In this study, the aim is to propose a new method for fuzzification of nested dummy variables. The fuzzification idea of dummy variables has been acquired from non-linear part of regime switching models in econometrics. In these models, the concept of transfer functions is like the notion of fuzzy membership functions, but no principle or linguistic sentence have been used for inputs. Consequen...

The aim of this study is to examine the equity premium puzzle in Iran for the quarterly period of 1993-2016. In this regard, the hybrid bivariate Garch model and also fuzzy dummy variables with consumption capital asset pricing model (C-CAPM) have been used. The results of study show that using C-CAPM within fuzzy dummy variables (CCAPM-F), the relative risk aversion coefficient of investor is ...

The possibility to handle dummy variables and to manipulate dummy summations are important features in many applications. In particular, in theoretical physics, the possibility to represent complicated expressions concisely and to realize simplifications efficiently depend on both capabilities. However, when dummy variables are used, there are many more ways to express a given mathematical obje...

Dummy variables frequently are used in regression analysis but often in an incorrect fashion. A brief review of examples in the medical care literature showed that the interpretation of dummy variable regression coefficients and their significance was often incorrect or unclear. This article shows how dummy variables can be used and assessed properly. The importance of testing for the joint eff...

in structural time seriesregression models, binary (classic) dummy variables are used to quantify the effects of economic structural breaks, changes or qualitative variables. the binary dummy variable can be challenged using this dummy variable in which 0 or 1 represent absence or presence of structural breaks(or changes), but presence of the structural breaks(or changes) may not have uniform e...

A method is given for obtaining equivalence subgroups of a family of differential equations from the equivalence group of simpler equations of a similar form, but in which the arbitrary functions specifying the family element depend on fewer variables. Examples of applications to classical equations are presented, some of which show how the method can actually be used for a much easier determin...

Dummy variables are variables that take the values of only 0 or 1. They may be explanatory or outcome variables; however, the focus of this article is explanatory or independent variable construction and usage. Typically, dummy variables are used in the following applications: time series analysis with seasonality or regime switching; analysis of qualitative data, such as survey responses; cate...