The linear and nonlinear seemingly unrelated regression problem with general error distribution is analyzed using recent likelihood theory that arguably provides the definitive distribution for assessing a scalar parameter; this involves implicit but well defined conditioning and marginalization for determining intrinsic measures of departure. Highly accurate p-values are obtained for the key d...

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameterand height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated re...

Environmental benefits have become priority objectives for the management of forests, including private forest owners in many countries. Understanding and promoting environmental-friendly requires a measure environmental concern knowledge factors that influence it. Such allows to explore underlying motivations include aspects their management. This turn helps developing implementing effective p...

<p style='text-indent:20px;'>This paper considers simultaneous optimal prediction and estimation problems in the context of linear random-effects models. Assume a pair seemingly unrelated models (SULREMs) with error terms correlated. Our aim is to find analytical formulas for calculating best unbiased predictors (BLUPs) all unknown parameters two by means solving constrained quadratic mat...

Motivated by an important biomarker study in nutritional epidemiology, we consider the combination of the linear mixed measurement error model and the linear seemingly unrelated regression model, hence Seemingly Unrelated Measurement Error Models. In our context, we have data on protein intake and energy (caloric) intake from both a food frequency questionnaire (FFQ) and a biomarker, and wish t...

Suppose you have to route agents through a network from a source node to a destination node in some optimal way; for instance by minimizing the total travel cost. Nothing new up to now – you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some exploration of the network, to avoid congesti...

This is an introduction of the initial publication of the new Special Section of the MCFNS journal on micro-detail detection and tracking problems and various related interdisciplinary studies in other disciplines, which are deemed to be synergistic or relevant to detection and tracking problems. The initial selection of publications presented here arose from the Smolensk Conference held on Oct...

Seemingly unrelated regression (SUR) models are useful in studying the interactions among different variables. In a high dimensional setting or when applied to large panel of time series, these models require a large number of parameters to be estimated and suffer of inferential problems. To avoid overparametrization and overfitting issues, we propose a hierarchical Dirichlet process prior for ...