Influence Networks

Some behaviors, ideas or technologies spread and become persistent in society, whereas others vanish. This paper analyzes the role of social influence in determining such distinct collective outcomes. Agents are assumed to acquire information from others through a certain sampling process that generates an influence network and use simple rules to decide whether to adopt or not depending on the observed sample. The diffusion threshold (i.e., the spreading rate above which the behavior becomes persistent in the population) and the endemic state (i.e., the fraction of adopters in the stationary state of the dynamics) are characterized as a function of the primitives of the model. The results highlight the importance of the correlation between visibility and connectivity (or degree) for diffusion purposes.social influence, networks, diffusion threshold, endemic state.

On the concept of depth for functional data

The statistical analysis of functional data is a growing need in many research areas. We propose a new depth notion for functional observations based on the graphic representation of the curves. Given a collection of functions, it allows to establish the centrality of a function and provides a natural center-outward ordering of the sample curves. Robust statistics such as the median function or a trimmed mean function can be defined from this depth definition. Its finite-dimensional version provides a new depth for multivariate data that is computationally very fast and turns out to be convenient to study high-dimensional observations. The natural properties are established for the new depth and the uniform consistency of the sample depth is proved. Simulation results show that the trimmed mean presents a better behavior than the mean for contaminated models. Several real data sets are considered to illustrate this new concept of depth. Finally, we use this new depth to generalize to functions the Wilcoxon rank sum test. It allows to decide whether two groups of curves come from the same population. This functional rank test is applied to girls and boys growth curves concluding that they present different growth patterns

Depth-based inference for functional data

We propose robust inference tools for functional data based on the notion of depth for curves. We extend the ideas of trimmed regions, contours and central regions to functions and study their structural properties and asymptotic behavior. Next, we introduce a scale curve to describe dispersion in a sample of functions. The computational burden of these techniques is not heavy and so they are also adequate to analyze high-dimensional data. All these inferential methods are applied to different real data sets

Depth-based classification for functional data

Classification is an important task when data are curves. Recently, the notion of statistical depth has been extended to deal with functional observations. In this paper, we propose robust procedures based on the concept of depth to classify curves. These techniques are applied to a real data example. An extensive simulation study with contaminated models illustrates the good robustness properties of these depth-based classification methods

A half-graph depth for functional data

A recent and highly attractive area of research in statistics is the analysis of functional data. In this paper a new definition of depth for functional observations is introduced based on the notion of "half-graph" of a curve. It has computational advantages with respect to other concepts of depth previously proposed. The half-graph depth provides a natural criterion to measure the centrality of a function within a sample of curves. Based on this depth a sample of curves can be ordered from the center outward and L-statistics are defined. The properties of the half-graph depth, such as the consistency and uniform convergence, are established. A simulation study shows the robustness of this new definition of depth when the curves are contaminated. Finally real data examples are analyzed

SOLOMON'S DILEMMA: AN EXPERIMENTAL STUDY ON DYNAMIC IMPLEMENTATION

This paper reports an experimental investigation on two mechanisms for the so-called King Solomon Dilemma, where one of them fails to implement the social choice rule dynamically. We compare the two mechanisms in terms of their welfare, incentive and learning properties.experiments, implementation, backward induction, bounded rationality

Diffusion and contagion in networks with heterogeneous agents and homophily

We study how a behavior (an idea, buying a product, having a disease, adopting a cultural fad or a technology) spreads among agents in an a social network that exhibits segregation or homophily (the tendency of agents to associate with others similar to themselves). Individuals are distinguished by their types (e.g., race, gender, age, wealth, religion, profession, etc.) which, together with biased interaction patterns, induce heterogeneous rates of adoption. We identify the conditions under which a behavior diffuses and becomes persistent in the population. These conditions relate to the level of homophily in a society, the underlying proclivities of various types for adoption or infection, as well as how each type interacts with its own type. In particular, we show that homophily can facilitate diffusion from a small initial seed of adopters.Diffusion, Homophily, Segregation, Social Networks

