A New Biased Estimator Derived from Principal Component Regression Estimator

A New Biased Estimator Derived from Principal Component Regression Estimator

Show other versions (1)

A new biased estimator obtained by combining the Principal Component Regression Estimator and the special case of Liu-type estimator is proposed. The properties of the new estimator are derived and comparisons between the new estimator and other estimators in terms of mean squared error are presente...

Full description

Bibliographic Details
Main Authors:	Low, HC (Author), Ng, SF (Author), Quah, SH (Author)
Format:	Article
Language:	English
Series:	JOURNAL OF MODERN APPLIED STATISTICAL METHODS
Online Access:	View Fulltext in Publisher

Similar Items

A new biased estimator derived from principal component regression estimator
by: Low, H.C, et al.

Fractional principal components regression: a general approach to biased estimators
by: Lee, Wonwoo
Published: (2014)

Combining modified ridge-type and principal component regression estimators
by: Adewale F. Lukman, et al.
Published: (2020-09-01)

A Stochastic Restricted Principal Components Regression Estimator in the Linear Model
by: Daojiang He, et al.
Published: (2014-01-01)

A Principal Component Regression Approach for Estimating Ventricular Repolarization Duration Variability
by: Pasi A. Karjalainen, et al.
Published: (2007-01-01)

A Principal Component Regression Approach for Estimating Ventricular Repolarization Duration Variability
by: Laitinen Tomi, et al.
Published: (2007-01-01)

Performance of a New Restricted Biased Estimator in Logistic Regression
by: Yasin ASAR
Published: (2018-04-01)

Two Classes of Almost Unbiased Type Principal Component Estimators in Linear Regression Model
by: Yalian Li, et al.
Published: (2014-01-01)

Evaluating the Use of Ridge Regression and Principal Components in Propensity Score Estimators under Multicollinearity
by: Gripencrantz, Sarah
Published: (2014)

Biased estimation techniques for multiple linear regression
by: Wittmer, Phillip Dean
Published: (2011)

The principal problem with principal components regression
by: Heidi Artigue, et al.
Published: (2019-01-01)

A new biased estimator for multivariate regression models with highly collinear variables
by: Wissel, Julia
Published: (2009)

A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
by: Issam Dawoud, et al.
Published: (2020-11-01)

The Analysis and Prediction of Stock Price from Macro-Economic Factors: An Application of Principal Component Regression, Fuzzy Linear Regression and Stein Estimation
by: Lou, Yu-Mei, et al.
Published: (1996)

Ridge and related biased estimators in linear regression models
by: Willis, Thomas F
Published: (1979)

On Robustness of Principal Component Regression
by: Agarwal, Anish, et al.
Published: (2022)

Modified principal components regression
by: Wu, Huan-Ter
Published: (2015)

Principal Component and Multiple Regression Analyses for the Estimation of Suspended Sediment Yield in Ungauged Basins of Northern Thailand
by: Piyawat Wuttichaikitcharoen, et al.
Published: (2014-08-01)

The combination of biased and robust estimation techniques in multiple regression models
by: Askin, Ronald Gene
Published: (2008)

Ridge regression : biased estimation based on ill-conditioned data
by: Bulmahn, Barbara J.
Published: (2011)

Nonparametric Principal Components Regression Compared with Forward Regression
by: Chen, Hong Rui, et al.
Published: (2016)

Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation
by: Sharad Damodar Gore, et al.
Published: (2009-10-01)

Derivation of TEC and estimation of instrumental biases from GEONET in Japan
by: G. Ma, et al.
Published: (2003-10-01)

Two Kinds of Weighted Biased Estimators in Stochastic Restricted Regression Model
by: Chaolin Liu, et al.
Published: (2014-01-01)

Evaluation of predictive equations using biased estimators for the linear regression model
by: Friedman, David J.
Published: (2010)

Principal component approach in variance component estimation for international sire evaluation
by: Jakobsen Jette, et al.
Published: (2011-05-01)

Permutation tests to estimate significances on Principal Components Analysis
by: Vasco M. N. C. S. Vieira
Published: (2012-06-01)

Data Restoration by Linear Estimation of the Principal Components From Lossy Data
by: Yonggeol Lee, et al.
Published: (2020-01-01)

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America
by: T. Soares dos Santos, et al.
Published: (2016-01-01)

Robust estimation of the number of components for mixtures of linear regression
by: Meng, Li
Published: (2014)

Local Linear Principle Component Regression Function Estimation.
by: Ming-Horng Lin, et al.
Published: (1999)

Bias-corrected variance components estimation of Partial EIV model
by: WANG Leyang, et al.
Published: (2019-05-01)

Stochastic Restricted Biased Estimators in Misspecified Regression Model with Incomplete Prior Information
by: Manickavasagar Kayanan, et al.
Published: (2018-01-01)

A new estimator and its performance / Ng Set Foong, Low Heng Chin and Quah Soon Hoe
by: Ng, Set Foong, et al.
Published: (2009)

Reducing the bias of estimates of genotype by environment interactions in random regression sire models
by: Meuwissen Theo HE, et al.
Published: (2009-03-01)

Efficient Semiparametric Estimators for Nonlinear Regressions and Models under Sample Selection Bias
by: Kim, Mi Jeong
Published: (2012)

Bias of using odds ratio estimates in multinomial logistic regressions to estimate relative risk or prevalence ratio and alternatives
by: Suzi Alves Camey, et al.
Published: (2014-01-01)

Curve estimation based on localised principal components : theory and applications
by: Zayed, Mohammad Abd-Allateef
Published: (2011)

Pemodelan Principal Component Regression dengan Software R
by: Margaretha Ohyver
Published: (2012-06-01)

Ridge regression and principal components regression : Some finite sample results and extensions
by: Firinguetti, L.
Published: (1982)