Approximate mrpp p-values obtained from four exact moments

A F0RTRAN-77 subroutine for a general version of multi-response permutation procedures (MRPP) is described. The exact four moments are employed in conjunction with the Pearson type I, type III, and type VI distributions to calculate the associated P-values.     

Joint probability of statistical success of multiple phase III trials

In drug development, after completion of phase II proof‐of‐concept trials, the sponsor needs to make a go/no‐go decision to start expensive phase III trials. The probability of statistical success (PoSS) of the phase III trials based on data from earlier studies is an important factor in that decision‐making process. Instead of statistical power, the predictive power of a phase III trial, which takes into account the uncertainty in the estimation of treatment effect from earlier studies, has been proposed to evaluate the PoSS of a single trial. However, regulatory authorities generally require statistical significance in two (or more) trials for marketing licensure. We show that the predictive statistics of two future trials are statistically correlated through use of the common observed data from earlier studies. Thus, the joint predictive power should not be evaluated as a simplistic product of the predictive powers of the individual trials. We develop the relevant formulae for the appropriate evaluation of the joint predictive power and provide numerical examples. Our methodology is further extended to the more complex phase III development scenario comprising more than two (K > 2) trials, that is, the evaluation of the PoSS of at least k₀ () trials from a program of K total trials. Copyright © 2013 John Wiley & Sons, Ltd.     

A formula for Type III sums of squares

Abstract

Type III methods were introduced by SAS to address difficulties in dummy-variable models for effects of multiple factors and covariates. They are widely used in practice; they are the default method in several statistical computing packages. Type III sums of squares (SSs) are defined by a set of instructions; an explicit mathematical formulation does not seem to exist.

An explicit formulation is derived in this paper. It is used to illustrate Type III SSs and to establish their properties in the two-factor ANOVA model.     

Bayesian estimation under a mixture of the Burr type XII distribution and its reciprocal

The Bayesian estimation for the parameters of the finite mixture of the Burr type XII distribution with its reciprocal are obtained based on the type-I censored data. The Bayes estimators are computed based on squared error and Linex loss functions and using the idea of Markov chain Monte Carlo algorithm. Based on the Monte Carlo simulation, Bayes estimators are compared with their corresponding maximum-likelihood estimators.     

A study of simple unbalanced factorial designs that use type ii and type iii sums of squares

Methods for analysing unbalanced factorial designs can be traced back to the work of Frank Yates in the 1930s . Yet, still today the question on how his methods of fitting constants (Type II) and weighted squares of means (Type III) behave when negligible or insignificant interactions exist, is still unanswered. In this paper, by means of a simulation study, Type II and Type III ANOVA results are examined for all unbalanced structures originating from a 2x3 balanced factorial design within homogeneous groups (design types) accounting for structure, number of observations lost and which cells contained the missing observations. The two level factor is further analysed to test the null hypothesis, for both Type II and Type III analyses, that the unbalanced structures within each design type provide comparable F values. These results are summarised and the conclusion shows that this work agrees with statements made by Yates Burdick and Herr and Shaw and Mitchell-Olds, but there are some results which require further investigation.     

Quantile Uncertainty and Value‐at‐Risk Model Risk

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.     

Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems

The optimisation of decentralised energy systems has to integrate a series of factors, by implementing an approach based on interdisciplinary comprehension. There are technical, financial, environmental and social conditions that determine the selection and dimensioning of energy systems, particularly if these aim at covering the demand of remote regions by utilising renewable energy sources. Such a study requests the overall consideration of the local geological, morphological and climatic conditions, the capacities of the networks, and also the inclusion of the economic and social limitations, an approach that leads to a number of alternative solutions. The application of multi-criteria analysis can integrate the various aspects into a uniform evaluation procedure. This paper discusses the results of a study on determining the achievable penetration of renewable energy sources into an insular system for the purpose of electricity generation. The multi-criteria analysis method Electre III was implemented for this purpose. The research relies on data produced within the framework of the SEDEPIC project, financed by the ALTENER II/DG XVII programme.     

商业银行信用风险管理技术分析

针对目前中国银行业最薄弱的信用度风险管理问题,从信用风险管理的基本业务流程出发,对现有的西方商业银行的信用风险管理技术进行了系统的整理研究,并结合我国商业银行信用风险管理的技术现状和《新巴塞尔协议》中IRB法的基本要求,深入剖析了我国银行信用风险管理技术与国际监管标准之间存在的差距,并提出了相应的对策。     

跨国银行业并表监管原则探析

银行业的国际化发展使得对国际银行及其分支机构的国际监管更加重要。并表监管原则创新性地确立了母国和东道国的监管责任及其合作关系,成为跨国银行监管的一项核心基本原则,许多国家也在国内立法中实行该原则。并表监管作为监管原则是非常复杂的,许多问题仍有待探讨。我国新近颁布的《外资银行并表监管管理办法》适应了我国入世后金融业即将全面开放的需要,具有重要意义。