The Sailing Boat Price Study Based on Principal Component Regression Analysis

Abstract

This paper conducts research on the pricing of second-hand sailboats under certain assumptions. Initially, a substantial amount of potentially relevant indicators and data related to sailboat pricing were collected from the internet. The Pearson correlation coefficient was used to investigate the correlation between these indicators and to filter them. Due to the distinctive characteristics of sailboats, they were categorized into monohull sailboats and catamarans for separate analysis. Subsequently, the processed data were used for price prediction using a BP neural network, yielding preliminary results. To obtain an explicit method for calculating sailboat prices, this paper employed principal component analysis to calculate the pricing objective function for both types of sailboats. This led to the derivation of two multivariate linear regression equations, which were subjected to significance testing. The results indicate that the objective functions obtained in this paper can serve as references for pricing second-hand sailboats.