Parameter identification for multiperiodic functions


Munir M., Kausar N., Shakil M.

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, vol.173, 2021 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 173
  • Publication Date: 2021
  • Doi Number: 10.1016/j.techfore.2021.121134
  • Journal Name: TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
  • Journal Indexes: Social Sciences Citation Index, Scopus, ABI/INFORM, Aquatic Science & Fisheries Abstracts (ASFA), INSPEC, Political Science Complete, Social services abstracts, Sociological abstracts, Worldwide Political Science Abstracts, DIALNET
  • Keywords: Bi-Logistic population growth, Periodic extension, Time-varying carrying, Sensitivity functions, Parameter estimates, Almost periodic functions, GROWTH, MODEL, WAVE

Abstract

In this paper, we first present the idea of multiperiodic extension for a given function. These functions called the multiperiodic or the extended period functions have more than one period or a vector period instead of a scalar number. We present a method to estimate the parameters of these multiperiodic functions using the data collected from their given functions. The results on the parameter estimation, sensitivity functions and generalized sensitivity analysis of the multiperiodic extensions of the functions show that this method is useful for estimating the parameters of a larger model describing a more complex system on the basis of the parameter estimation of the smaller model describing a simpler or a smaller system.