We investigate the parameter estimation of regression models with fixed group effects, when variable is missing while group-related variables are available. This problem involves clustering to infer based on variables, and build a model target given eventually some additional variables. Thus, this can be formulated as joint distribution modeling The usual strategy for two-step approach starting...

Motivated by a recently proposed error estimator for the transfer function of reduced-order model given linear dynamical system, we further develop more theoretical results in this work. Furthermore, propose several variants estimator, and compare those with existing ones both theoretically numerically. It has been shown that some estimators perform better than or equally well as ones. All cons...

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propos...

Naturally ventilated tropical greenhouse is classified as a complex system because it involves with nonlinear process and multivariable system. The purpose of this study is to determine the mathematical model of NVTG climates to in order to describe and predict the dynamic behavior of temperature and humidity inside NVTG for development of its control system. The modeling of the system is divid...

Variational (deep) parametric auto-encoders (VAE) have shown a great potential for unsupervised extraction of latent representations from large amounts of data. Human face exhibits an inherent hierarchy in facial representations (encoded in facial action units (AUs) and their intensity). This makes VAE a sophisticated method for learning facial features for AU intensity estimation. Yet, most ex...

Reliability analysis is one of the significant applications of statistics. Many parametric and non-parametric techniques are available for reliability estimation based on precise life time observations, without considering the uncertainty of individual observations. But life time observations are not precise measurements but more or less fuzzy. Therefore by considering life time measurements as...

A nonparametric model-assisted survey estimator for status estimation based on local polynomial regression is extended to incorporate spatial auxiliary information. Under mild assumptions, this estimator is design-unbiased and consistent. Simulation studies show that the nonparametric regression estimator is competitive with standard parametric techniques when a parametric specification is corr...