This paper provides several error estimations for total variation (TV) type regularization, which arises in a series of areas, instance, signal and imaging processing, machine learning, etc. In this paper, some basic properties the minimizer TV regularization problem such as stability, consistency convergence rate are fully investigated. Both priori posteriori rules considered paper. Furthermor...

Codeword-stabilized codes are a general class of quantum codes that includes stabilizer codes and many families of nonadditive codes with good parameters. For such a nonadditive code correcting all t-qubit errors, we propose an algorithm that employs a single measurement to test all errors located on a given set of t qubits. Compared with exhaustive error screening, this reduces the total numbe...

The primary objective of this article is to explore the feasibility of the application of cost minimization analysis in a teaching hospital environment. The investigation is concerned with the development of cost per admission and cost per patient day models. These models are further used for determining the value of the length of stay that would minimize cost per patient day (projected length ...

We develop a new formulation of Stein’s method to obtain computable upper bounds on the total variation distance between the geometric distribution and a distribution of interest. Our framework reduces the problem to the construction of a coupling between the original distribution and the “discrete equilibrium” distribution from renewal theory. We illustrate the approach in four nontrivial exam...

The total survey error (TSE) paradigm provides a theoretical framework for optimizing surveys by maximizing data quality within budgetary constraints. In this article, the TSE paradigm is viewed as part of a much larger design strategy that seeks to optimize surveys by maximizing total survey quality; i.e., quality more broadly defined to include user-specified dimensions of quality. Survey met...

Survey error is known to be pervasive and bias even simple, but important, estimates of means, rates, totals, such as the poverty unemployment rate. In order summarize analyze extent, sources, consequences survey error, we define empirical counterparts key components Total Error Framework that can estimated using data combination. Specifically, estimate total decompose it into three high level ...