Results 271 to 280 of about 3,251,267 (306)
The baboon as a statistician: Can non-human primates perform linear regression on a graph?
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WIREs Computational Statistics, 2012
AbstractLinear regression plays a fundamental role in statistical modeling. This article provides a step‐by‐step coverage of linear models in the order of model specification, model estimation, statistical inference, variable selection, model diagnosis, and prediction. Computation issues in linear regression and intimately relevant extensions of linear
Su, Xiaogang, Yan, Xin, Tsai, Chih Ling
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AbstractLinear regression plays a fundamental role in statistical modeling. This article provides a step‐by‐step coverage of linear models in the order of model specification, model estimation, statistical inference, variable selection, model diagnosis, and prediction. Computation issues in linear regression and intimately relevant extensions of linear
Su, Xiaogang, Yan, Xin, Tsai, Chih Ling
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On the linearity of regression
Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1982A stochastic process X={X t :t∈T| is called spherically generated if for each random vector $$X = (X_{t_1 } , \ldots ,X_{t_n } )$$ , there exist a random vector Y=(Y1,..., Y m) with a spherical (radially symmetric) distribution
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Linearized Ridge Regression Estimator in Linear Regression
Communications in Statistics - Theory and Methods, 2011In this article, we aim to study the linearized ridge regression (LRR) estimator in a linear regression model motivated by the work of Liu (1993). The LRR estimator and the two types of generalized Liu estimators are investigated under the PRESS criterion.
Feng Gao, Xu-Qing Liu
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2001
A linear regression model assumes that the regression function E(Y|X) is linear in the inputs X 1,..., X p . Linear models were largely developed in the precomputer age of statistics, but even in today’s computer era there are still good reasons to study and use them.
Jerome H. Friedman +2 more
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A linear regression model assumes that the regression function E(Y|X) is linear in the inputs X 1,..., X p . Linear models were largely developed in the precomputer age of statistics, but even in today’s computer era there are still good reasons to study and use them.
Jerome H. Friedman +2 more
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2010
Publisher Summary This chapter introduces the use of the regression model to make inferences on means of populations identified by specified values of one or more quantitative factor variables. It discusses the uses of the linear regression model and explains the procedures for the estimation of the parameters of that model and the subsequent ...
Donna L. Mohr +2 more
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Publisher Summary This chapter introduces the use of the regression model to make inferences on means of populations identified by specified values of one or more quantitative factor variables. It discusses the uses of the linear regression model and explains the procedures for the estimation of the parameters of that model and the subsequent ...
Donna L. Mohr +2 more
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1998
In this chapter, we study extensively the estimation of a linear relationship between two variables, Y i and X i , of the form: $${Y_i} = \alpha + \beta {X_i} + {u_i}\;i = 1,2, \ldots ,n$$ (3.1) where Y i denotes the i-th observation on the dependent variable Y which could be consumption, investment or output, and X i denotes the i-th ...
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In this chapter, we study extensively the estimation of a linear relationship between two variables, Y i and X i , of the form: $${Y_i} = \alpha + \beta {X_i} + {u_i}\;i = 1,2, \ldots ,n$$ (3.1) where Y i denotes the i-th observation on the dependent variable Y which could be consumption, investment or output, and X i denotes the i-th ...
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Correlation and Simple Linear Regression
2011Up until now in this book, you have been dealing with the situation in which you have had only one group or two groups of events or objects in your research study and only one measurement (i.e., variable) “number” on each of these. This chapter asks you to change gears again and to deal with the situation in which you are measuring two variables ...
Simone M. Cummings, Thomas J. Quirk
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Grouping and linear regression
Journal of Chronic Diseases, 1982With a large number of observations, the method of grouping is often employed to provide simpler graphs or tables. When one investigates the relationship between two variables, one usually groups based on the magnitude of the independent variable, and then plots the dependent variable averages against independent variable averages to get a clearer ...
Max Halperin +2 more
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