The prima donna of epigenetics: the regulation of gene expression by DNA methylation

This review focuses on the mechanisms of DNA methylation, DNA methylation pattern formation and their involvement in gene regulation. Association of DNA methylation with imprinting, embryonic development and human diseases is discussed. Furthermore, besides considering changes in DNA methylation as mechanisms of disease, the role of epigenetics in general and DNA methylation in particular in transgenerational carcinogenesis, in memory formation and behavior establishment are brought about as mechanisms based on the cellular memory of gene expression patterns.

Public-private partnership investments in dry ports – Russian logistics markets and risks

The investments have always been considered as an essential backbone and so-called ‘locomotive’ for the competitive economies. However, in various countries, the state has been put under tight budget constraints for the investments in capital intensive projects. In response to this situation, the cooperation between public and private sector has grown based on public-private mechanism. The promotion of favorable arrangement for collaboration between public and private sectors for the provision of policies, services, and infrastructure in Russia can help to address the problems of dry ports development that neither municipalities nor the private sector can solve alone. Especially, the stimulation of public-private collaboration is significant under the exposure to externalities that affect the magnitude of the risks during all phases of project realization. In these circumstances, the risk in the projects also is becoming increasingly a part of joint research and risk management practice, which is viewed as a key approach, aiming to take active actions on existing global and specific factors of uncertainties. Meanwhile, a relatively little progress has been made on the inclusion of the resilience aspects into the planning process of a dry ports construction that would instruct the capacity planner, on how to mitigate the occurrence of disruptions that may lead to million dollars of losses due to the deviation of the future cash flows from the expected financial flows on the project. The current experience shows that the existing methodological base is developed fragmentary within separate steps of supply chain risk management (SCRM) processes: risk identification, risk evaluation, risk mitigation, risk monitoring and control phases. The lack of the systematic approach hinders the solution of the problem of risk management processes of dry port implementation. Therefore, management of various risks during the investments phases of dry port projects still presents a considerable challenge from the practical and theoretical points of view. In this regard, the given research became a logical continuation of fundamental research, existing in the financial models and theories (e.g., capital asset pricing model and real option theory), as well as provided a complementation for the portfolio theory. The goal of the current study is in the design of methods and models for the facilitation of dry port implementation through the mechanism of public-private partnership on the national market that implies the necessity to mitigate, first and foremost, the shortage of the investments and consequences of risks. The problem of the research was formulated on the ground of the identified contradictions. They rose as a continuation of the trade-off between the opportunities that the investors can gain from the development of terminal business in Russia (i.e. dry port implementation) and risks. As a rule, the higher the investment risk, the greater should be their expected return. However, investors have a different tolerance for the risks. That is why it would be advisable to find an optimum investment. In the given study, the optimum relates to the search for the efficient portfolio, which can provide satisfaction to the investor, depending on its degree of risk aversion. There are many theories and methods in finance, concerning investment choices. Nevertheless, the appropriateness and effectiveness of particular methods should be considered with the allowance of the specifics of the investment projects. For example, the investments in dry ports imply not only the lump sum of financial inflows, but also the long-term payback periods. As a result, capital intensity and longevity of their construction determine the necessity from investors to ensure the return on investment (profitability), along with the rapid return on investment (liquidity), without precluding the fact that the stochastic nature of the project environment is hardly described by the formula-based approach. The current theoretical base for the economic appraisals of the dry port projects more often perceives net present value (NPV) as a technique superior to other decision-making criteria. For example, the portfolio theory, which considers different risk preference of an investor and structures of utility, defines net present value as a better criterion of project appraisal than