Copules archimédiennes et families de lois bidimensionnelles dont les marges sont données

Every bivariate distribution function with continuous marginals can be represented in terms of a unique copula, that is, in terms of a distribution function on the unit square with uniform marginals. This paper is concerned with a special class of copulas called Archimedean, which includes the uniform representation of many standard bivariate distributions. Conditions are given under which these copulas are stochastically ordered and pointwise limits of sequences of Archimedean copulas are examined. We also provide two new one-parameter families of bivariate distributions which include as limiting cases the Frechet bounds and the independence distribution.     

‘Minimum level of activity’—A quick method of assessing growth potential in the smaller business

The purpose of this article is to provide a method for making a quick assessment of the growth potential of small and medium-sized companies. It provides in particular a calculation of the maximum level of activity to cover costs and achieve a given rate of profitability. This method makes use of graphic material and of simple relations, and does not involve complex calculations. It enables the user to make a simplified forecast of his accounts.     

OR/MS methodology—A conceptual framework

Many authors deal, explicitly or implicitly, with OR/MS methodology and the term ‘methodology’ has gained such an inclusive connotation that it comes to denote nothing in particular. This has diluted the analytical precision of OR/MS ‘methodology’ as well as its practicability. Therefore an attempt to form a conceptual framework for OR/MS methodology will be presented. This framework consists of seven components addressing specific methodological aspects: each component has specific properties which distinguish it from the others; all of them together form a consistent hierarchy suitable to aid the successful development and implementation of OR/MS methods.     

Mitochondrial Dynamics in Cell Life and Death

Mitochondria are dynamic organelles that are able to change their morphology during cellular development and to meet the energetic needs of the cell, for example. During the past several years, knowledge about the molecular machinery involved in the control of mitochondrial shape has improved considerably. In August 2005, leading researchers in the field of mitochondrial dynamics met at the Venetian Institute of Molecular Medicine in Padova, Italy, to discuss novel and intriguing findings presented at the first workshop on "Mitochondrial Dynamics in Cell Life and Death." Some of the findings related to apoptosis and aging are described in this Perspective.     

Pooling operators with the marginalization property

In this paper, we consider the problem of combining a number of opinions which have been expressed as probability measures P₁, …, P_n, over some space. It is shown that a pooling formula which has the marginalization property of McConway (1981) must be of the form T = Σⁿ_i=₁W_i P_i + (1 - Σⁿ_i =₁W_i)Q, where Q is an arbitrary measure and W₁, …, W_n ϵ [—1,1] are weights such that| Σ_J Σ _j w_j | ≤ 1 for every subset J of {1, …, n}. If, in addition, T is required to preserve the independence of arbitrary events A and B whenever these events are independent under each P_i, then either T = P_i for some 1 ≤ i ≤ n or T = Q, in which case Q takes values in {0, l}.     

The two-sample t test versus satterthwaite's approximate f test

A comparison between the two-sample t test and Satterthwaite's approximate F test is made, assuming the choice between these two tests is based on a preliminary test on the variances. Exact formulas for the sizes and powers of the tests are derived. Sizes and powers are then calculated and compared for several situations.     

The Volatility of Realized Volatility

In recent years, with the availability of high-frequency financial market data modeling realized volatility has become a new and innovative research direction. The construction of “observable” or realized volatility series from intra-day transaction data and the use of standard time-series techniques has lead to promising strategies for modeling and predicting (daily) volatility. In this article, we show that the residuals of commonly used time-series models for realized volatility and logarithmic realized variance exhibit non-Gaussianity and volatility clustering. We propose extensions to explicitly account for these properties and assess their relevance for modeling and forecasting realized volatility. In an empirical application for S&P 500 index futures we show that allowing for time-varying volatility of realized volatility and logarithmic realized variance substantially improves the fit as well as predictive performance. Furthermore, the distributional assumption for residuals plays a crucial role in density forecasting.     

Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support

In sequential pattern analysis, the frequency of patterns is evaluated by the support. While computed efficiently from large databases, we show that the support cannot be compared between different databases, since it is influenced by the actual sequence length distribution. Models for this sequence length distribution are surveyed. One of these models, the Good distribution, appears to be sufficiently flexible for practice. It is used to exemplify an approach for adjusting the relative support such that the resulting adjusted support values are better comparable between different databases. We illustrate our findings with texts from the bilingual FinDe corpus.