Functional Linear Regression Analysis Based on Partial Least Squares and Its Application

Wang, Huiwen; Huang, Lele

doi:10.1007/978-3-319-40643-5_15

Cited by 10 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After extracting the first principal component t 1 and u 1 , PLS implements X regression of t 1 and Y regression of t 1 respectively. The algorithm will be terminated if the regression equation reaches a satisfactory accuracy, while it continues to extract the second principal component until reaching the [16].…”

Section: Methodsmentioning

confidence: 99%

Empirical Research on the Influence Factors of E-commerce Development in China

Wang¹,

Liu²

2015

TOCSJ

View full text Add to dashboard Cite

Due to multiple factors affecting e-commerce development, in the environment of network growth, specifically the dramatic increase of mobile Internet users, how to grasp the key influence factors and enhance the healthy development of e-commerce in China? This paper discusses the influence factors of e-commerce development from the perspectives of information infrastructure construction, economic level, educational level, urbanization level, technology level, living standards, human capital level and price index. Based on the time series data from year 2000 to 2012, this paper proposes the influence factor model of e-commerce development by partial least square regression, and analyzes the influence factors using correlation coefficient and variable importance in projection. The research findings show that the most critical factors affecting e-commerce development in China are mobile phone penetration, per capita disposable income, number of computers per hundred households and urbanization rate; and real GDP per capita, knowledge index and Internet penetration also have a certain impact on e-commerce development. This paper reveals the key factors affecting e-commerce development and puts forward some reasonable suggestions in the aspects of information infrastructure construction, mobile e-commerce development, people's living standards and cultural quality.

show abstract

Section: Methodsmentioning

confidence: 99%

Empirical Research on the Influence Factors of E-commerce Development in China

Wang¹,

Liu²

2015

TOCSJ

View full text Add to dashboard Cite

show abstract

“…The PLS method is identified by Wold et al as a particularly useful multivariate statistical analysis method [32]. It surmounts the issue of multicollinearity because of the comprehensive means of extracting components and information and its screening methodology [33].…”

Section: Pls Modelmentioning

confidence: 99%

Decomposition and Forecasting of CO2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

Cui

Zhao

2018

Energies

View full text Add to dashboard Cite

China faces significant challenges related to global warming caused by CO2 emissions, and the power industry is a large CO2 emitter. The decomposition and accurate forecasting of CO2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) > line loss rate (1.112) > GDP per capita (0.669) > generation structure (0.522) > the urbanization level (0.512) > electricity intensity (0.310) > industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

show abstract

“…Li uses the Partial Least Squares Regression (PLSR) methods to establish airliner's price prediction model 3 . The PLSR methods have good practical value by integrating the methods of regression modeling, correlation analysis and principal components analysis together 4 . However, the computation process becomes rather complex and with low efficiency when variable numbers become large.…”

Section: _________________________________________mentioning

confidence: 99%

Method for Price Prediction and Analysis for Airliner Based on Hierarchical Partial Least Squares Regression During Overall Design

Ma¹,

Song²,

Yang³

2017

dtcse

View full text Add to dashboard Cite

Concerning the difficulties of lots of independent variables, high dependency and high risk of losing key information during the modeling process of airliner price prediction, this paper makes use of the advantage of Hierarchical PLSR (Hi-PLSR) in handling small-sample multivariate data fitting to establish the price prediction model based on the design parameters during overall design. The selected design parameters were divided into several groups so as to analysis the influence of various variables on the price and screen out the price driving factors. Then price prediction model was established through the Hi-PLSR method and the model's prediction precision was verified. At last, engineering value ratio was used to modify the model so as to build a price prediction model suitable for the jetliners made in different countries. The calculation and analysis process suggested that Hi-PLSR method overcoming the difficulties mentioned above can efficiently reflect the relationship between the design parameters and the price.

show abstract

Functional Linear Regression Analysis Based on Partial Least Squares and Its Application

Cited by 10 publications

References 25 publications

Empirical Research on the Influence Factors of E-commerce Development in China

Empirical Research on the Influence Factors of E-commerce Development in China

Decomposition and Forecasting of CO2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

Method for Price Prediction and Analysis for Airliner Based on Hierarchical Partial Least Squares Regression During Overall Design

Contact Info

Product

Resources

About