A New Log-location Regression Model with Influence Diagnostics and Residual Analysis

By Emrah Altun, Haitham M. Yousof, G. Hamedani. Facta Universitatis Series Mathematics and Informatics, 2018

60 citations recorded by the source corpus.

A new four-parameter lifetime model called OddLog-Logistic Burr XII distribution, is defined and investigated. Some of itsmathematical properties are derived. Some useful characterization resultsbased on \ the ratio of two truncated moments, based on the hazard functionas well as on the conditional expectation of certain functions of the randomvariable are presented. The maximum likelihood method is used to estimatethe model parameters by means of a graphical Monte Carlo simulation study.Moreover, we introduce a new log-location regression model based on theproposed distribution. The Jackknife estimation method as an alternativemethod is used to estimate the unknown parameters of new regression model. Thegeneralized cook distance and likelihood distance measures are used todetect the possible influential observations. The martingale and modifieddeviance residuals are defined to detect outliers and evaluate the modelassumptions. The potentiality of the new regression model is illustrated bymeans of a real data set.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a340731009880a427784cc090a7d3f95706c73ab

Citations in the corpus

• A Generalization of Lomax Distribution with Properties, Copula and Real Data Applications (2020, unknown): “A random variable (RV) is said to have the Lomax distribution if its survival function (SF) is given by Sα(y) = 1 − Πα(y) = (1 + y) |y≥0, (1)”