General theoretical notions on univariate regression

Constantin Anghelache, Ion Partachi, Madalina-Gabriela Anghel, Gyorgy Bodo and Radu Stoian
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Constantin Anghelache: Academia de Studii Economice din Bucuresti/Universitatea „Artifex„ din Bucuresti
Ion Partachi: Academia de Studii Economice a Moldovei, Chisinau
Madalina-Gabriela Anghel: Universitatea „Artifex„ din Bucuresti
Gyorgy Bodo: Academia de Studii Economice din Bucuresti
Radu Stoian: Academia de Studii Economice din Bucuresti

Romanian Statistical Review Supplement, 2016, vol. 64, issue 11, 136-144

Abstract: In this article, the authors started from the fact that in general, the concept of conditional probability and the conditional linear probability in terms of orthogonal projections are common to the crowd of linear functions. Against this background, a presentation on the main conditionality involved in univariate regression was conducted. Thus, linearity, uncolinerity and conditional normality are presented and demonstrated. At the same time, homoscedasticitate conditioning is highlighed. Further, the presentation of conditions linearity and homoscedasticitate is based on the concept of error highlighting to be considered for univariate regression. Further, it points out that the estimation is performed by the method of least squares parameter which reduces to beta estimation. Another element considered and clarified concerns the replacement of the probability through the distribution probability sampling, that is subject to minimization criterion.

Keywords: Conditional probability; integrable function; exogenous variable; univariate regression; orthogonal projection (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:rsr:supplm:v:64:y:2016:i:11:p:136-144

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