discounted payback period (DPP). Meanwhile, in business practice, the DPP is more popular. Knowing that the NPV is based on the assumptions of certainty of project life, it cannot be an accurate appraisal approach alone to determine whether or not the project should be accepted for the approval in the environment that is not without of uncertainties. In order to reflect the period or the project’s useful life that is exposed to risks due to changes in political, operational, and financial factors, the second capital budgeting criterion – discounted payback period is profoundly important, particularly for the Russian environment. Those statements represent contradictions that exist in the theory and practice of the applied science. Therefore, it would be desirable to relax the assumptions of portfolio theory and regard DPP as not fewer relevant appraisal approach for the assessment of the investment and risk measure. At the same time, the rationality of the use of both project performance criteria depends on the methods and models, with the help of which these appraisal approaches are calculated in feasibility studies. The deterministic methods cannot ensure the required precision of the results, while the stochastic models guarantee the sufficient level of the accuracy and reliability of the obtained results, providing that the risks are properly identified, evaluated, and mitigated. Otherwise, the project performance indicators may not be confirmed during the phase of project realization. For instance, the economic and political instability can result in the undoing of hard-earned gains, leading to the need for the attraction of the additional finances for the project. The sources of the alternative investments, as well as supportive mitigation strategies, can be studied during the initial phases of project development. During this period, the effectiveness of the investments undertakings can also be improved by the inclusion of the various investors, e.g. Russian Railways’ enterprises and other private companies in the dry port projects. However, the evaluation of the effectiveness of the participation of different investors in the project lack the methods and models that would permit doing the particular feasibility study, foreseeing the quantitative characteristics of risks and their mitigation strategies, which can meet the tolerance of the investors to the risks. For this reason, the research proposes a combination of Monte Carlo method, discounted cash flow technique, the theory of real options, and portfolio theory via a system dynamics simulation approach. The use of this methodology allows for comprehensive risk management process of dry port development to cover all aspects of risk identification, risk evaluation, risk mitigation, risk monitoring, and control phases. A designed system dynamics model can be recommended for the decision-makers on the dry port projects that are financed via a public-private partnership. It permits investors to make a decision appraisal based on random variables of net present value and discounted payback period, depending on different risks factors, e.g. revenue risks, land acquisition risks, traffic volume risks, construction hazards, and political risks. In this case, the statistical mean is used for the explication of the expected value of the DPP and NPV; the standard deviation is proposed as a characteristic of risks, while the elasticity coefficient is applied for rating of risks. Additionally, the risk of failure of project investments and guaranteed recoupment of capital investment can be considered with the help of the model. On the whole, the application of these modern methods of simulation creates preconditions for the controlling of the process of dry port development, i.e. making managerial changes and identifying the most stable parameters that contribute to the optimal alternative scenarios of the project realization in the uncertain environment. System dynamics model allows analyzing the interactions in the most complex mechanism of risk management process of the dry ports development and making proposals for the improvement of the effectiveness of the investments via an estimation of different risk management strategies. For the comparison and ranking of these alternatives in their order of preference to the investor, the proposed indicators of the efficiency of the investments, concerning the NPV, DPP, and coefficient of variation, can be used. Thus, rational investors, who averse to taking increased risks unless they are compensated by the commensurate increase in the expected utility of a risky prospect of dry port development, can be guided by the deduced marginal utility of investments. It is computed on the ground of the results from the system dynamics model. In conclusion, the outlined theoretical and practical implications for the management of risks, which are the key characteristics of public-private partnerships, can help analysts and planning managers in budget decision-making, substantially alleviating the effect from various risks and avoiding unnecessary cost overruns in dry port projects.

