@book{6498fc1f9a5d42f7898254305c3976f4,

title = "Subset selection with a generalized selection goal based on a loss function",

abstract = "Assume k (integer k = 2) populations are given. The associated independent random variables have continuous distribution functions with an unknown location parameter. The selection goal is to select a non-empty subset which contains the best, in the sense of largest location parameter, population with confidence level P* (k^{-1} <P* <1). In the present paper a generalized selection goal based on a general loss function is presented. This new loss function takes into account the difference, in parameter value, between the best population in the selected subset and the best of all k populations minus e (e \geq 0); it is zero if an e-best population is an element of the subset. An e-best population is any population with a parameter value within e of the value of the largest parameter. The generalized selection goal is thought to be of great value from an application point of view. The subset selection goal of Gupta is a special case of the introduced generalized selection goal. The special case of two normal populations is studied in detail.",

author = "{Laan, van der}, P. and {Eeden, van}, C.",

year = "1993",

language = "English",

series = "Memorandum COSOR",

publisher = "Technische Universiteit Eindhoven",

}