909 resultados para Discrete-time Dynamics


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„Risikomaße in der Finanzmathematik“ Der Value-at -Risk (VaR) ist ein Risikomaß, dessen Verwendung von der Bankenaufsicht gefordert wird. Der Vorteil des VaR liegt – als Quantil der Ertrags- oder Verlustverteilung - vor allem in seiner einfachen Interpretierbarkeit. Nachteilig ist, dass der linke Rand der Wahrscheinlichkeitsverteilung nicht beachtet wird. Darüber hinaus ist die Berechnung des VaR schwierig, da Quantile nicht additiv sind. Der größte Nachteil des VaR ist in der fehlenden Subadditivität zu sehen. Deswegen werden Alternativen wie Expected Shortfall untersucht. In dieser Arbeit werden zunächst finanzielle Risikomaße eingeführt und einige ihre grundlegenden Eigenschaften festgehalten. Wir beschäftigen uns mit verschiedenen parametrischen und nichtparametrischen Methoden zur Ermittlung des VaR, unter anderen mit ihren Vorteilen und Nachteilen. Des Weiteren beschäftigen wir uns mit parametrischen und nichtparametrischen Schätzern vom VaR in diskreter Zeit. Wir stellen Portfoliooptimierungsprobleme im Black Scholes Modell mit beschränktem VaR und mit beschränkter Varianz vor. Der Vorteil des erstens Ansatzes gegenüber dem zweiten wird hier erläutert. Wir lösen Nutzenoptimierungsprobleme in Bezug auf das Endvermögen mit beschränktem VaR und mit beschränkter Varianz. VaR sagt nichts über den darüber hinausgehenden Verlust aus, während dieser von Expected Shortfall berücksichtigt wird. Deswegen verwenden wir hier den Expected Shortfall anstelle des von Emmer, Korn und Klüppelberg (2001) betrachteten Risikomaßes VaR für die Optimierung des Portfolios im Black Scholes Modell.

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Wir betrachten einen zeitlich inhomogenen Diffusionsprozess, der durch eine stochastische Differentialgleichung gegeben wird, deren Driftterm ein deterministisches T-periodisches Signal beinhaltet, dessen Periodizität bekannt ist. Dieses Signal sei in einem Besovraum enthalten. Wir schätzen es mit Hilfe eines nichtparametrischen Waveletschätzers. Unser Schätzer ist von einem Wavelet-Dichteschätzer mit Thresholding inspiriert, der 1996 in einem klassischen iid-Modell von Donoho, Johnstone, Kerkyacharian und Picard konstruiert wurde. Unter gewissen Ergodizitätsvoraussetzungen an den Prozess können wir nichtparametrische Konvergenzraten angegeben, die bis auf einen logarithmischen Term den Raten im klassischen iid-Fall entsprechen. Diese Raten werden mit Hilfe von Orakel-Ungleichungen gezeigt, die auf Ergebnissen über Markovketten in diskreter Zeit von Clémencon, 2001, beruhen. Außerdem betrachten wir einen technisch einfacheren Spezialfall und zeigen einige Computersimulationen dieses Schätzers.

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Although associated with adverse outcomes in other cardiopulmonary diseases, limited evidence exists on the prognostic value of anaemia in patients with acute pulmonary embolism (PE). We sought to examine the associations between anaemia and mortality and length of hospital stay in patients with PE. We evaluated 14,276 patients with a primary diagnosis of PE from 186 hospitals in Pennsylvania, USA. We used random-intercept logistic regression to assess the association between anaemia at the time of presentation and 30-day mortality and discrete-time logistic hazard models to assess the association between anaemia and time to hospital discharge, adjusting for patient (age, gender, race, insurance type, clinical and laboratory variables) and hospital (region, size, teaching status) factors. Anaemia was present in 38.7% of patients at admission. Patients with anaemia had a higher 30-day mortality (13.7% vs. 6.3%; p <0.001) and a longer length of stay (geometric mean, 6.9 vs. 6.6 days; p <0.001) compared to patients without anaemia. In multivariable analyses, anaemia remained associated with an increased odds of death (OR 1.82, 95% CI: 1.60-2.06) and a decreased odds of discharge (OR 0.85, 95% CI: 0.82-0.89). Anaemia is very common in patients presenting with PE and is independently associated with an increased short-term mortality and length of stay.

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OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

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This paper treats the problem of setting the inventory level and optimizing the buffer allocation of closed-loop flow lines operating under the constant-work-in-process (CONWIP) protocol. We solve a very large but simple linear program that models an entire simulation run of a closed-loop flow line in discrete time to determine a production rate estimate of the system. This approach introduced in Helber, Schimmelpfeng, Stolletz, and Lagershausen (2011) for open flow lines with limited buffer capacities is extended to closed-loop CONWIP flow lines. Via this method, both the CONWIP level and the buffer allocation can be optimized simultaneously. The first part of a numerical study deals with the accuracy of the method. In the second part, we focus on the relationship between the CONWIP inventory level and the short-term profit. The accuracy of the method turns out to be best for such configurations that maximize production rate and/or short-term profit.

