Estimating the Efforts of Mobile Application Development in the Planning Phase Using Nonlinear Regression Analysis

• Main Authors: Prykhodko Sergiy, Prykhodko Natalia, Knyrik Kateryna
• Format: Article
• Language: English
• Published: Sciendo 2020-12-01
• Series: Applied Computer Systems
• Subjects: estimation; maximum likelihood estimation; mobile applications; parameter estimation; planning; regression analysis; transform
• Online Access: https://doi.org/10.2478/acss-2020-0019
• ISSN: 2255-8691

The authors consider the construction of a nonlinear multiple regression model, its confidence and prediction intervals to evaluate the efforts of mobile application development in the planning phase based on the multivariate normalizing transformation and outlier detection. The constructed model is compared to the linear regression model and nonlinear regression models based on the univariate transformations, such as the decimal logarithm, Box–Cox, and Johnson transformation. This model, in comparison with other regression models, has better prediction accuracy.