A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...

Abstract Background Time-to-event data that is subject to interval censoring common in the practice of medical research and versatile statistical methods for estimating associations such settings have been limited. For right censored data, non-parametric pseudo-observations proposed as a basis regression modeling with possibility use different association measures. In this article, we propose m...

In this paper, we discuss regression analysis of bivariate interval-censored failure time data that often occur in biomedical and epidemiological studies. To solve problem, propose a kind general flexible copula-based semiparametric partly linear additive hazards models can allow for both time-dependent covariates possible nonlinear effects. For inference, sieve maximum likelihood estimation ap...