title: Inside of the Linear Relation between Dependent and Independent Variables.
abstract: Simple and multiple linear regression analyses are statistical methods used to investigate the link between activity/property of active compounds and the structural chemical features. One assumption of the linear regression is that the errors follow a normal distribution. This paper introduced a new approach to solving the simple linear regression in which no assumptions about the distribution of the errors are made. The proposed approach maximizes the probability of observing the event according to the random error. The use of the proposed approach is illustrated in ten classes of compounds with different activities or properties. The proposed method proved reliable and was showed to fit properly the observed data compared to the convenient approach of normal distribution of the errors.
authors.affiliation: Institute for Doctoral Studies, Technical University of Cluj-Napoca, Muncii Boulevard 103-105, 400641 Cluj-Napoca, Romania ; Institute for Doctoral Studies, Babeş-Bolyai University, Kogălniceanu Street No. 1, 400084 Cluj-Napoca, Romania ; Department of Chemistry, University of Oradea, Universităţii Street No. 1, 410087 Oradea, Romania.
authors.forename: Lorentz
authors.initials: L
authors.lastname: Jäntschi
authors.affiliation: Institute for Doctoral Studies, Babeş-Bolyai University, Kogălniceanu Street No. 1, 400084 Cluj-Napoca, Romania.
authors.forename: Lavinia L
authors.initials: LL
authors.lastname: Pruteanu
authors.affiliation: Department of Chemistry, University of Oradea, Universităţii Street No. 1, 410087 Oradea, Romania ; Department of Medical Informatics and Biostatistics, Iuliu Haţieganu University of Medicine and Pharmacy, Louis Pasteur Street No. 6, 400349 Cluj-Napoca, Romania.
authors.forename: Alina C
authors.initials: AC
authors.lastname: Cozma
authors.affiliation: Department of Medical Informatics and Biostatistics, Iuliu Haţieganu University of Medicine and Pharmacy, Louis Pasteur Street No. 6, 400349 Cluj-Napoca, Romania.
authors.forename: Sorana D
authors.initials: SD
authors.lastname: Bolboacă
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D015233:Models, Statistical; D021281:Quantitative Structure-Activity Relationship