Semiparametric estimation of the memory parameter in economic time series raises the problem of the small sample size and the poor approximation of the asymptotic distribution to the finite sample counterpart. This paper considers the bootstrap to improve the finite sample distribution of the popular log peridogram regression and shows that it can significantly reduce the error in the coverage ...

aim : the aim of this study was to determine whether there is relation between body mass index and symptoms of gastro-esophageal reflux disease in our community using logit, probit and complementary log-log models. background : the most frequent statistical tool to address the relationship among a dichotomous response and other covariates is logistic regression. however logistic regression is f...

We introduce Bayesian additive regression trees (BART) for log-linear models including multinomial logistic and count with zero-inflation overdispersion. BART has been applied to nonparametric mean binary classification problems in a range of settings. However, existing applications have mostly limited Gaussian “data,” either observed or latent. This is primarily because efficient MCMC algorith...