Optimum stratification in bivariate auxiliary variables under Neyman allocation

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...

On Optimum Stratification

In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), w...

An Optimum Allocation with a Family of Estimators Using Auxiliary Information in Sample Survey

Neyman-Pearson classification under a strict constraint

Motivated by problems of anomaly detection, this paper implements the Neyman-Pearson paradigm to deal with asymmetric errors in binary classification with a convex loss. Given a finite collection of classifiers, we combine them and obtain a new classifier that satisfies simultaneously the two following properties with high probability: (i), its probability of type I error is below a pre-specifi...

Auxiliary Variables and Recursive Procedures

Much research in axiomatic semantics suuers from a lack of formality. In particular, most proposed veriication calculi for imperative programs dealing with recursive procedures are known to be unsound or incomplete. Focussing on total correctness, we present a new consequence rule which yields a sound and complete Hoare-style calculus in the presence of parameterless recursive procedures. Both,...