The Nonparametric Path Function Estimation of Fourier Series at Low Oscillations for Modeling Timely Paying Credit

EasyChair Preprint no. 6839

Abstract

Purpose: This research aims to estimate the nonparametric path function of the Fourier series and to describe the lemma and theorem for the analysis of the nonparametric path of the Fourier series at low oscillation levels (K=2,3,4,5).

Method: The analytical method used is a Fourier series nonparametric path analysis with a low level of oscillation. Primary data is obtained from customers at a Bank (Bank X) in Indonesia. The data is in the form of item scores that are used as the average variable so that the average data scale is obtained which is the data of the relevant latent variable.

Findings: The function estimation in nonparametric path analysis using the Fourier series approach is . The best nonparametric path model that can describe the 5C variable on Time to Pay through Willingness to Pay is when the oscillation K=4 with R2 is 78%.

Originality: This study applies the Fourier series approach to path analysis in modeling on time to pay credit in the banking sector

Keyphrases: Fourier series, on-time pay, path analysis, willingness to pay

@Booklet{EasyChair:6839,
  author = {Sudarshan Bhalshankar},
  title = {The Nonparametric Path Function Estimation of Fourier Series at Low Oscillations for Modeling Timely Paying Credit},
  howpublished = {EasyChair Preprint no. 6839},

  year = {EasyChair, 2021}}