Integración de Hadoop con planificadores batch

Cada vez es mayor el número de aplicaciones desarrolladas en el ámbito científico, como en la Bioinformática o en las Geociencias, escritas bajo el modelo MapReduce, empleando herramientas de código abierto como Apache Hadoop. De la necesidad de integrar Hadoop en entornos HPC, para posibilitar la ejecutar aplicaciones desarrolladas bajo el paradigma MapReduce, nace el presente proyecto. Se analizan dos frameworks diseñados para facilitar dicha integración a los desarrolladores: HoD y myHadoop. En este proyecto se analiza, tanto las posibilidades en cuanto a entornos que ofrecen dichos frameworks para la ejecución de aplicaciones MapReduce, como el rendimiento de los clúster Hadoop generados con HoD o myHadoop respecto a un clúster Hadoop físico.

Sequential estimation of multipath MIMO-OFDM channels

Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

Sequential estimation of time-varying multipath channel for MIMO-OFDM systems

In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

A sequential model for older workers' labor transitions after a health shock

In this work we study older workers'(50-64) labor force transitions after a health/disability shock. We find that the probability of keeping working decreases with both age and severity of the shock. Moreover, we find strong interactions between age and severity in the 50-64 age range and none in the 30-49 age range. Regarding demographics we find that being female and married reduce the probability of keeping work. On the contrary, being main breadwinner, education and skill levels increase it. Interestingly, the effect of some demographics changes its sign when we look at transitions from inactivity to work. This is the case of being married or having a working spouse. Undoubtedly, leisure complementarities should play a role in the latter case. Since the data we use contains a very detailed information on disabilities, we are able to evaluate the marginal effect of each type of disability either in the probability of keeping working or in returning back to work. Some of these results may have strong policy implications.

Bundling and competition for slots: Sequential pricing

In this paper we study, as in Jeon-Menicucci (2009), competition between sellerswhen each of them sells a portfolio of distinct products to a buyer having limitedslots. This paper considers sequential pricing and complements our main paper (Jeon-Menicucci, 2009) that considers simultaneous pricing.First, Jeon-Menicucci (2009) find that under simultaneous individual pricing, equilibriumoften does not exist and hence the outcome is often inefficient. By contrast,equilibrium always exists under sequential individual pricing and we characterize it inthis paper. We find that each seller faces a trade-off between the number of slots heoccupies and surplus extraction per product, and there is no particular reason thatthis leads to an efficient allocation of slots.Second, Jeon-Menicucci (2009) find that when bundling is allowed, there alwaysexists an efficient equilibrium but inefficient equilibria can also exist due to purebundling (for physical products) or slotting contracts. Under sequential pricing,we find that all equilibria are efficient regardless of whether firms can use slottingcontracts, and both for digital goods and for physical goods. Therefore, sequentialpricing presents an even stronger case for laissez-faire in the matter of bundling thansimultaneous pricing.

Hot vs. cold: Sequential responses and preference stability in experimental games

In experiments with two-person sequential games we analyzewhether responses to favorable and unfavorable actions dependon the elicitation procedure. In our hot treatment thesecond player responds to the first player s observed actionwhile in our cold treatment we follow the strategy method and have the second player decide on a contingent action foreach and every possible first player move, without firstobserving this move. Our analysis centers on the degree towhich subjects deviate from the maximization of their pecuniaryrewards, as a response to others actions. Our results show nodifference in behavior between the two treatments. We also findevidence of the stability of subjects preferences with respectto their behavior over time and to the consistency of theirchoices as first and second mover.

Strategies for sequential prediction of stationary time series

We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.

A sequential model for older workers’ labor transitions after a health shock

In this work we study older workers (50 64) labor force transitions after a health/disability shock. We find that the probability of keeping working decreases with both age and severity of the shock. Moreover, we find strong interactions between age and severity in the 50 64 age range and none in the 30 49 age range. Regarding demographics we find that being female and married reduce the probability of keeping work. On the contrary, being main breadwinner, education and skill levels increase it. Interestingly, the effect of some demographics changes its sign when we look at transitions from inactivity to work. This is the case of being married or having a working spouse. Undoubtedly, leisure complementarities should play a role in the latter case. Since the data we use contains a very detailed information on disabilities, we are able to evaluate the marginal effect of each type of disability either in the probability of keeping working or in returning back to work. Some of these results may have strong policy implications.

