Hintikka thinks that second-order logic is not pure logic,and because of Godel's incompleteness theorems,he suggests that we should liberate ourselves from the mistaken idea that first-order logic is the foundatio...Hintikka thinks that second-order logic is not pure logic,and because of Godel's incompleteness theorems,he suggests that we should liberate ourselves from the mistaken idea that first-order logic is the foundational logic of mathematics.With this background he introduces his independence friendly logic(IFL).In this paper,I argue that approaches taking Hintikka’s IFL as a foundational logic of mathematics face serious challenges.First,the quantifiers in Hintikka’s IFL are not distinguishable from Linstrom's general quantifiers,which means that the quantifiers in IFL involve higher order entities.Second,if we take Wright’s interpretation of quantifiers or if we take Hale’s criterion for the identity of concepts,Quine’s thesis that second-order logic is set theory will be rejected.Third,Hintikka's definition of truth itself cannot be expressed in the extension of language of IFL.Since second-order logic can do what IFL does,the significance of IFL for the foundations of mathematics is weakened.展开更多
Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In mos...Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In most cases mutual independence among the variables is assumed, however this fails to take into accounts the correlation between the outcomes of interests. A special bivariate form of the multivariate Lagrange family of distribution, names Generalized Bivariate Poisson Distribution, is considered in this paper. Objectives: We estimate the model parameters using the method of maximum likelihood and show that the model fits the count variables representing components of metabolic syndrome in spousal pairs. We use the likelihood local score to test the significance of the correlation between the counts. We also construct confidence interval on the ratio of the two correlated Poisson means. Methods: Based on a random sample of pairs of count data, we show that the score test of independence is locally most powerful. We also provide a formula for sample size estimation for given level of significance and given power. The confidence intervals on the ratio of correlated Poisson means are constructed using the delta method, the Fieller’s theorem, and the nonparametric bootstrap. We illustrate the methodologies on metabolic syndrome data collected from 4000 spousal pairs. Results: The bivariate Poisson model fitted the metabolic syndrome data quite satisfactorily. Moreover, the three methods of confidence interval estimation were almost identical, meaning that they have the same interval width.展开更多
基金Renmin University of China’s 2018 Fund for Building World-Class Universities(Disciplines).
文摘Hintikka thinks that second-order logic is not pure logic,and because of Godel's incompleteness theorems,he suggests that we should liberate ourselves from the mistaken idea that first-order logic is the foundational logic of mathematics.With this background he introduces his independence friendly logic(IFL).In this paper,I argue that approaches taking Hintikka’s IFL as a foundational logic of mathematics face serious challenges.First,the quantifiers in Hintikka’s IFL are not distinguishable from Linstrom's general quantifiers,which means that the quantifiers in IFL involve higher order entities.Second,if we take Wright’s interpretation of quantifiers or if we take Hale’s criterion for the identity of concepts,Quine’s thesis that second-order logic is set theory will be rejected.Third,Hintikka's definition of truth itself cannot be expressed in the extension of language of IFL.Since second-order logic can do what IFL does,the significance of IFL for the foundations of mathematics is weakened.
文摘Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In most cases mutual independence among the variables is assumed, however this fails to take into accounts the correlation between the outcomes of interests. A special bivariate form of the multivariate Lagrange family of distribution, names Generalized Bivariate Poisson Distribution, is considered in this paper. Objectives: We estimate the model parameters using the method of maximum likelihood and show that the model fits the count variables representing components of metabolic syndrome in spousal pairs. We use the likelihood local score to test the significance of the correlation between the counts. We also construct confidence interval on the ratio of the two correlated Poisson means. Methods: Based on a random sample of pairs of count data, we show that the score test of independence is locally most powerful. We also provide a formula for sample size estimation for given level of significance and given power. The confidence intervals on the ratio of correlated Poisson means are constructed using the delta method, the Fieller’s theorem, and the nonparametric bootstrap. We illustrate the methodologies on metabolic syndrome data collected from 4000 spousal pairs. Results: The bivariate Poisson model fitted the metabolic syndrome data quite satisfactorily. Moreover, the three methods of confidence interval estimation were almost identical, meaning that they have the same interval width.
