Author: Phillip Dean WittmerPublisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 122
Book Description
Biased Estimation Techniques for Multiple Linear Regression
Author: Phillip Dean WittmerPublisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 122
Book Description
Two Biased Estimation Techniques in Linear Regression: Application to Aircraft
Author: Milking Data Through Biased Regression Techniques
Author: R. F. GunstPublisher:
ISBN:
Category :
Languages : en
Pages : 8
Book Description
The recent interest in biased estimation procedures in multiple linear regression arises from the large variances of the least squares estimators (unbiased) of the regression coefficients when multicollinearities are present. The biased estimation procedures greatly reduce this variance at the cost of some bias. It is the purpose of this paper to look at this bias with reference to the nature of the specific problem being investigated. (Author).
The Combination of Biased and Robust Estimation Techniques in Multiple Regression Models
Author: Ronald Gene AskinPublisher:
ISBN:
Category : Regression analysis
Languages : en
Pages : 434
Book Description
Biased Estimators for the Parameters of Linear Regression Model
Author: Bushra Abdalrasool AliPublisher: LAP Lambert Academic Publishing
ISBN: 9783659388736
Category :
Languages : en
Pages : 96
Book Description
This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations.
On the Biased Estimation in Regression
Author: Esko LeskinenPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 168
Book Description
Biased Estimation as a Solution to the Multicollinearity Problem in Multiple Linear Regression
Author: Albert Joseph KleePublisher:
ISBN:
Category : Multicollinearity
Languages : en
Pages : 546
Book Description
Applied Econometrics with R
Author: Christian KleiberPublisher: Springer Science & Business Media
ISBN: 0387773185
Category : Business & Economics
Languages : en
Pages : 229
Book Description
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.
New Methods and Comparative Evaluations for Robust and Biased- Robust Regression Estimation
Author: James Robert SimpsonPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 26
Book Description
Comparison of Some Biased Estimation Methods (including Ordinary Subset Regression) in the Linear Model
Author: Steven M. SidikPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 50
Book Description