Choice by sequential procedures

We propose a rule of decision-making, the sequential procedure guided byroutes, and show that three influential boundedly rational choice models can be equivalentlyunderstood as special cases of this rule. In addition, the sequential procedure guidedby routes is instrumental in showing that the three models are intimately related. We showthat choice with a status-quo bias is a refinement of rationalizability by game trees, which, inturn, is also a refinement of sequential rationalizability. Thus, we provide a sharp taxonomyof these choice models, and show that they all can be understood as choice by sequentialprocedures.

Valuation bubbles and sequential bubbles

Price bubbles in an Arrow-Debreu valuation equilibrium in infinite-timeeconomy are a manifestation of lack of countable additivity of valuationof assets. In contrast, known examples of price bubbles in sequentialequilibrium in infinite time cannot be attributed to the lack of countableadditivity of valuation. In this paper we develop a theory of valuation ofassets in sequential markets (with no uncertainty) and study the nature ofprice bubbles in light of this theory. We consider an operator, calledpayoff pricing functional, that maps a sequence of payoffs to the minimumcost of an asset holding strategy that generates it. We show that thepayoff pricing functional is linear and countably additive on the set ofpositive payoffs if and only if there is no Ponzi scheme, and providedthat there is no restriction on long positions in the assets. In the knownexamples of equilibrium price bubbles in sequential markets valuation islinear and countably additive. The presence of a price bubble indicatesthat the asset's dividends can be purchased in sequential markers at acost lower than the asset's price. We also present examples of equilibriumprice bubbles in which valuation is nonlinear but not countably additive.

A characterization of sequential rationalizability

A choice function is sequentially rationalizable if there is an ordered collection of asymmetric binary relations that identifies the selected alternative in every choice problem. We propose a property, F-consistency, and show that it characterizes the notion of sequential rationalizability. F-consistency is a testable property that highlights the behavioral aspects implicit in sequentially rationalizable choice. Further, our characterization result provides a novel tool with which to study how other behavioral concepts are related to sequential rationalizability, and establish a priori unexpected implications. In particular, we show that the concept of rationalizability by game trees, which, in principle, had little to do with sequential rationalizability, is a refinement of the latter. Every choice function that is rationalizable by a game tree is also sequentially rationalizable. Finally, we show that some prominent voting mechanisms are also sequentially rationalizable.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

Sequential screening

We present a model of price discrimination where a monopolistfaces a consumer who is privately informed about thedistribution of his valuation for an indivisible unit ofgood but has yet to learn privately the actual valuation.The monopolist sequentially screens the consumer with amenu of contracts:the consumer self-selects once by choosing a contract andthen self-selects again when he learns the actual valuation. A deterministic sequential mechanism is a menu of refundcontracts, each consisting of an advance payment and a refundamount in case of no consumption, but sequential mechanismsmay involve randomization.We characterize the optimal sequential mechanism when someconsumer types are more eager in the sense of first-orderstochastic dominance, and when some types face greatervaluation uncertainty in the sense of mean-preserving-spread.We show that it can be optimal to subsidize consumer typeswith smaller valuation uncertainty (through low refund, as inairplane ticket pricing) in order to reduce the rent to thosewith greater uncertainty. The size of distortion depends bothon the type distribution and on how informative the consumer'sinitial private knowledge is about his valuation, but noton how much he initially knows about the valuation per se.

A zero-delay sequential scheme for lossy coding of individual sequences

We consider adaptive sequential lossy coding of bounded individual sequences when the performance is measured by the sequentially accumulated mean squared distortion. Theencoder and the decoder are connected via a noiseless channel of capacity $R$ and both are assumed to have zero delay. No probabilistic assumptions are made on how the sequence to be encoded is generated. For any bounded sequence of length $n$, the distortion redundancy is defined as the normalized cumulative distortion of the sequential scheme minus the normalized cumulative distortion of the best scalarquantizer of rate $R$ which is matched to this particular sequence. We demonstrate the existence of a zero-delay sequential scheme which uses common randomization in the encoder and the decoder such that the normalized maximum distortion redundancy converges to zero at a rate $n^{-1/5}\log n$ as the length of the encoded sequence $n$ increases without bound.