Transfection of newt blastema mesenchyme using the techniques of lipofection and direct gene transfer

The regenerating amphibian limb provides a useful system for studying genes involved in the establishment of positional information. While a number of candidate genes that may playa role in pattern formation have been identified, their function in vivo is unknown in this system. To better ascertain the role of these genes, it would be useful to be able to alter their normal patterns of expression in vivo and to assess the effects of this misexpression on limb pattern. In order to achieve this, a method of introducing a plasmid containing the eDNA of a gene of interest into a newt blastema (a growth zone of mesenchymal progenitor cells) is needed. Unfortunately, most commonly used transfection techniques cannot be used with newt blastema cells. In this study, I have used the techniques of lipofection and direct gene transfer to introduce plasmid DNA containing reporter genes into the cells of a regenerating newt limb. The technique of lipofection was most effective when the blastema cells were transfected in vitro. The optimal ratio for transfection was shown to be 1:3 DNA:Lipofectin (W/w) , and an increase in the amount of DNA present in the mixture (1:3 ratio maintained) resulted in a corresponding increase in gene expression. The technique of direct gene transfer was used to transfect newt blastema cells with and without prior complex formation with Lipofectin. Injection of plasmid DNA alone provided the most 3 promising results. It was possible to introduce plasmid DNA containing the reporter gene ~-galactosidase and achieve significant gene expression in cells associated with the injection site. In the future, it would be interesting to use this technique to inject plasmid DNA containing a gene which may have a role in pattern formation into specific areas of the newt blastema and to analyze the resulting limb pattern that emerges.

Analyse fonctionnelle du gène BMP-2 lors de la régénération du membre chez l’axolotl

Les amphibiens urodèles (e.g. les axolotls) possèdent la remarquable capacité de régénérer plusieurs parties de leur corps. Ils peuvent, entre autres, régénérer parfaitement un membre amputé par épimorphose, un processus biphasique comprenant une phase de préparation, spécifique à la régénération, et une phase de redéveloppement, commune à l’épimorphose et au développement embryonnaire. Durant la phase de préparation, les cellules du moignon se dédifférencient en cellules pseudo-embryonnaires, prolifèrent et migrent distalement au plan d’amputation pour former un blastème de régénération. Parmi les vertébrés, la dédifférenciation est unique aux urodèles. Afin de mieux comprendre le contrôle moléculaire de la régénération chez les urodèles, nous avons choisi d’étudier BMP-2, un facteur de croissance, en raison de son implication dans la régénération des phalanges distales chez les mammifères. Le facteur de transcription MSX-1 a également été sélectionné en raison de sa capacité à induire la dédifférenciation cellulaire in vitro et de son interaction potentielle avec la signalisation des BMPs. Les résultats présentés dans cette thèse démontrent que BMP-2 et MSX-1 sont exprimés lors des phases de préparation et de redéveloppement de l’épimorphose, et que leur profil d'expression spatio-temporel est très semblable, ce qui suggère une interaction de leurs signaux. En outre, chez les tétrapodes amniotes, l’expression de Shh est restreinte au mésenchyme postérieur des membres en développement et chevauche l’expression de BMP-2. Toutefois, l’expression de BMP-2 n’est pas restreinte à la région postérieure mais forme un gradient postéro-antérieur. Shh est le principal régulateur de la formation du patron de développement antéro-postérieur du ii membre. Étant donné les domaines d’expression chevauchants de BMP-2 et Shh et la restriction postérieure d’expression de Shh, on croit que Shh régule la formation du patron de développement de postérieur à antérieur par l’activation de l’expression de BMP-2. Fait intéressant, l’axolotl exprime également Shh dans la région postérieure, mais le développement des pattes se fait de la région antérieure à la région postérieure au lieu de postérieur à antérieur comme chez les autres tétrapodes, et ceci durant le développement et la régénération. Nous avons utilisé cette caractéristique de l’axolotl pour démontrer que la signalisation Shh ne structure pas l’autopode via BMP-2. En effet, l’expression de BMP-2 n'est pas régulée par l'inhibition de la signalisation Shh, et son expression est du côté opposé à celle de Shh durant le développement et la régénération des pattes de l’axolotl. Il a été observé durant le développement du membre chez la souris que MSX-1 est régulé par la signalisation Shh. Nos résultats ont démontrés que chez l’axolotl, MSX-1 ne semble pas régulé par l'inhibition de la signalisation Shh au cours de la régénération du membre. De plus, nous avons démontré que contrairement à l’expression de Shh, l’expression de BMP-2 est corrélée avec l’ordre de formation des phalanges, est impliquée dans la condensation cellulaire et dans l'apoptose précédant la chondrogenèse. L’ensemble de ces résultats suggère un rôle de BMP-2 dans l’initiation de l’ossification endochondrale. Enfin, nous avons démontré que la signalisation BMP est indispensable pour l’épimorphose du membre durant la phase de redéveloppement.

