必应词典为您提供Latent-class-model的释义,网络释义: 潜在类别模型;潜在组模型;潜在类别模式;
Latent Class Model
潜在剖面分析和潜在类别分析(Latent Class Analysis, LCA)均属于潜类别模型(Latent Class Model, LCM),即根据个体在观测指标上的反应模式,将其分到不同的类别中。二者的区别在于前者处理连续观测指标,后者处理分类观测指标。 Kunle:Mplus—潜在剖面分析(Latent Profile Analysis, LPA)(合集)141 赞同 · 44 评论文章...
之前介绍的LCGM只能描述一个变量的独立发展轨迹,为单变量LCGM(Univariate LCGM)。如果想要以多个变量为依据对样本进行分组并查看多个变量的发展轨迹,可以采用并行潜类别增长模型(Parallel-Process Latent Class Growth Model)。 即Univariate LCGM可以分析某个变量的独立发展轨迹,Parallel-Process LCGM可以分析多个变量的联...
相比之下,潜在类别混合模型在于假设人口是异质的,并且由 G 潜在类别的受试者组成,其特征是 G 平均轨迹曲线。 潜类别混合模型 潜在类别成员由离散随机变量 ci 定义,如果主题 i 属于潜在类别 g (g = 1, …,G),则该变量等于 g。变量 ci 是潜在的;根据协变量 Xci 使用多项逻辑模型描述其概率: ...
Model 1 can be described graphically in terms of a path diagram (or a graphical model) in which manifest variables are not connected to each other directly, but indirectly through the common source X. The latent variable is assumed to explain all of the ...
Based on this model, we propose a laten- t class model-i-vector-probabilistic linear discriminant analysis (LCM-Ivec-PLDA) system. Besides, as the divided segments are very short, their neighbors are taken into consideration. To overcome the initial sensitivity problem, we use an agglomera- ...
潜在类别模型(Latent Class Model, LCM; Lazarsfeld & Henry, 1968)或潜在类别分析(Latent Class Analysis, LCA)是通过间断的潜变量即潜 在类别(Class)变量来解释外显指标间的关联,使外显指标间的关联通过潜在类别变量来估计,进而维持其局部独立性的统计方法(见图11)。其基本假设是,外显变量各种反应的概率分布可以...
As an example, we used the LC cluster model to develop a segmentation of current bank customers based upon the types of accounts they have. Separate models were developed specifying different numbers of clusters and the model selected was the one that had the lowest BIC statistic. This criteria...
With a latent-class model, each individual belongs to a single latent class, which determines the person's set of response probabilities for the observed, or manifest, variables. A more general model, proposed herein, adds a single parameter and involves drawing, separately and independently for ...