On formulations of skew factor models: skew errors versus skew factors

10/11/2018
by   Sharon X. Lee, et al.
0

In the past few years, there have been a number of proposals for generalizing the factor analysis (FA) model and its mixture version (known as mixtures of factor analyzers (MFA)) using non-normal and asymmetric distributions. These models adopt various types of skew densities for either the factors or the errors. While the relationships between various choices of skew distributions have been discussed in the literature, the differences between placing the assumption of skewness on the factors or on the errors have not been closely studied. This paper examines these formulations and discusses the connections between these two types of formulations for skew factor models. In doing so, we introduce a further formulation that unifies these two formulations; that is, placing a skew distribution on both the factors and the errors.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/07/2018

Mixtures of Factor Analyzers with Fundamental Skew Symmetric Distributions

Mixtures of factor analyzers (MFA) provide a powerful tool for modelling...
research
01/28/2020

On the Dimensional Indeterminacy of One-Wave Factor Analysis Under Causal Effects

It is shown, with two sets of survey items that separately load on two d...
research
05/14/2020

On mean and/or variance mixtures of normal distributions

Parametric distributions are an important part of statistics. There is n...
research
03/29/2020

A formulation for continuous mixtures of multivariate normal distributions

Several formulations have long existed in the literature in the form of ...
research
08/01/2020

Review on Ranking and Selection: A New Perspective

In this paper, we briefly review the development of ranking-and-selectio...
research
04/11/2018

Sparse Bayesian Factor Analysis when the Number of Factors is Unknown

Despite the popularity of sparse factor models, little attention has bee...

Please sign up or login with your details

Forgot password? Click here to reset