154 resultados para Stochastic covariate


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The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

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We shall examine a model, first studied by Brockwell et al. [Adv Appl Probab 14 (1982) 709.], which can be used to describe the longterm behaviour of populations that are subject to catastrophic mortality or emigration events. Populations can suffer dramatic declines when disease, such as an introduced virus, affects the population, or when food shortages occur, due to overgrazing or fluctuations in rainfall. However, perhaps surprisingly, such populations can survive for long periods and, although they may eventually become extinct, they can exhibit an apparently stationary regime. It is useful to be able to model this behaviour. This is particularly true of the ecological examples that motivated the present study, since, in order to properly manage these populations, it is necessary to be able to predict persistence times and to estimate the conditional probability distribution of population size. We shall see that although our model predicts eventual extinction, the time till extinction can be long and the stationary exhibited by these populations over any reasonable time scale can be explained using a quasistationary distribution. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Consider a tandem system of machines separated by infinitely large buffers. The machines process a continuous flow of products, possibly at different speeds. The life and repair times of the machines are assumed to be exponential. We claim that the overflow probability of each buffer has an exponential decay, and provide an algorithm to determine the exact decay rates in terms of the speeds and the failure and repair rates of the machines. These decay rates provide useful qualitative insight into the behavior of the flow line. In the derivation of the algorithm we use the theory of Large Deviations.

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We use a stochastic patch occupancy model of invertebrates in the Mound Springs ecosystem of South Australia to assess the ability of incidence function models to detect environmental impacts on metapopulations. We assume that the probability of colonisation decreases with increasing isolation and the probability of extinction is constant across spring vents. We run the models to quasi-equilibrium, and then impose an impact by increasing the local extinction probability. We sample the output at various times pre- and postimpact, and examine the probability of detecting a significant change in population parameters. The incidence function model approach turns out to have little power to detect environmental impacts on metapopulations with small numbers of patches. (C) 2001 Elsevier Science Ltd. All rights reserved.

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enin et al. (2000) recently introduced the idea of similarity in the context of birth-death processes. This paper examines the extent to which their results can be extended to arbitrary Markov chains. It is proved that, under a variety of conditions, similar chains are strongly similar in a sense which is described, and it is shown that minimal chains are strongly similar if and only if the corresponding transition-rate matrices are strongly similar. A general framework is given for constructing families of strongly similar chains; it permits the construction of all such chains in the irreducible case.

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Resources can be aggregated both within and between patches. In this article, we examine how aggregation at these different scales influences the behavior and performance of foragers. We developed an optimal foraging model of the foraging behavior of the parasitoid wasp Cotesia rubecula parasitizing the larvae of the cabbage butterfly Pieris rapae. The optimal behavior was found using stochastic dynamic programming. The most interesting and novel result is that the effect of resource aggregation within and between patches depends on the degree of aggregation both within and between patches as well as on the local host density in the occupied patch, but lifetime reproductive success depends only on aggregation within patches. Our findings have profound implications for the way in which we measure heterogeneity at different scales and model the response of organisms to spatial heterogeneity.

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This paper develops a general framework for valuing a wide range of derivative securities. Rather than focusing on the stochastic process of the underlying security and developing an instantaneously-riskless hedge portfolio, we focus on the terminal distribution of the underlying security. This enables the derivative security to be valued as the weighted sum of a number of component pieces. The component pieces are simply the different payoffs that the security generates in different states of the world, and they are weighted by the probability of the particular state of the world occurring. A full set of derivations is provided. To illustrate its use, the valuation framework is applied to plain-vanilla call and put options, as well as a range of derivatives including caps, floors, collars, supershares, and digital options.

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This work studied the structure-hepatic disposition relationships for cationic drugs of varying lipophilicity using a single-pass, in situ rat liver preparation. The lipophilicity among the cationic drugs studied in this work is in the following order: diltiazem. propranolol. labetalol. prazosin. antipyrine. atenolol. Parameters characterizing the hepatic distribution and elimination kinetics of the drugs were estimated using the multiple indicator dilution method. The kinetic model used to describe drug transport (the two-phase stochastic model) integrated cytoplasmic binding kinetics and belongs to the class of barrier-limited and space-distributed liver models. Hepatic extraction ratio (E) (0.30-0.92) increased with lipophilicity. The intracellular binding rate constant (k(on)) and the equilibrium amount ratios characterizing the slowly and rapidly equilibrating binding sites (K-S and K-R) increase with the lipophilicity of drug (k(on) : 0.05-0.35 s(-1); K-S : 0.61-16.67; K-R : 0.36-0.95), whereas the intracellular unbinding rate constant (k(off)) decreases with the lipophilicity of drug (0.081-0.021 s(-1)). The partition ratio of influx (k(in)) and efflux rate constant (k(out)), k(in)/k(out), increases with increasing pK(a) value of the drug [from 1.72 for antipyrine (pK(a) = 1.45) to 9.76 for propranolol (pK(a) = 9.45)], the differences in k(in/kout) for the different drugs mainly arising from ion trapping in the mitochondria and lysosomes. The value of intrinsic elimination clearance (CLint), permeation clearance (CLpT), and permeability-surface area product (PS) all increase with the lipophilicity of drug [CLint (ml . min(-1) . g(-1) of liver): 10.08-67.41; CLpT (ml . min(-1) . g(-1) of liver): 10.80-5.35; PS (ml . min(-1) . g(-1) of liver): 14.59-90.54]. It is concluded that cationic drug kinetics in the liver can be modeled using models that integrate the presence of cytoplasmic binding, a hepatocyte barrier, and a vascular transit density function.