Substrats neuronaux de la mémoire épisodique et de la mémoire de travail dans le vieillissement normal et pathologique

La maladie d’Alzheimer (MA) est de loin le type de démence le plus répandu chez les personnes âgées. Il est maintenant possible de proposer un certain nombre d’interventions ou de stratégies préventives aux personnes portant un diagnostic de MA ou à risque de développer la maladie. Il est donc important de diagnostiquer cette maladie le plus tôt possible. Les personnes avec un trouble cognitif léger (TCL) représentent une population d’intérêt puisqu’elles sont à haut risque d’évoluer vers une démence et plusieurs d’entres elles seraient ainsi dans une phase prodromale de la MA. Les travaux de cette thèse visent à explorer les activations fonctionnelles associées à la mémoire épisodique et à la mémoire de travail dans le TCL ainsi qu’aux effets de la sévérité de la maladie et des caractéristiques de la tâche sur ces activations. Dans un premier temps, nous exposerons les connaissances relatives au niveau des atteintes cognitives, du patron d’activation fonctionnelle et des plus récents modèles élaborés pour expliquer les changements d’activation dans le vieillissement normal et pathologique (Chapitre 1). Par la suite, les études réalisées dans le cadre de cette thèse seront présentées. Nous avons d’abord étudié la fiabilité du signal d’activation chez les TCL et chez les personnes âgées saines (PA) à l’aide de tâches d’encodage et de récupération de mots (Chapitre 2). Nous avons ensuite comparé le patron d’activation cérébral des PA et des personnes TCL alors qu’elles réalisaient une tâche d’encodage et de récupération de mots. L’effet de la sévérité a été évalué en corrélant les activations des personnes TCL à leurs scores obtenu à une échelle évaluant leur cognition globale (Chapitre 3). L’effet de sévérité a ensuite été étudié de manière plus approfondie chez un plus grand nombre de TCL en utilisant la médiane du groupe à cette même échelle pour déterminer un groupe de TCL plus atteints et un groupe de TCL moins atteints. Ces deux groupes ont ensuite été comparés à un groupe de PA lors d’une tâche d’encodage de paires de mots reliés sémantiquement ou non-reliés (Chapitre 4), une tâche de reconnaissance de paires de mots mesurant principalement la familiarité ou principalement la recollection (Chapitre 5), ainsi que deux tâches impliquant des composantes différentes de la mémoire de travail et des fonctions exécutives, soit la manipulation de l’information et l’attention divisée (Chapitre 6). Les résultats présentés dans cette thèse ont mis en évidence une distinction entre le patron d’activation des TCL et des PA qui semble caractérisée par une interaction entre le niveau de sévérité de la maladie et les processus cognitifs impliqués dans la tâche. L’effet de sévérité a été observé lors de plusieurs tâches impliquant des processus cognitifs différents où les MCI moins atteints ont montré principalement des hyperactivations sous-tendant des mécanismes compensatoires et les MCI plus atteints ont montré principalement des hypoactivations soulignant la dégradation de ces mécanismes. Par ailleurs, les résultats de nos études ont aussi montré que cet effet de sévérité est modulé par le moment d’altération du processus cognitif impliqué dans la tâche: les processus altérés précocément dans le TCL sont caractériséees par des hyperactivations chez les TCL moins atteints tandis que les processus altérés plus tardivement ont plutôt élicité des hyperactivations chez les TCL plus atteints. Les implications de ces résultats, ainsi que les limites des études, sont discutés (Chapitre 7).

