Description
Statistical computing problems wildly exist in modern structural equation model-partial least square (SEM-PLS). The book firstly introduces the basic knowledge of quantile regression, various kinds of modern SEM-PLS, and then R and Python techniques and examples in statistical computing. Chapter 2 carries out simulation studies in various SEM-PLS. More specially, the chapter briefly provides different simulation settings based on structural equation models and higher order latent variable models. Chapter 3 introduces the classical SEM-PLS estimation through a talent flow case in artificial intelligent. The study focuses on high-level talents in the field of artificial intelligence as the research object, and build a SEM-PLS model that can reflect the internal structural mechanism of the impact of talent mobility on scientific research performance.