In this paper, we investigate the multiple attribute decision making problems with 2-tuple linguistic information. Motivated by the ideal of generalized weighted Bonferroni mean and generalized weighted geometric Bonferroni mean, we develop the 2-tuple linguistic generalized Bonferroni mean (2TLGBM) operator for aggregating the 2-tuple linguistic information and 2-tuple linguistic generalized g...

Percentiles are convenient indices to characterize the entire range of the values of simulation outputs. However, they have only seldom been used in simulation studies. One of the reason has been the lack of sequential estimation procedures, which are needed to obtain estimates of predeened accuracy. In this paper we introduce a sequential procedure for estimating several percentiles simultaneo...

The construction of simple classi1cation rules is a frequent problem in medical research. Maximally selected rank statistics allow the evaluation of cutpoints, which provide the classi1cation of observations into two groups by a continuous or ordinal predictor variable. The computation of the exact distribution of a maximally selected rank statistic is discussed and a new lower bound of the dis...

In the income (or consumption) poverty framework, a relevant open problem is connected with the distinction between poor and non-poor. This is usually done by considering a pre-specified income threshold called poverty line. If the income of an observation unit is lower (higher) than the poverty line, then such an observation unit is poor (non-poor or rich). Unfortunately, this procedure may of...

The Bonferroni mean is an important aggregation technique which can reflect the correlations of the aggregation arguments. The classical Bonferroni mean is an extension of the arithmetic mean, and is generalized by some researchers based on the idea of the geometric mean. In this paper, based on the Bonferroni mean and the harmonic mean, we introduce some new aggregating operators: the fuzzy Bo...

Bayes/frequentist correspondences between the p-value and the posterior probability of the null hypothesis have been studied in univariate hypothesis testing situations. This paper extends these comparisons to multiple testing and in particular to the Bonferroni multiple testing method, in which p-values are adjusted by multiplying by k, the number of tests considered. In the Bayesian setting, ...

In this paper, we establish a new analogue of the classical Bonferroni inequalities and their improvements by Galambos for sums of type ∑ π∈P(U)(−1)(|π| − 1)!f(π) where U is a finite set, P(U) is the partition lattice of U and f : P(U) → R is some suitable non-negative function. Applications of this new analogue are given to counting connected k-uniform hypergraphs, network reliability, and cum...