Studies on the Effect of Randomness on the Synchronization of Coupled Systems and on the Dynamics of Intermittently driven systems

Nonlinear dynamics has emerged into a prominent area of research in the past few Decades.Turbulence, Pattern formation,Multistability etc are some of the important areas of research in nonlinear dynamics apart from the study of chaos.Chaos refers to the complex evolution of a deterministic system, which is highly sensitive to initial conditions. The study of chaos theory started in the modern sense with the investigations of Edward Lorentz in mid 60's. Later developments in this subject provided systematic development of chaos theory as a science of deterministic but complex and unpredictable dynamical systems. This thesis deals with the effect of random fluctuations with its associated characteristic timescales on chaos and synchronization. Here we introduce the concept of noise, and two familiar types of noise are discussed. The classifications and representation of white and colored noise are introduced. Based on this we introduce the concept of randomness that we deal with as a variant of the familiar concept of noise. The dynamical systems introduced are the Rossler system, directly modulated semiconductor lasers and the Harmonic oscillator. The directly modulated semiconductor laser being not a much familiar dynamical system, we have included a detailed introduction to its relevance in Chaotic encryption based cryptography in communication. We show that the effect of a fluctuating parameter mismatch on synchronization is to destroy the synchronization. Further we show that the relation between synchronization error and timescales can be found empirically but there are also cases where this is not possible. Studies show that under the variation of the parameters, the system becomes chaotic, which appears to be the period doubling route to chaos.

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced

Diversity, local uses and availability of medicinal plants and wild yams in the Mahafaly region of south-western Madagascar

Short summary: This study was undertaken to assess the diversity of plant resources utilized by the local population in south-western Madagascar, the social, ecological and biophysical conditions that drive their uses and availability, and possible alternative strategies for their sustainable use in the region. The study region, ‘Mahafaly region’, located in south-western Madagascar, is one of the country’s most economically, educationally and climatically disadvantaged regions. With an arid steppe climate, the agricultural production is limited by low water availability and a low level of soil nutrients and soil organic carbon. The region comprises the recently extended Tsimanampetsotsa National Park, with numerous sacred and communities forests, which are threatened by slash and burn agriculture and overexploitation of forests resources. The present study analyzed the availability of wild yams and medicinal plants, and their importance for the livelihood of the local population in this region. An ethnobotanical survey was conducted recording the diversity, local knowledge and use of wild yams and medicinal plants utilized by the local communities in five villages in the Mahafaly region. 250 households were randomly selected followed by semi-structured interviews on the socio-economic characteristics of the households. Data allowed us to characterize sociocultural and socioeconomic factors that determine the local use of wild yams and medicinal plants, and to identify their role in the livelihoods of local people. Species-environment relationships and the current spatial distribution of the wild yams were investigated and predicted using ordination methods and a niche based habitat modelling approach. Species response curves along edaphic gradients allowed us to understand the species requirements on habitat conditions. We thus investigated various alternative methods to enhance the wild yam regeneration for their local conservation and their sustainable use in the Mahafaly region. Altogether, six species of wild yams and a total of 214 medicinal plants species from 68 families and 163 genera were identified in the study region. Results of the cluster and discriminant analysis indicated a clear pattern on resource, resulted in two groups of household and characterized by differences in livestock numbers, off-farm activities, agricultural land and harvests. A generalized linear model highlighted that economic factors significantly affect the collection intensity of wild yams, while the use of medicinal plants depends to a higher degree on socio-cultural factors. The gradient analysis on the distribution of the wild yam species revealed a clear pattern for species habitats. Species models based on NPMR (Nonparametric Multiplicative Regression analysis) indicated the importance of vegetation structure, human interventions, and soil characteristics to determine wild yam species distribution. The prediction of the current availability of wild yam resources showed that abundant wild yam resources are scarce and face high harvest intensity. Experiments on yams cultivation revealed that germination of seeds was enhanced by using pre-germination treatments before planting, vegetative regeneration performed better with the upper part of the tubers (corms) rather than the sets of tubers. In-situ regeneration was possible for the upper parts of the wild tubers but the success depended significantly on the type of soil. The use of manure (10-20 t ha¹) increased the yield of the D. alata and D. alatipes by 40%. We thus suggest the promotion of other cultivated varieties of D. alata found regions neighbouring as the Mahafaly Plateau.

