We propose a new selection procedures in unequal probability sampling that can be used with Horvitz and Thompson Estimator. Expression for inclusion probability for ith unit ( i  ) and joint inclusion probability of ith and jth unit ( ij  ) has been obtained. Some desirable properties of i  and ij  has been verified for proposed procedure.

Bayesian network (BN) A directed graph whose nodes represent variables, and edges represent influences. Together with conditional probability distributions, a Bayesian network represents the joint probability distribution of its variables. Conditional probability distribution Assignment of probabilities to all instances of a set of variables when the value of one or more variables is known. Con...

Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiples random variables. The problem of efficient representation of probability distributions is central in term of computational efficiency in the field of probabilistic reasoning. The main problem arises when dealing with joint probability distributions over a set of random vari...

fracture mapping of late permian-early triassic flat-lying sedimentary rocks in the sydney basin,new south wales, australia, shows that joints developed originally in extension were faulted in subsequentevents. joints with a regional distribution fall into two (early and late) formed groups. group i joints propagatedhorizontally and never interfered with each other. these joints were subsequent...

Bayesian networks (BNs) are an efficient way of representing joint probability distributions over sets of random variables; they are commonly employed in AI for reasoning under uncertainty.1 A BN is made up of two components: a directed acyclic graph (DAG), whose nodes represent random variables, and a set of conditional probability tables (CPTs), specifying the conditional probability distribu...

1.1 Definitions The individual strategy set Ai is finite with mi elements, {ai . . .a mi i }, indexed a ki i . A mixed strategy for player i, αi is a probability distribution over Ai, with αi(ai i ) as the probability of choosing a ki i . Thus ∑i ki=1 αi(a ki i ) = 1. The space of all mixed strategies for player i is denoted ∆Ai. Let a ∈ A = (a1 1 ,a k2 2 , . . .a kN N ) be a profile of pure st...