coefficient of determination: an empirical study [PDF]
, 2014 This article investigates the effects of outliers on the coefficient of determination, R2 which is computed by Ordinary Least Squares (OLS) estimator. It is now evident that the OLS is greatly affected by outliers and hence the R2 is also affected.
Fitrianto, Anwar +3 more
core +1 more source
Convex Combination of Ordinary Least Squares and Two-stage Least Squares Estimators
, 2015 In the presence of confounders, the ordinary least squares (OLS) estimator is known to be biased. This problem can be remedied by using the two-stage least squares (TSLS) estimator, based on the availability of valid instrumental variables (IVs). This reduction in bias, however, is offset by an increase in variance.
Ginestet, Cedric E. +2 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Families of children with cancer experience significant financial strain, even with universal healthcare. Indirect costs, such as productivity losses and non‐medical expenses, are rarely included in economic evaluations, and little is known about how effectively financial aid programmes alleviate this burden. Childhood brain tumours
Megumi Lim +8 more
wiley +1 more source
Combining modified ridge-type and principal component regression estimators
Scientific African, 2020 The performance of ordinary least squares estimator (OLSE) when there is multicollinearity (MC) in a linear regression model becomes inefficient. The principal components regression and the modified ridge-type estimator have been proposed at a different ...
Adewale F. Lukman +3 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Survivors of childhood acute lymphoblastic leukemia (ALL) often exhibit early deficits in muscle and movement competence, which can compromise long‐term health. Integrative neuromuscular training (INT), a multifaceted approach combining fundamental movement activities with strength exercises, may help address these deficits during ...
Anna Maria Markarian +7 more
wiley +1 more source