Koostööäriprotsesside läbiviimine plokiahelal: süsteem

Tänapäeval peavad organisatsioonid tegema omavahel koostööd, et kasutada ära üksteise täiendavaid võimekusi ning seeläbi pakkuda oma klientidele parimaid tooteid ja teenuseid. Selleks peavad organisatsioonid juhtima äriprotsesse, mis ületavad nende organisatsioonilisi piire. Selliseid protsesse nimetatakse koostööäriprotsessideks. Üks peamisi takistusi koostööäriprotsesside elluviimisel on osapooltevahelise usalduse puudumine. Plokiahel loob detsentraliseeritud pearaamatu, mida ei saa võltsida ning mis toetab nutikate lepingute täitmist. Nii on võimalik teha koostööd ebausaldusväärsete osapoolte vahel ilma kesksele asutusele tuginemata. Paraku on aga äriprotsesside läbiviimine selliseid madala taseme plokiahela elemente kasutades tülikas, veaohtlik ja erioskusi nõudev. Seevastu juba väljakujunenud äriprotsesside juhtimissüsteemid (Business Process Management System – BPMS) pakuvad käepäraseid abstraheeringuid protsessidele orienteeritud rakenduste kiireks arendamiseks. Käesolev doktoritöö käsitleb koostööäriprotsesside automatiseeritud läbiviimist plokiahela tehnoloogiat kasutades, kombineerides traditsioonliste BPMS- ide arendusvõimalused plokiahelast tuleneva suurendatud usaldusega. Samuti käsitleb antud doktoritöö küsimust, kuidas pakkuda tuge olukordades, milles uued osapooled võivad jooksvalt protsessiga liituda, mistõttu on vajalik tagada paindlikkus äriprotsessi marsruutimisloogika muutmise osas. Doktoritöö uurib tarkvaraarhitektuurilisi lähenemisviise ja modelleerimise kontseptsioone, pakkudes välja disainipõhimõtteid ja nõudeid, mida rakendatakse uudsel plokiahela baasil loodud äriprotsessi juhtimissüsteemil CATERPILLAR. CATERPILLAR-i süsteem toetab kahte lähenemist plokiahelal põhinevate protsesside rakendamiseks, läbiviimiseks ja seireks: kompileeritud ja tõlgendatatud. Samuti toetab see kahte kontrollitud paindlikkuse mehhanismi, mille abil saavad protsessis osalejad ühiselt otsustada, kuidas protsessi selle täitmise ajal uuendada ning anda ja eemaldada osaliste juurdepääsuõigusi.Nowadays, organizations are pressed to collaborate in order to take advantage of their complementary capabilities and to provide best-of-breed products and services to their customers. To do so, organizations need to manage business processes that span beyond their organizational boundaries. Such processes are called collaborative business processes. One of the main roadblocks to implementing collaborative business processes is the lack of trust between the participants. Blockchain provides a decentralized ledger that cannot be tamper with, that supports the execution of programs called smart contracts. These features allow executing collaborative processes between untrusted parties and without relying on a central authority. However, implementing collaborative business processes in blockchain can be cumbersome, error-prone and requires specialized skills. In contrast, established Business Process Management Systems (BPMSs) provide convenient abstractions for rapid development of process-oriented applications. This thesis addresses the problem of automating the execution of collaborative business processes on top of blockchain technology in a way that takes advantage of the trust-enhancing capabilities of this technology while offering the development convenience of traditional BPMSs. The thesis also addresses the question of how to support scenarios in which new parties may be onboarded at runtime, and in which parties need to have the flexibility to change the default routing logic of the business process. We explore architectural approaches and modelling concepts, formulating design principles and requirements that are implemented in a novel blockchain-based BPMS named CATERPILLAR. The CATERPILLAR system supports two methods to implement, execute and monitor blockchain-based processes: compiled and interpreted. It also supports two mechanisms for controlled flexibility; i.e., participants can collectively decide on updating the process during its execution as well as granting and revoking access to parties.https://www.ester.ee/record=b536494

On the optimal management of teams under budget constraints

We study optimal wage schemes for teams, under the presence of budget constraints, in a model in which agents’ effort decisions are mapped into the probability of the team’s success. We show that (first-best) efficiency can only be attained with complex contracts that are vulnerable to ex post manipulations and off-equilibrium path violations of the budget constraints. Within the domain of simple (and budget-balanced) contracts, an interesting scheme, which treats equal members of the team unequally, emerges as optimalTeam production, budget constraints, efficiency, manipulability, impartiality