The inactivity time, or lost lifespan specifically for mortality data, concerns time from occurrence of an event interest to the current point and has recently emerged as a new summary measure cumulative information inherent in time-to-event data. This provides several benefits over traditional methods, including more straightforward interpretation yet less sensitivity heavy censoring. However,...

Time series of different nature might be characterised by the presence deterministic and/or stochastic seasonal patterns. By seasonality, we refer to periodic fluctuations affecting not only mean but also shape, dispersion and in general density variable interest over time. Using traditional approaches for adjustment efficient because they do ensure, instance, that adjusted data are free from b...

This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step procedure, where the regressors are computed in first step. The asymptotic properties of estimator, namely, consistency normality established. show that variance-covariance matrix needs to be adjusted account first-step error. propose general estimator var...

Bayesian quantile regression has drawn more attention in widespread applications recently. Yu and Moyeed (2001) proposed an asymmetric Laplace distribution to provide likelihood based mechanism for Bayesian inference of quantile regression models. In this work, the primary objective is to evaluate the performance of Bayesian quantile regression compared with simple regression and quantile regre...