Bayesian parameter estimation for latent Markov random fields and social networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

The economic theory of international supply chains: a systems view

This paper offers an integrated analysis of out-sourcing, off-shoring and foreign direct investment within a systems view of international business. This view takes the supply chain rather than the firm as the basic unit of analysis. It argues that competition in the global economy selects supply chains that maximise the joint profit of all the firms in the chain. The systems view is compared with the firm-centred view commonly used in strategy literature. The paper shows that a firm’s strategy must be embedded within an efficient supply chain strategy, and that this strategy must be negotiated with, rather than imposed upon, other firms. The paper analyses the conditions under which various supply chain strategies - and by implication various firm-level strategies - are efficient. Only by adopting a systems view of supply chains is it possible to determine which firm-level strategies will succeed in a volatile global economy.

Economic analysis of international supply chains: an internalization perspective

Offshoring and outsourcing in global value chains have been extensively analyzed from a strategic management perspective (Gereffi & Li, 2012; Gereffi, Humphrey & Sturgeon, 2005; Mudambi & Venzin, 2010). This paper examines these issues from an internalization theory perspective by summarizing the contribution of internalization theory to supply chain analysis; considering how a division of labor is coordinated and comparing coordination by management with coordination by the market; and discussing the formal models of supply chains developed by economists. Supply chain researchers possessing an interest in economic principles and good mathematical skills can make an important contribution to internalization theory, and it is hoped that this paper will encourage them to do so.

Business cycle asymmetries: characterisation and testing based on Markov-switching autoregressions

Tests for business cycle asymmetries are developed for Markov-switching autoregressive models. The tests of deepness, steepness, and sharpness are Wald statistics, which have standard asymptotics. For the standard two-regime model of expansions and contractions, deepness is shown to imply sharpness (and vice versa), whereas the process is always nonsteep. Two and three-state models of U.S. GNP growth are used to illustrate the approach, along with models of U.S. investment and consumption growth. The robustness of the tests to model misspecification, and the effects of regime-dependent heteroscedasticity, are investigated.

Threshold autoregressive and Markov switching models: an application to commercial real estate

Although financial theory rests heavily upon the assumption that asset returns are normally distributed, value indices of commercial real estate display significant departures from normality. In this paper, we apply and compare the properties of two recently proposed regime switching models for value indices of commercial real estate in the US and the UK, both of which relax the assumption that observations are drawn from a single distribution with constant mean and variance. Statistical tests of the models' specification indicate that the Markov switching model is better able to capture the non-stationary features of the data than the threshold autoregressive model, although both represent superior descriptions of the data than the models that allow for only one state. Our results have several implications for theoretical models and empirical research in finance.

Hidden Markov analysis describes dive patterns in semiaquatic animals

Existing methods of dive analysis, developed for fully aquatic animals, tend to focus on frequency of behaviors rather than transitions between them. They, therefore, do not account for the variability of behavior of semiaquatic animals, and the switching between terrestrial and aquatic environments. This is the first study to use hidden Markov models (HMM) to divide dives of a semiaquatic animal into clusters and thus identify the environmental predictors of transition between behavioral modes. We used 18 existing data sets of the dives of 14 American mink (Neovison vison) fitted with time-depth recorders in lowland England. Using HMM, we identified 3 behavioral states (1, temporal cluster of dives; 2, more loosely aggregated diving within aquatic activity; and 3, terminal dive of a cluster or a single, isolated dive). Based on the higher than expected proportion of dives in State 1, we conclude that mink tend to dive in clusters. We found no relationship between temperature and the proportion of dives in each state or between temperature and the rate of transition between states, meaning that in our study area, mink are apparently not adopting different diving strategies at different temperatures. Transition analysis between states has shown that there is no correlation between ambient temperature and the likelihood of mink switching from one state to another, that is, changing foraging modes. The variables provided good discrimination and grouped into consistent states well, indicating promise for further application of HMM and other state transition analyses in studies of semiaquatic animals.

Heaps and Chains: Is the Chaining Argument for parity a sorites?

I argue that the Ruth Chang’s Chaining Argument for her parity view of value incomparability trades illicitly on the vagueness of the predicate ‘is comparable with’. Chang is alert to this danger and argues that the predicate is not vague, but this defense does not succeed. The Chaining Argument also faces a dilemma. The predicate is either vague or precise. If it is vague, then the argument is most plausibly a sorites. If it is precise, then the argument is either question begging or dialectically ineffective. I argue that no chaining-type argument can succeed.

