Grey target decision making is one of the important problems of decision-making theory. It is critical to express uncertain information effectively and depose them in a reasonable…
Abstract
Purpose
Grey target decision making is one of the important problems of decision-making theory. It is critical to express uncertain information effectively and depose them in a reasonable and simple way. The purpose of this paper is to solve the grey target problem by the grey potential degree method without whiten value and without distribution function. Furthermore, this new approach has an advantage of realizing both comparing and standardization work during the process of treating the data.
Design/methodology/approach
First, this paper makes a brief overview of the existing method for grey target decision. Then, the conception of a grey potential degree system is introduced and the conception of standard grey potential degree is build up, and a new grey potential-based method based on the grey target multiple attribute decision method is proposed. At the same time, the standard grey potential and its application in multiple resource data are studied.
Findings
At the same time the standard grey potential and its application in multiple resource data are studied. Standard grey potential is presented by means of three examples together with the comparison with the existing method to demonstrate that the grey potential-based method could be used to solve the problem of grey target decision conveniently and effectively.
Originality/value
It is very important to compare grey numbers to obtain scientific and reasonable results for a grey target decision-making problem. However, in the actual application of grey numbers, it is difficult to find out the probability density function or the whiten function of grey numbers. When grey numbers are compared and deposed through the whiten value, much information regarding grey numbers will be lost and, at the same time, the value of grey numbers in uncertainty is partly lost. The method discussed in this paper is reasonable and feasible.
Details
Keywords
Yinao Wang, Aiqing Ruan and Zhihui Zhan
This paper aims to study the improved effect of the instrumental variable method to estimate parameters of linear regression model with the stochastic explanatory variables…
Abstract
Purpose
This paper aims to study the improved effect of the instrumental variable method to estimate parameters of linear regression model with the stochastic explanatory variables problem.
Design/methodology/approach
By Monte‐Carlo method, taking a linear regression model with intercept of 3, slope of 4 as an example, whose random error in standard normal distribution, to test whether parameter estimators are biased and how about the average relative error of estimator of slope when random explanatory variables are in different contemporaneously correlated with random error item. By the instrumental variables which are independent with random error item and in varying degrees related to random explanatory variable, the study tests the estimation accuracy of the slope using the instrumental variable method.
Findings
This paper tests that the ordinary least square parameter estimators are biased, and especially that the average relative error of estimator of slope is significantly large, more than 10 percent, when random explanatory variables are different and contemporaneously correlated with the random error item. For the instrumental variables that are independent from random error item and in varying degrees related to the random explanatory variable, the estimation accuracy of the slope is significantly improved and the relative error dropped to less than 4 percent, but the estimation accuracy of the intercept term showed no significant improvement by the instrumental variable method.
Practical implications
The method exposed in the paper shows how to improve estimation by an instrumental variable method.
Originality/value
The paper succeeds in showing how to improve estimation by the instrumental variable method of numerical simulation.
Details
Keywords
Zhi‐geng Fang, Si‐feng Liu, Aiqing Ruan and Xuewei Zhang
A study is made of the payoff matrix which is made up of grey interval number because of asymmetry information, player's finite knowledge and bounded rationality and all sorts of…
Abstract
Purpose
A study is made of the payoff matrix which is made up of grey interval number because of asymmetry information, player's finite knowledge and bounded rationality and all sorts of stochastic and non‐stochastic factors.
Design/methodology/approach
On the base of concept of equipollent, superior and inferior potential degree, the paper designs determinant rules of interval grey number potential relations, opens out player's decision‐making laws in the conditions of finite knowledge and logos. And it designs the grey game decision‐making rules which player choices maximum potential degree of grey game value (the most favorableness situation) under the cases of that there are all likely to be minimum potential degree of grey game value (the most disadvantage situation), which is a reliable way for both sides to accept.
Findings
The paper recognizes and defines overrated and underrated risk of potential optimal pure strategy in the grey game, designs arithmetic for determining player's overrated and underrated risk under the situation of potential optimal pure strategy.
Practical implications
The presents system meets the requirement of judging pure strategy solutions in the grey potential situation.
Originality/value
This paper builds up the system of judgment for grey potential.