Results 31 to 40 of about 75,653 (260)
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
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HAC ESTIMATION BY AUTOMATED REGRESSION [PDF]
Econometric Theory, 2005 Summary: A simple regression approach to heteroskedastic and autocorrelation consistent (HAC) and long run variance (LRV) estimation is suggested. The method exploits the fact that the quantities of interest relate to only one point of the spectrum (the origin).
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Handling Nonresponse in Business Surveys
Survey Research Methods, 2012 Business surveys are a valuable indication of the current and the future economic situation. However refusals are very common in this context and may induce bias in the estimates of interest.
Riccardo Borgoni +2 more
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Mathematics, 2023 For nonparametric regression estimation, conventional research all focus on isotropic regression function. In this paper, a linear wavelet estimator of anisotropic regression function is constructed, the rate of convergence of this estimator is discussed
Jia Chen, Junke Kou
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Improved Mixed Estimator Using Two Auxiliary Variables For Full Extreme Maximum And Minimum Values In Single Phase Sampling [PDF]
المجلة العراقية للعلوم الاحصائيةThe use of multiple auxiliary variables has been established to improve precision in the estimators of ratio, regression and product respectively. However, the presence of extreme values in the distribution could annul such efficiency Olatayo et al ...
Timothy O. Olatayo +2 more
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Regression Estimator for the Tail Index [PDF]
Journal of Statistical Theory and Practice, 2020 AbstractEstimating the tail index parameter is one of the primal objectives in extreme value theory. For heavy-tailed distributions the Hill estimator is the most popular way to estimate this parameter. Several recent publications’ aim was to improve the Hill estimator, using different methods, for example the bootstrap, or the Kolmogorov–Smirnov ...
László Németh, András Zempléni
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Minimax Ridge Regression Estimation. [PDF]
The Annals of Statistics, 1977 The technique of ridge regression, first proposed by Hoerl and Kennard, has become a popular tool for data analysts faced with a high degree of multicollinearity in their data. By using a ridge estimator, one hopes to both stabilize one's estimates (lower the condition number of the design matrix) and improve upon the squared error loss of the least ...
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Estimation in regression models with externally estimated parameters [PDF]
Biostatistics, 2005 In many regression applications, some of the model parameters are estimated from separate data sources. Typically, these estimates are plugged into the regression model and the remainder of the parameters is estimated from the primary data source. This situation arises frequently in compartment modeling when there is an external input function to the ...
Tarpey, Thaddeus, Ogden, R. Todd
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Partial AUC Estimation and Regression
Biometrics, 2003 Summary. Accurate diagnosis of disease is a critical part of health care. New diagnostic and screening tests must be evaluated based on their abilities to discriminate diseased from nondiseased states. The partial area under the receiver operating characteristic (ROC) curve is a measure of diagnostic test accuracy.
Dodd, Lori E., Pepe, Margaret S.
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with sickle cell anemia (SCA) in low‐income settings are at risk of severe malnutrition, but optimal nutritional management has not been established. We evaluated an intensified ready‐to‐use therapeutic food (RUTF) regimen in children with persistent severe malnutrition after initial treatment and assessed whether early ...
Safiya Gambo +9 more
wiley +1 more source