The direct sampling method proposed by Walker et al. (JCGS 2011) can generate draws from weighted distributions possibly having intractable normalizing constants. may be of interest as a tool in situations which require drawing an unfamiliar distribution. However, the original algorithm have difficulty producing some situations. present work restricts attention to univariate setting where weigh...

This paper unifies the work on multiple reinsurers, distortion risk measures, premium budgets, and heterogeneous beliefs. An insurer minimizes a measure, while seeking reinsurance with finitely many reinsurers. The reinsurers use principles, they are allowed to have beliefs regarding underlying probability distribution. We provide characterization of optimal indemnities, we show that layer-insu...

There are chances like a data distributor had given his sensitive data to a set of trusted agents. These agents can be called as third parties. There are chances that some of the data is leaked and found in an unauthorized place. This situation is called IDS. In existing case, the method called watermarking is using to identify the leakage. Or also uses the technique like injecting fake data th...

this paper examines the effect of systematic risk on accounting conservatism. the idea is that in firms with higher systematic risk, managers have higher incentives to delay the recognition of bad news in the hope of future good news. they also face less demand for conservatism from investors and auditors. in this paper, for measuring systematic risk and accounting conservatism, we used beta fr...

Many situations of physical and biological interest involve diffusions on manifolds. It is usually assumed that irregularities in the geometry of these manifolds do not influence diffusions. The validity of this assumption is put to the test by studying Brownian motions on nearly flat 2D surfaces. It is found by perturbative calculations that irregularities in the geometry have a cumulative and...

The DUCK-calculus presented here is a re­ cent approach to cope with probabilistic un­ certainty in a sound and efficient way. Un­ certain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally. The basic in­ ference mechanism relies on local bounds propagation, implementable by deductive databases with a bottom-up fixpoint evalu­ ation. In si...

We present a new approach for finding conditional plans with loops and branches for planning in situations with uncertainty in state properties as well as in object quantities. We use a state abstraction technique from static analysis of programs to builds such plans incrementally using generalizations of input example plans generated by classical planners. Preconditions of the resulting plans ...

The effects of information on market design are explored in a simple setting where firms have private information about their correlated fixed costs and the government aims to maximize its expected revenue conditional on achieving efficient allocations. Government revenues are higher when the costs are less correlated (or are more of a private value). The reduced correlation increases the firms...

Although regression trees were originally designed for large datasets, they can profitably be used on small datasets as well, including those from replicated or unreplicated complete factorial experiments. We show that in the latter situations, regression tree models can provide simpler and more intuitive interpretations of interaction effects as differences between conditional main effects. We...