The characteristic of correspondence analysis estimator to estimate latent variable model method using high-dimensional AIC
Bambang Avip Priatna M., Lukman Lukman, Encum Sumiaty · AIP conference proceedings · 2016
This paper aims to determine the properties of Correspondence Analysis (CA) estimator to estimate latent variable models.The method used is the High-Dimensional AIC (HAIC) method with simulation of Bernoulli distribution data.Stages are: (1) determine the matrix CA; (2) create a model of the CA estimator to estimate the latent variables by using HAIC; (3) simulated the Bernoulli distribution data with repetition 1,000,748 times.The simulation results show the CA estimator models work well.