潜在クラス・混合モデル
8 の手法がこの系統にあります。
注目
潜在クラス分析 (LCA)Latent class analysis identifies unobserved subgroups — latent classes — within a population by finding patterns of responses across a set of categorical observed indicators. It is潜在プロフィール分析 (LPA)Latent Profile Analysis (LPA) is a person-centered finite mixture modeling technique that identifies unobserved subgroups — called profiles — within a population based on patterns 潜在移行分析Latent Transition Analysis (LTA) is a method for studying transitions between latent classes over time, developed by Collins and Lanza (2010). LTA combines latent class analysis (g潜在クラス分析（LCA）Latent class analysis is a probabilistic model-based clustering technique that identifies unobserved subgroups — latent classes — within a population on the basis of patterns of ca混合モデル (Mixture Modeling)Mixture modeling assumes that a population is composed of K unobserved subpopulations, each described by its own probability distribution. The observed data are treated as draws frロバスト潜在クラス分析Robust latent class analysis (robust LCA) extends the standard latent class model by incorporating outlier-resistant estimation techniques — such as trimmed likelihood, M-estimatio
学びの道筋
このトピックで最も多く参照される基礎的な手法を、発展してきた順に並べました — はじめての方はここから読み始めてください。