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This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model. We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose. The design based on a time-to-DLT model uses patients' DLT information over multiple treatment cycles in estimating the probability of DLT at the end of treatment cycle 1. Dose-escalation decisions are made whenever a cycle-1 DLT occurs, or two months after the previous check point. Compared to the design based on a logistic regression model, the new design shows more safety benefits for trials in which more late-onset toxicities are expected. As a trade-off, the new design requires more patients on average. The design based on a discrete-time multi-state (DTMS) model has three important attributes: (1) Toxicities are categorized over a distribution of severity levels, (2) Early toxicity may inform dose escalation, and (3) No suspension is required between accrual cohorts. The proposed model accounts for the difference in the importance of the toxicity severity levels and for transitions between toxicity levels. We compare the operating characteristics of the proposed design with those from a similar design based on a fully-evaluated model that directly models the maximum observed toxicity level within the patients' entire assessment window. We describe settings in which, under comparable power, the proposed design shortens the trial. The proposed design offers more benefit compared to the alternative design as patient accrual becomes slower.

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A quantum simulator of U(1) lattice gauge theories can be implemented with superconducting circuits. This allows the investigation of confined and deconfined phases in quantum link models, and of valence bond solid and spin liquid phases in quantum dimer models. Fractionalized confining strings and the real-time dynamics of quantum phase transitions are accessible as well. Here we show how state-of-the-art superconducting technology allows us to simulate these phenomena in relatively small circuit lattices. By exploiting the strong non-linear couplings between quantized excitations emerging when superconducting qubits are coupled, we show how to engineer gauge invariant Hamiltonians, including ring-exchange and four-body Ising interactions. We demonstrate that, despite decoherence and disorder effects, minimal circuit instances allow us to investigate properties such as the dynamics of electric flux strings, signaling confinement in gauge invariant field theories. The experimental realization of these models in larger superconducting circuits could address open questions beyond current computational capability.

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PURPOSE Based on a nation-wide database, this study analysed the influence of methotrexate (MTX), TNF inhibitors and a combination of the two on uveitis occurrence in JIA patients. METHODS Data from the National Paediatric Rheumatological Database in Germany were used in this study. Between 2002 and 2013, data from JIA patients were annually documented at the participating paediatric rheumatological sites. Patients with JIA disease duration of less than 12 months at initial documentation and ≥2 years of follow-up were included in this study. The impact of anti-inflammatory treatment on the occurrence of uveitis was evaluated by discrete-time survival analysis. RESULTS A total of 3,512 JIA patients (mean age 8.3±4.8 years, female 65.7%, ANA-positive 53.2%, mean age at arthritis onset 7.8±4.8 years) fulfilled the inclusion criteria. Mean total follow-up time was 3.6±2.4 years. Uveitis developed in a total of 180 patients (5.1%) within one year after arthritis onset. Uveitis onset after the first year was observed in another 251 patients (7.1%). DMARD treatment in the year before uveitis onset significantly reduced the risk for uveitis: MTX (HR 0.63, p=0.022), TNF inhibitors (HR 0.56, p<0.001) and a combination of the two (HR 0.10, p<0.001). Patients treated with MTX within the first year of JIA had an even a lower uveitis risk (HR 0.29, p<0.001). CONCLUSION The use of DMARDs in JIA patients significantly reduced the risk for uveitis onset. Early MTX use within the first year of disease and the combination of MTX with a TNF inhibitor had the highest protective effect. This article is protected by copyright. All rights reserved.

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The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^

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Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

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Results of 40Ar-39Ar Ar dating constrain the age of the submerged volcanic succession, part of the seaward-dipping reflector sequence of the Southeast Greenland volcanic rifted margin, recovered during Leg 163. At the 63ºN drilling transect, the fully normally magnetized volcanic units at Holes 989B (Unit 1) and 990A (Units 1 and 2) are dated at 57.1 ± 1.3 Ma and 55.6 ± 0.6 Ma, respectively. This correlates with a common magnetochron, C25n. The underlying, reversely magnetized lavas at Hole 990A (Units 3-13) yield an average age of 55.8 ± 0.7 Ma and may correlate with C25r. The argon data, however, are also consistent with eruption of the lavas at Site 990 during the very earliest portion of C24. If so, the normally polarized units have to be correlated to a cryptochron (e.g., C24r-11 at ~55.57 Ma). The lavas at Holes 989B and 990A have typical oceanic compositions, implying that final plate separation between Greenland and northwest Europe took place at ~56 Ma. The age for Hole 989B lava is younger than expected from the seismic interpretations, posing questions about the structural evolution of the margin. An age of 49.6 ± 0.2 Ma for the basaltic lava at Site 988 (~66ºN) points to the importance of postbreakup tholeiitic magmatism at the rifted margin. Together with results from Leg 152, a virtually complete time frame for ~12 m.y. of pre-, syn-, and postbreakup volcanism during rifted margin evolution in Southeast Greenland can now be assembled. This time frame includes continental type volcanism at ~61-60 Ma, synbreakup volcanism beginning at ~57 Ma, and postbreakup volcanism at ~49.6 Ma. These discrete time windows coincide with distinct periods of tholeiitic magmatism from the onshore East Greenland Tertiary Igneous Province and is consistent with discrete mantle-melting events triggered by plume arrival (~61-60 Ma) under central Greenland, continental breakup (~57-54 Ma), and passage of the plume axis beneath the East Greenland rifted margin after breakup (~50-49 Ma), respectively.

