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Linear regression : a mathematical introduction / Damodar N. Gujarati.

LIBRA QA278.2 .G8445 2019
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Format:
Book
Author/Creator:
Gujarati, Damodar N., author.
Series:
Quantitative applications in the social sciences ; no. 07-177.
Quantitative applications in the social sciences ; 177
Language:
English
Subjects (All):
Regression analysis.
Matrices.
Sampling (Statistics).
Local Subjects:
Matrices.
Regression analysis.
Sampling (Statistics).
Physical Description:
xxiv, 242 pages : illustrations ; 22 cm.
Place of Publication:
Thousand Oaks, California : Sage Publications, Inc., [2019]
Contents:
The linear regression model (LRM)
The classical linear regression model (CLRM)
The classical normal linear regression model: the method of maximum likelihood (ML)
Linear regression model: distribution theory and hypothesis testing
Generalized least squares (GLS): extensions of the classical linear regression model
Extensions of the classical linear regression model: the case of stochastic or endogenous regressors
Selected topics in linear regression.
Notes:
Includes bibliographical references and index.
ISBN:
9781544336572
1544336578
OCLC:
1031041736

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