We propose a multivariate probability distribution that models a linear correlation between binary and continuous variables. The proposed distribution is a natural extension of the previously developed multivariate binary distribution. As an application of the proposed distribution, we develop a factor analysis for a mixture of continuous and binary variables. We also discuss improper solutions associated with factor analysis. As a prescription to avoid improper solutions, we propose a constraint that each row vector of factor loading matrix has the same norm. We numerically validated the proposed factor analysis and norm constraint prescription by analyzing real datasets.
翻译:我们建议多变量概率分布, 以模拟二进制变量和连续变量之间的线性关联。 拟议的分布是先前开发的多变量二进制分布的自然延伸。 作为拟议分布的一种应用, 我们为连续变量和二进制变量的混合开发一个要素分析。 我们还讨论与要素分析相关的不适当解决方案。 作为避免不正确解决方案的处方, 我们提出一个限制, 即每个行要素载荷矩阵的矢量都有相同的规范。 我们通过分析真实数据集, 以数字方式验证了拟议要素分析和规范约束处方 。