A statistic to check model adequacy in time series

A simple statistic is suggested to examine if the assumptions on variances in a fitted time series model is valid or not. The properties of the statistic are discussed and examples are considered.     

Bayesian regression under combinations of constraints

A Bayesian method for regression under several types of constraints is proposed. The constraints can be range-restricted and include shape restrictions, constraints on the value of the regression function, smoothness conditions and combinations of these types of constraints. The support of the prior distribution is included in the set of piecewise linear functions. It is shown that the proposed prior can be arbitrarily close to the distribution induced by the addition of a polynomial plus an (m−1)-fold integrated Brownian motion. Hence, despite its piecewise linearity, the regression function behaves (approximately) like an m−1 times continuously differentiable random function. Furthermore, thanks to the piecewise linear property, many combinations of constraints can easily be considered. The regression function is estimated by the posterior mode computed by a simulated annealing algorithm. The constraints on the shape and the values of the regression function are taken into account thanks to the proposal distribution, while the smoothness condition is handled by the acceptation step. Simulations from the posterior distribution are obtained by a Gibbs sampling algorithm.     

现代中国多民族国家策略——“民族”识别的历史动因探源

以云南地区的多元和多样性表现为例探讨现代中国多民族国家的策略和历史境遇。通过梳理中国历史上民族国家策略的历史进程,发现中国近现代历史中国民党和共产党在民族国家策略上的差异,以及现代中国“民族”识别的出现,是中国深远的历史情境中的一个必然结果,亦是中国共产党建立现代国家与各民族达成共识的基本路径。     

Middle Managers Moulding International Strategy: An Irish Start-up in Jamaican Telecoms

This is a story of how a group of middle managers moved beyond just implementing their firm’s tightly prescribed strategy for developing an international venture to the point where it could be argued that they failed to accomplish the four clear strategic objectives set by the firm’s executive management. Instead, the authors suggest, their success was in collectively orchestrating an emergent strategy¹ which provided the executive with a better, more profitable and durable embodiment of their strategic vision.Operating between the parent firm’s original strategic intent and the political and economic realities of the host country environment, their strategic influence is worthy of close examination. They can be divided into two distinctive groups—parent country nationals and host-country nationals—and the extent to which they co-operate with or obstruct each other will have a significant effect on the success of the enterprise.² The middle management in this case example, an Irish company launching a mobile telecommunications network in Jamaica, is drawn from both groups. This article investigates the apparent autonomy from executive control afforded these particular middle managers to identify the contingent factors that appear to allow, or constrain, their positive transmutation of the original strategic objectives. The key questions addressed are first, how the two groups, both individually and collectively, played out their roles in shifting strategy, and second, once these contextual dynamics have been identified, how other executive management groups can learn from this Irish/Jamaican experience considering similar international ventures. The authors’ response highlights those elements of strategy design, organisational structure and human resource management that they believe are critical in maximising the strategic contribution of middle managers to international ventures, and hence providing a better chance of success.     

Specialised Perception, Selection, and Strategic Surprise: Learning from the Moths and Bees

This paper draws on comparisons between organisations and organisms to illustrate how peripheral vision can influence behaviour. Like biological organisms, organisations have sensors to inform them of threats and opportunities. The process by which these sensors are developed is ‘selection, adaptation and learning’, or SAL. While SAL’s influence is helpful, it is not always on the side of the organisation. However there are systems that can help an organisation detect oncoming challenges. These include: leveraging the peripheral vision of the CEO; improving general purpose sensors; a better reading of specialised sensors; and installing new specialised or routine sensors in areas where none presently exists.     

Use of Biological Markers in Risk Assessment1

Measurements of intermediate end points in the carcinogenic process may reduce uncertainty in human risk assessment from bioassay data, by identifying sources of interspecies variation and dose nonlinearity. This paper describes desirable properties of such markers: persistence, predictive power, temporal relevance, and consistency across dose rate and species. We illustrate these properties by evaluating markers for squamous cell nasal carcinoma in rodents exposed to formaldehyde. We also discuss design issues for bioassays that evaluate markers and tumors simultaneously at necropsy.     

Analysing intangible resources and managing knowledge in a supply chain context

This paper reports the initial empirical work (and related findings) which has been carried out in a UK Government funded project titled `The Development of Partnership Strategies and the Management of Knowledge which Underpins Capabilities'. The companies collaborating in the research were Cellnet plc, Flymo Ltd and four of their strategic suppliers. This paper describes the validation of a technique for analysing the role of intangible resources in the development of partnership strategies. The technique codifies the tacit knowledge which a company's managers have of their company's strengths thereby enabling this understanding to be communicated to partners and used as a basis for joint strategic development. The paper goes on to outline a technique which is currently being tested for managing the knowledge associated with inter-organisational innovation.     

Exact Goodness‐of‐Fit Testing for the Ising Model

The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness of fit. Here, we propose various test statistics and an exact goodness‐of‐fit test for the finite‐lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness‐of‐fit testing using a Monte Carlo approach. However, finding a Markov basis is often computationally intractable. Thus, we develop a Monte Carlo method for exact goodness‐of‐fit testing for the Ising model that avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane.