multi-path is favorite alternative for sensor networks, as it provides an easy mechanism to distributetraffic, as well as considerate fault tolerance. in this paper, a new clustering based multi path routingprotocol namely ecrr (energy efficient cluster based routing algorithm for improving reliability) isproposed, which is a new routing algorithm and guarantees the achievement to required qos ...

We develop a novel approach to consistent checks of parametric regression models when many regressors are present. The principle is to replace the nonparametric alternative by a class of semiparametric alternatives, namely single-index models, that is rich enough to allow detection of any nonparametric alternative. We propose an omnibus test based on the kernel method that performs against a se...

We develop a novel dimension-reduction approach to consistent checks of parametric regression models when many regressors are present. The principle is to replace the nonparametric alternative by a class of semiparametric alternatives, namely single-index models, that is rich enough to allow detection of any nonparametric alternative. We propose an omnibus test based on the kernel method that p...

The field of productive efficiency analysis is currently divided between two main paradigms: the deterministic, nonparametric Data Envelopment Analysis (DEA) and the parametric Stochastic Frontier Analysis (SFA). This paper examines an encompassing semiparametric frontier model that combines the DEA-type nonparametric frontier, which satisfies monotonicity and concavity, with the SFA-style stoc...

In the classical data envelopment analysis (DEA) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. In recent years, there are few researches on handling missing data. This paper suggests a new interval based approach to apply missing data, which is the modified version of Kousmanen (2009) approach. First, the prop...

in the classical data envelopment analysis (dea) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. in recent years, there are few researches on handling missing data. this paper suggests a new interval based approach to apply missing data, which is the modified version of kousmanen (2009) approach. first, the prop...