Successive Sampling With $p (p \geqq 1)$ Auxiliary Variables

Exact Sampling Using Auxiliary Variables

P P 1 2

In the paper, we consider the problem of computing visibility information on digital terrain models. Visibility problems on polyhedral terrains are classi ed according to the kind of visibility information computed into point visibility, line visibility and region visibility. A survey of the state-of-the-art of the algorithms for computing visibility is presented, according to the classi cation...

φ: P n �� � (P 1) n+1

We develop in this paper some methods for studying the implicitization problem for a rational map φ : Pn 99K (P1)n+1 defining a hypersurface in (P1)n+1, based on computing the determinant of a graded strand of a Koszul complex. We show that the classical study of Macaulay Resultants and Koszul complexes coincides, in this case, with the approach of approximation complexes and we study and give ...

Auxiliary Variables in TLA+

Auxiliary variables are often needed for verifying that an implementation is correct with respect to a higher-level specification. They augment the formal description of the implementation without changing its semantics—that is, the set of behaviors that it describes. This paper explains rules for adding history, prophecy, and stuttering variables to TLA specifications, ensuring that the augmen...

Running head: SELECTION OF AUXILIARY VARIABLES 1 Selection of auxiliary variables in missing data problems: Not all auxiliary variables are created equal

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved, consists of including m...