Generalization of the linguistic aggregation operator and its application in decision making

A generalization of the linguistic aggregation functions (or operators) is presented by using generalized and quasiarithmetic means.Firstly,the linguistic weighted generalized mean (LWGM) and the linguistic generalized ordered weighted averaging (LGOWA) operator are introduced.These aggregation functions use linguistic information and generalized means in the weighted average (WA) and in the ordered weighted averaging (OWA) function.They are very useful for uncertain situations where the available information cannot be assessed with numerical values but it is possible to use linguistic assessments.These aggregation operators generalize a wide range of aggregation operators that use linguistic information such as the linguistic generalized mean (LGM),the linguistic OWA (LOWA) operator and the linguistic ordered weighted quadratic averaging (LOWQA) operator.We also introduce a further generalization by using quasi-arithmetic means instead of generalized means obtaining the quasi-LWA and the quasi-LOWA operator.Finally,we develop an application of the new approach where we analyze a decision making problem regarding the selection of strategies.     

Reweighting the general household survey 1979-2007

We have calculated two new sets of weights applicable to the General Household Survey (GHS) from 1979 to 2007. One of these is for use with any general analysis of GHS topics and the second is designed for analyses of data collected in the Family Information section. The methods used follow closely those employed by ONS from 1996 onwards. The performance of the weights is assessed in estimating the Total Fertility Rate (TFR) from 1971-2007, an aggregate measure of fertility for which reliable figures are available at national level from vital registration statistics. Our weights improve the GHS estimates, reducing bias both in the TFR and in age-specific fertility rates.