Parametric Models of the Learning Curve Effects with Continuous Responses

• 발행기관: 한국자료분석학회
• 저자명: So-Young Kim Man Sik Park
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.14 No.2, 567~576쪽, 전체 10쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2012.04.30

영문 초록

In general, as a person gets much experience of a certain task, he tends to complete the job more quickly in that he becomes good at the job. This natural phenomenon is called ‘law of diminishing returns’ in economics or the learning curve effects. The learning curve is a graphical representation of the effects. If the elapsed time decreases as time goes by, learning curve is represented as a monotonically decreasing pattern over the time. In this paper, we propose new models for estimating the learning curve effects and provide some useful information on how many trials we need in order to overcome the learning curve (or to become proficient) and how much time he is supposed to spend to complete the job. We adopt some usual cumulative distribution functions (cdf) to capture the shapes of learning curves. We evaluate performance and uniqueness of models proposed here in the simulation.

목차

1. Introduction

2. Estimation Methods Review

3. The Proposed Models

4. Simulation Studies

5. Conclusions

Reference

키워드

learning curve cumulative density function analysis of variance cumulative sum moving average