It is becoming more typical in regression problems today to have the situation where “pn”, that is, where the number of covariates is greater than the number of observations. Approaches to this problem include such strategies as model selection and dimension reduction, and, of course, a...

Finite population estimation is the overall goal of sample surveys. When information regarding auxiliary variables are available, one may take advantage of general regression estimators (GREG) to improve sample estimates precision. GREG estimators may be derived when the relationship between...

We discuss the scientific contribution of Battaglia and Protopapas’ paper concerning the debate on global warming supported by an extensive analysis of temperature time series in the Alpine region. In the work, Authors use several exploratory and modelling tools for assessing and...

We investigate a family of conditional independence models defined by constraints on complete but non hierarchical marginal log–linear parameters. By exploiting results on the mixed parameterization, we show that these models are smooth when a certain Jacobian matrix has spectral radius...

We encounter missing data in many longitudinal studies. When the missing data are nonignorable, it is important to analyze the data by incorporating the missing data mechanism into the observed data likelihood function. The classical maximum likelihood (ML) method for analyzing longitudinal...