Decomposition of surface electromyographic signal using Hidden Markov Model

The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

The uniqueness of signature problem in the non-Markov setting

We establish a general framework for a class of multidimensional stochastic processes over [0,1] under which with probability one, the signature (the collection of iterated path integrals in the sense of rough paths) is well-defined and determines the sample paths of the process up to reparametrization. In particular, by using the Malliavin calculus we show that our method applies to a class of Gaussian processes including fractional Brownian motion with Hurst parameter H>1/4, the Ornstein–Uhlenbeck process and the Brownian bridge.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Towards conceptualizing reverse service supply chains

Purpose – Recognizing the heterogeneity of services, this paper aims to clarify the characteristics of forward and the corresponding reverse supply chains of different services. Design/methodology/approach – The paper develops a two-dimensional typology matrix, representing four main clusters of services according to the degree of input standardization and the degree of output tangibility. Based on this matrix, this paper develops a typology and parsimonious conceptual models illustrating the characteristics of forward and the corresponding reverse supply chains of each cluster of services. Findings – The four main clusters of service supply chains have different characteristics. This provides the basis for the identification, presentation and explanation of the different characteristics of their corresponding reverse service supply chains. Research limitations/implications – The findings of this research can help future researchers to analyse, map and model forward and reverse service supply chains, and to identify potential research gaps in the area. Practical/implications – The findings of the research can help managers of service firms to gain better visibility of their forward and reverse supply chains, and refine their business models to help extend their reverse/closed-loop activities. Furthermore, the findings can help managers to better optimize their service operations to reduce service gaps and potentially secure new value-adding opportunities. Originality/value – This paper is the first, to the authors ' knowledge, to conceptualize the basic structure of the forward and reverse service supply chains while dealing with the high level of heterogeneity of services.

Mass spectrometric investigation of the DNA-binding properties of an anthracycline with two trisaccharide chains

Cosmomycin D (CosD) is an anthracycline that has two trisaccharide chains linked to its ring system. Gel electrophoresis showed that CosD formed stable complexes with plasmid DNA under conditions where daunorubicin (Dn) and doxorubicin (Dx) dissociated to some extent during the experiments. The footprint and stability of CosD complexed with 10- and 16 trier DNA was investigated using several applications of electrospray ionisation mass spectrometry (ESI-MS). ESI-MS binding profiles showed that fewer CosD molecules bound to the sequences than Dn or Dx. In agreement with this, ESI-MS analysis of nuclease digestion products of the complexes showed that CosD protected the DNA to a greater extent than Dn or Dx. In tandem MS experiments, all CosD-DNA complexes were more stable than Dn- and Dx-DNA complexes. These results Support that CosD binds more tightly to DNA and exerts a larger footprint than ESI-MS investigations of the binding properties of CosD Could be carried out rapidly and using only small amounts of sample. (C) 2008 Elsevier Inc. All rights reserved.

Loops, Chains, Sheets, and Networks from Variable Coordination of Cu(hfac)(2) with a Flexibly Hinged Aminoxyl Radical Ligand

One pair of reactants, Cu(hfac)(2) = M and the hinge-flexible radical ligand 5-(3-N-tert-butyl-N-aminoxylphenyl)pyrimidine (3PPN = L), yields a diverse set of five coordination complexes: a cyclic loop M(2)L(1) dimer; a 1:1 cocrystal between an M(2)L(2) loop and an ML(2) fragment; a ID chain of M(2)L(2) loops linked by M; two 2D M(3)L(2) networks of (M-L)(n) chains crosslinked by M with different repeat length pitches; a 3D M(3)L(2) network of M(2)L(2) loops cross-linking (M-L)(n)-type chains with connectivity different from those in the 2D networks. Most of the higher dimensional complexes exhibit reversible, temperature-dependent spin-state conversion of high-temperature paramagnetic states to lower magnetic moment states having antiferromagnetic exchange within Cu-ON bonds upon cooling, with accompanying bond contraction. The 3D complex also exhibited antiferromagnetic exchange between Cu(II) ions linked in chains through pyrimidine rings.

Energy of bond defects in quantum spin chains obtained from local approximations and from exact diagonalization

We study the influence of ferromagnetic and antiferromagnetic bond defects on the ground-state energy of antiferromagnetic spin chains. In the absence of translational invariance, the energy spectrum of the full Hamiltonian is obtained numerically, by an iterative modi. cation of the power algorithm. In parallel, approximate analytical energies are obtained from a local-bond approximation, proposed here. This approximation results in significant improvement upon the mean-field approximation, at negligible extra computational effort. (C) 2008 Published by Elsevier B.V.

NMR study of slow motions of HDA hydrocarbons chains inside lamellar structures

Measurements of H-1 and C-13 Nuclear Magnetic Resonance (NMR) for the nano-composite materials formed by the intercalation of hexadecylamine (HDA) in metal oxides (TiO2, V2O5 and MoO3), are reported. The H-1 NMR spin-lattice relaxation in the rotating frame was described by using the spectral density due to Davidson and Cole, which incorporates a distribution of correlation times characterized by a width parameter epsilon. The fitting of the data was obtained for epsilon = 0.74, indicating that the correlation times are distributed over a narrow range in this system. High-resolution C-13 NMR techniques were used to resolve the NMR lines of middle-chain methylene groups in the spectra and variable contact time cross-polarization {H-1-}C-13 experiments were employed to analyze the reorientation dynamics of the CH3 and CH2 groups in the HDA chains.