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- W3208353634 abstract "In the teaching and researching of linear regression analysis, it is interesting and enlightening to explore how the dependent variable vector can be inner-transformed into regression coefficient estimator vector from a visible geometrical view. As an example, the roadmap of such inner transformation is presented based on a simple multiple linear regression model in this work. By applying the matrix algorithms like singular value decomposition (SVD) and Moore-Penrose generalized matrix inverse, the dependent variable vector lands into the right space of the independent variable matrix and is metamorphosed into regression coefficient estimator vector through the three-step of inner transformation. This work explores the geometrical relationship between the dependent variable vector and regression coefficient estimator vector as well as presents a new approach for vector rotating." @default.
- W3208353634 created "2021-11-08" @default.
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- W3208353634 date "2021-01-01" @default.
- W3208353634 modified "2023-09-27" @default.
- W3208353634 title "A Geometric View on Inner Transformation between the Variables of a Linear Regression Model" @default.
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- W3208353634 doi "https://doi.org/10.4236/am.2021.1210061" @default.
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