Multisensor Modeling Underwater with Uncertain Information

This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. It describes methods for building models by a three- dimensional spatial decomposition of stochastic, multisensor feature vectors. New sensor information is incrementally incorporated into the model by stochastic backprojection. Error and ambiguity are explicitly accounted for by blurring a spatial projection of remote sensor data before incorporation. The stochastic models can be used to derive surface maps or other representations of the environment. The methods are demonstrated on data sets from multibeam bathymetric surveying, towed sidescan bathymetry, towed sidescan acoustic imagery, and high-resolution scanning sonar aboard a remotely operated vehicle.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

On the spectra of certain integro-differential-delay problems with applications in neurodynamics

We investigate the spectrum of certain integro-differential-delay equations (IDDEs) which arise naturally within spatially distributed, nonlocal, pattern formation problems. Our approach is based on the reformulation of the relevant dispersion relations with the use of the Lambert function. As a particular application of this approach, we consider the case of the Amari delay neural field equation which describes the local activity of a population of neurons taking into consideration the finite propagation speed of the electric signal. We show that if the kernel appearing in this equation is symmetric around some point a= 0 or consists of a sum of such terms, then the relevant dispersion relation yields spectra with an infinite number of branches, as opposed to finite sets of eigenvalues considered in previous works. Also, in earlier works the focus has been on the most rightward part of the spectrum and the possibility of an instability driven pattern formation. Here, we numerically survey the structure of the entire spectra and argue that a detailed knowledge of this structure is important within neurodynamical applications. Indeed, the Amari IDDE acts as a filter with the ability to recognise and respond whenever it is excited in such a way so as to resonate with one of its rightward modes, thereby amplifying such inputs and dampening others. Finally, we discuss how these results can be generalised to the case of systems of IDDEs.

Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation

Many modern statistical applications involve inference for complex stochastic models, where it is easy to simulate from the models, but impossible to calculate likelihoods. Approximate Bayesian computation (ABC) is a method of inference for such models. It replaces calculation of the likelihood by a step which involves simulating artificial data for different parameter values, and comparing summary statistics of the simulated data with summary statistics of the observed data. Here we show how to construct appropriate summary statistics for ABC in a semi-automatic manner. We aim for summary statistics which will enable inference about certain parameters of interest to be as accurate as possible. Theoretical results show that optimal summary statistics are the posterior means of the parameters. Although these cannot be calculated analytically, we use an extra stage of simulation to estimate how the posterior means vary as a function of the data; and we then use these estimates of our summary statistics within ABC. Empirical results show that our approach is a robust method for choosing summary statistics that can result in substantially more accurate ABC analyses than the ad hoc choices of summary statistics that have been proposed in the literature. We also demonstrate advantages over two alternative methods of simulation-based inference.

Parametric preference functionals under risk in the gain domain: a Bayesian analysis

The performance of rank dependent preference functionals under risk is comprehensively evaluated using Bayesian model averaging. Model comparisons are made at three levels of heterogeneity plus three ways of linking deterministic and stochastic models: the differences in utilities, the differences in certainty equivalents and contextualutility. Overall, the"bestmodel", which is conditional on the form of heterogeneity is a form of Rank Dependent Utility or Prospect Theory that cap tures the majority of behaviour at both the representative agent and individual level. However, the curvature of the probability weighting function for many individuals is S-shaped, or ostensibly concave or convex rather than the inverse S-shape commonly employed. Also contextual utility is broadly supported across all levels of heterogeneity. Finally, the Priority Heuristic model, previously examined within a deterministic setting, is estimated within a stochastic framework, and allowing for endogenous thresholds does improve model performance although it does not compete well with the other specications considered.