Results 31 to 40 of about 7,731 (299)
A Generalized Linear Transformation and Its Effects on Logistic Regression
Mathematics, 2023 Linear transformations such as min–max normalization and z-score standardization are commonly used in logistic regression for the purpose of scaling.
Guoping Zeng, Sha Tao
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Mathematics, 2020 In the modeling and analysis of reliability data via the Lindley distribution, the maximum likelihood estimator is the most commonly used for parameter estimation. However, the maximum likelihood estimator is highly sensitive to the presence of outliers.
Muhammad Aslam Mohd Safari +2 more
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An Unbiased Two-Parameter Estimation with Prior Information in Linear Regression Model
The Scientific World Journal, 2014 We introduce an unbiased two-parameter estimator based on prior information and two-parameter estimator proposed by Özkale and Kaçıranlar, 2007. Then we discuss its properties and our results show that the new estimator is better than the two-parameter ...
Jibo Wu
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Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model
The Scientific World Journal, 2020 The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to estimate its parameter.
Adewale F. Lukman +3 more
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Consistent estimation in an implicit quadratic measurement error model
, 2004 An adjusted least squares estimator is derived that yields a consistent estimate of the parameters of an implicit quadratic measurement error model. In addition, a consistent estimator for the measurement error noise variance is proposed.
Er Kukush +5 more
core +1 more source
Robust-stein estimator for overcoming outliers and multicollinearity
Scientific Reports, 2023 Linear regression models with correlated regressors can negatively impact the performance of ordinary least squares estimators. The Stein and ridge estimators have been proposed as alternative techniques to improve estimation accuracy.
Adewale F. Lukman +3 more
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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
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CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3
Molecular Oncology, EarlyView.PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh +12 more
wiley +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
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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
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