关于序γαβ-理想统计收敛的模糊数列空间

以非降正数列a(n)、β(n)为框架,将模糊数列统计收敛和强收敛置于理想意义下,定义了两种新的模糊数列收敛的概念—关于序γαβ-理想统计收敛和关于序γ强αβ-理想收敛.同时,证明了这两种收敛的模糊数列空间的性质,以及这两种收敛之间的相互关系.给定模糊数列x={x_(k)},若它是强αβ-收敛的模糊数列,则x={x_(k)}一定是αβ-理想统计收敛的;当模糊数列x={x_(k)}有界时,反之成立.

LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.