Testing the equality of several linear regression models

Filipe J. Marques, Carlos A. Coelho, Paulo C. Rodrigues

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The linear regression models are widely used in different research fields, and often there is the need to analyze if there are similarities between two or more different linear models or to verify if a given relation between two variables remains the same in different intervals of time, in particular in cases where small differences might make a big difference. Motivated by these problems the authors consider a test of equality of k linear regression models which is a simultaneous test of equality of slopes, intercepts and variances. In order to overcome the extreme difficulties that exist in the use of the exact distribution of the likelihood ratio test (LRT) statistic and to make this test reliable and easy to use, we propose the use of near-exact distributions to approximate the distribution of the LRT statistic, under (Formula presented.), in the balanced case, and of new asymptotic approximations for the unbalanced case. The near-exact approximations are built by approximating one factor of an adequate factorization of the characteristic function of the logarithm of the LRT statistic and may be easily implemented. The asymptotic approximations are developed using an expansion for the ratio of gamma functions. The quality of these approximations is analyzed and confirmed. Power studies are conducted in order to better assess the performance of the test. Finally to illustrate the applicability of the test we consider a real data set of gross domestic product at market prices and final consumption expenditure in European countries and one tests the existence of similarities between countries.

Original languageEnglish
Pages (from-to)1-28
Number of pages28
JournalComputational Statistics
DOIs
Publication statusPublished - 1 Dec 2017

Keywords

  • Characteristic function
  • Hypotheses testing
  • Linear models
  • Mixtures
  • Near-exact distributions

Fingerprint Dive into the research topics of 'Testing the equality of several linear regression models'. Together they form a unique fingerprint.

Cite this