A geometric view on inner transformation between the variables of a linear regression model

Li, Zhaoyang (avtor), Antončič, Boštjan (avtor)

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.

• Jezik: Angleški jezik
• Ključne besede: econometrics, regression analysis, matrix singular value decomposition, Moore-Penrose generalized inverse, matrix inner transformation
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: EF - Ekonomska fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2021
• Št. strani: Str. 931-938
• Številčenje: Vol. 12, no. 10
• PID: 20.500.12556/RUL-134026
• UDK: 51-7
• ISSN pri članku: 2152-7385
• DOI: 10.4236/am.2021.1210061
• COBISS.SI-ID: 83841027
• Datum objave v RUL: 22.12.2021

Gradivo je del revije

• Naslov: Applied mathematics
• Skrajšan naslov: Appl. math.
• Založnik: Scientific Research Publishing, Inc.
• ISSN: 2152-7385
• COBISS.SI-ID: 1462364

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 29.10.2021

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: ekonometrija, regresijske analize