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We present a reconstruction of El Niño Southern Oscillation (ENSO) variability spanning the Medieval Climate Anomaly (MCA, A.D. 800-1300) and the Little Ice Age (LIA, A.D. 1500-1850). Changes in ENSO are estimated by comparing the spread and symmetry of d18O values of individual specimens of the thermocline-dwelling planktonic foraminifer Pulleniatina obliquiloculata extracted from discrete time horizons of a sediment core collected in the Sulawesi Sea, at the edge of the western tropical Pacific warm pool. The spread of individual d18O values is interpreted to be a measure of the strength of both phases of ENSO while the symmetry of the d18O distributions is used to evaluate the relative strength/frequency of El Niño and La Niña events. In contrast to previous studies, we use robust and resistant statistics to quantify the spread and symmetry of the d18O distributions; an approach motivated by the relatively small sample size and the presence of outliers. Furthermore, we use a pseudo-proxy approach to investigate the effects of the different paleo-environmental factors on the statistics of the d18O distributions, which could bias the paleo-ENSO reconstruction. We find no systematic difference in the magnitude/strength of ENSO during the Northern Hemisphere MCA or LIA. However, our results suggest that ENSO during the MCA was skewed toward stronger/more frequent La Niña than El Niño, an observation consistent with the medieval megadroughts documented from sites in western North America.

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A late Albian-early Cenomanian record (~103.3 to 99.0 Ma), including organic-rich deposits and a d13C increase associated with oceanic anoxic event 1d (OAE 1d), is described from Ocean Drilling Program sites 1050 and 1052 in the subtropical Atlantic. Foraminifera are well preserved at these sites. Paleotemperatures estimated from benthic d18O values average ~14°C for middle bathyal Site 1050 and ~17°C for upper bathyal Site 1052, whereas surface temperatures are estimated to have ranged from 26°C to 31°C at both sites. Among planktonic foraminifera, there is a steady balance of speciation and extinction with no discrete time of major faunal turnover. OAE 1d is recognized on the basis of a 1.2 per mill d13C increase (~100.0-99.6 Ma), which is similar in age and magnitude to d13C excursions documented in the North Atlantic and western Tethys. Organic-rich "black shales" are present throughout the studied interval at both sites. However, deposition of individual black shale beds was not synchronous between sites, and most of the black shale was deposited before the OAE 1d d13C increase. A similar pattern is observed at the other sites where OAE 1d has been recognized indicating that the site(s) of excess organic carbon burial that could have caused the d13C increase has (have) yet to be found. Our findings add weight to the view that OAEs should be chemostratigraphically (d13C) rather than lithostratigraphically defined.

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This paper examines the duration of intermediate goods imports and its determinants for Japanese affiliates in China. Our estimations, using a unique parent-affiliate-transaction matched panel dataset for a discrete-time hazard model over the 2000–2006 period, reveal that products with a higher upstreamness index, differentiated goods, and goods traded under processing trade are less likely to be substituted with local procurement. Firms located in more agglomerated regions with more foreign affiliates tend to shorten the duration of imports from the home country. For parent-firm characteristics, multinational enterprises that have many foreign affiliates or longer foreign production experience import intermediate goods for a longer duration.

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The purpose of this paper is to increase current empirical evidence on the relevance of real options for explaining firm investment decisions in oligopolistic markets. We study an actual investment case in the Spanish mobile telephony industry, the entrant in the market of a new operator, Yoigo. We analyze the option to abandon in order to show the relevance of the possibility of selling the company in an oligopolistic market where competitors are not allowed free entrance. The NPV (net present value) of the new entrant is calculated as a starting point. Then, based on the general approach proposed by Copeland and Antikarov (2001), a binomial tree is used to model managerial flexibility in discrete time periods, and value the option to abandon. The strike price of the option is calculated based on incremental EBITDA margins due to selling customers or merging with a competitor.