982 resultados para Interior point algorithm
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In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.
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We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.
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Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.
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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.
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We investigate on-line prediction of individual sequences. Given a class of predictors, the goal is to predict as well as the best predictor in the class, where the loss is measured by the self information (logarithmic) loss function. The excess loss (regret) is closely related to the redundancy of the associated lossless universal code. Using Shtarkov's theorem and tools from empirical process theory, we prove a general upper bound on the best possible (minimax) regret. The bound depends on certain metric properties of the class of predictors. We apply the bound to both parametric and nonparametric classes ofpredictors. Finally, we point out a suboptimal behavior of the popular Bayesian weighted average algorithm.
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Este estudo sobre as concepções de maternidades e paternidades no interior de Santiago, especificamente em Ribeira da Barca, visa analisar como as técnicas utilizadas no parto determinam a forma como se constitui a noção de pessoa, o que abre um dialogo entre a construções de concepções de maternidade e paternidade. Essa reflexão passa necessariamente por uma discussão da noção de pessoa como um individuo total indivisível, onde não existe uma fronteira visível entre a natureza e cultura. Essa forma como se constrói a noção de pessoa é verificável na maneira como se molda o corpo na gravidez, no parto e no pós-parto. Nessa óptica, é analisada como se dá forma ao corpo partindo do princípio que este é algo passivel de ser moldado, dinâmico e com fluxos vitais, integrado nos ciclos da vida e do ambiente (onde não existe uma fronteira visivel entre a natureza e a cultura). Essa discussão permite-nos pensar as concepções de maternidades e paternidades dependentes da relação e de vínculos que as pessoas estabelecem entre si numa trajectória, da forma como as mesmas se constituem como pessoa. Essa análise é extensiva a própria organização familiar que ultrapassa a consanguinidade, constituindo, assim, numa trama de relações que as pessoas constróem entre si
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Este trabalho resultou de uma análise das ligações inter-ilhas no arquipélago de Cabo Verde no intervalo de tempo entre 2008 a 2011, com o intuito de se saber qual é a situação dos transportes no país no ano em que termina o prazo de vigência do PEDTCV. Neste estudo, analisaram-se as ligações inter-ilhas existentes no país a nível aéreo e marítimo, também interligaram-se essas ligações com o fluxo de passageiros inter-ilhas nacionais e estrangeiros. O estudo foi encaminhado através de uma revisão bibliográfica sobre o conceito do turismo, a importância dos transportes para o turismo, os transportes e tipos, as infra-estruturas e o Turismo Interior. Para fazer essa análise de forma completa teve-se que recorrer à análise de fontes secundárias, estatísticas e documentais, pois o tema era abrangente e o tempo limitado. Estes dados foram facultados pelo INE, ENAPOR sa., IMP e os TACV.
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Audit report on the City of Center Point, Iowa for the year ended June 30, 2008
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We consider an agent who has to repeatedly make choices in an uncertainand changing environment, who has full information of the past, who discountsfuture payoffs, but who has no prior. We provide a learning algorithm thatperforms almost as well as the best of a given finite number of experts orbenchmark strategies and does so at any point in time, provided the agentis sufficiently patient. The key is to find the appropriate degree of forgettingdistant past. Standard learning algorithms that treat recent and distant pastequally do not have the sequential epsilon optimality property.