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Events during perinatal and early life may influence the incidence of breast cancer in adult life, and some case-control studies suggest that having been breastfed may reduce breast cancer risk. The authors studied this association among premenopausal and postmenopausal women by using data from the two Nurses' Health Studies, the Nurses' Health Study (using data from 1992 to 1996) and the Nurses' Health Study II (using data from 1991 to 1997). A history of being breastfed was self-reported by the study participants. During a total of 695,655 person-years, 1,073 cases of invasive breast cancer were diagnosed. The authors did not observe any important overall association between having been breastfed and the development of breast cancer later in life among premenopausal women (covariate-adjusted relative risk = 0.97, 95% confidence interval (CI): 0.78, 1.20) or postmenopausal women (covariate-adjusted relative risk = 1.12, 95% CI: 0.92, 1.37). No significant trend was observed with increasing duration of breastfeeding. The authors also used data on breastfeeding retrospectively collected from 2,103 mothers of participants of the two Nurses' Health Studies. With the mothers' reports, the covariate-adjusted odds ratio of breast cancer was 1.11 (95% CI: 0.88, 1.39) for women who were breastfed compared with those who were not. Data from these two large cohorts do not support the hypothesis that being breastfed confers protection against subsequent breast cancer.

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We investigate the theory of quantum fluctuations in non-equilibrium systems having large critical fluctuations. This allows us to treat the limits imposed by nonlinearities to quantum squeezing and noise reduction, and also to envisage future tests of quantum theory in regions of macroscopic quantum fluctuations. A long-term objective of this research is to identify suitable physical systems in which macroscopic 'Schrodinger cat'-like behaviour may be observed. We investigate two systems in particular of much current experimental interest, namely the degenerate parametric oscillator near threshold, and the evaporatively cooled (BEC). We compare the results obtained in the positive-P representation, as a fully quantum mechanical calculation, with the truncated Wigner phase space equation, also known as semi-classical theory. We show when these results agree and differ in calculations taken beyond the linearized approximation. In the region where the largest quantum fluctuations and Schrodinger cat-like behaviour might be expected, we find that the quantum predictions correspond very closely to the semi-classical theory. Nature abhors observing a Schrodinger car.

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We obtain the finite-temperature unconditional master equation of the density matrix for two coupled quantum dots (CQD's) when one dot is subjected to a measurement of its electron occupation number using a point contact (PC). To determine how the CQD system state depends on the actual current through the PC device, we use the so-called quantum trajectory method to derive the zero-temperature conditional master equation. We first treat the electron tunneling through the PC barrier as a classical stochastic point process (a quantum-jump model). Then we show explicitly that our results can be extended to the quantum-diffusive limit when the average electron tunneling rate is very large compared to the extra change of the tunneling rate due to the presence of the electron in the dot closer to the PC. We find that in both quantum-jump and quantum-diffusive cases, the conditional dynamics of the CQD system can be described by the stochastic Schrodinger equations for its conditioned state vector if and only if the information carried away from the CQD system by the PC reservoirs can be recovered by the perfect detection of the measurements.

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The present study estimated the population pharmacokinetics of lamotrigine in patients receiving oral lamotrigine therapy with drug concentration monitoring, and determined intersubject and intrasubject variability. A total of 129 patients were analyzed from two clinical sites. Of these, 124 patients provided spare data (198 concentration-time points); nine patients (four from a previous group plus five from the current group) provided rich data (431 points). The population analysis was conducted using P-PHARM (TM) (SIMED Scientific Software, Cedex, France), a nonlinear mixed-effect modeling program. A single exponential elimination model (first-order absorption) with heteroscedastic weighting was used. Apparent clearance (CL/F) and volume of distribution (V/F) were the pharmacokinetic parameters estimated. Covariate analysis was performed to determine which factors explained any of the variability associated with lamotrigine clearance. Population estimates of CL/F and V/F for lamotrigine generated in the final model were 2.14 +/- 0.81 L/h and 78.1 +/- 5.1 L/kg. Intersubject and intrasubject variability for clearance was 38% and 38%, respectively. The covariates of concomitant valproate and phenytoin therapy accounted for 42% of the intersubject variability of clearance. Age, gender, clinic site, and other concomitant antiepileptic drugs did not influence clearance. This study of the population pharmacokinetics of lamotrigine in patients using the drug clinically provides useful data and should lead to better dosage individualization for lamotrigine.