947 resultados para Bayesian recursions


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Most of the literature estimating DSGE models for monetary policy analysis ignores fiscal policy and assumes that monetary policy follows a simple rule. In this paper we allow both fiscal and monetary policy to be described by rules and/or optimal policy which are subject to switches over time. We find that US monetary and fiscal policy have often been in conflict, and that it is relatively rare that we observe the benign policy combination of an conservative monetary policy paired with a debt stabilizing fiscal policy. In a series of counterfactuals, a conservative central bank following a time-consistent fiscal policy leader would come close to mimicking the cooperative Ramsey policy. However, if policy makers cannot credibly commit to such a regime, monetary accommodation of the prevailing fiscal regime may actually be welfare improving.

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This paper aims at providing a Bayesian parametric framework to tackle the accessibility problem across space in urban theory. Adopting continuous variables in a probabilistic setting we are able to associate with the distribution density to the Kendall's tau index and replicate the general issues related to the role of proximity in a more general context. In addition, by referring to the Beta and Gamma distribution, we are able to introduce a differentiation feature in each spatial unit without incurring in any a-priori definition of territorial units. We are also providing an empirical application of our theoretical setting to study the density distribution of the population across Massachusetts.

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The Athlete Biological Passport (ABP) is an individual electronic document that collects data regarding a specific athlete that is useful in differentiating between natural physiologic variations of selected biomarkers and deviations caused by artificial manipulations. A subsidiary of the endocrine module of the ABP, that which here is called Athlete Steroidal Passport (ASP), collects data on markers of an altered metabolism of endogenous steroidal hormones measured in urine samples. The ASP aims to identify not only doping with anabolic-androgenic steroids, but also most indirect steroid doping strategies such as doping with estrogen receptor antagonists and aromatase inhibitors. Development of specific markers of steroid doping, use of the athlete's previous measurements to define individual limits, with the athlete becoming his or her own reference, the inclusion of heterogeneous factors such as the UDPglucuronosyltransferase B17 genotype of the athlete, the knowledge of potentially confounding effects such as heavy alcohol consumption, the development of an external quality control system to control analytical uncertainty, and finally the use of Bayesian inferential methods to evaluate the value of indirect evidence have made the ASP a valuable alternative to deter steroid doping in elite sports. The ASP can be used to target athletes for gas chromatography/combustion/ isotope ratio mass spectrometry (GC/C/IRMS) testing, to withdraw temporarily the athlete from competing when an abnormality has been detected, and ultimately to lead to an antidoping infraction if that abnormality cannot be explained by a medical condition. Although the ASP has been developed primarily to ensure fairness in elite sports, its application in endocrinology for clinical purposes is straightforward in an evidence-based medicine paradigm.

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What genotype should the scientist specify for conducting a database search to try to find the source of a low-template-DNA (lt-DNA) trace? When the scientist answers this question, he or she makes a decision. Here, we approach this decision problem from a normative point of view by defining a decision-theoretic framework for answering this question for one locus. This framework combines the probability distribution describing the uncertainty over the trace's donor's possible genotypes with a loss function describing the scientist's preferences concerning false exclusions and false inclusions that may result from the database search. According to this approach, the scientist should choose the genotype designation that minimizes the expected loss. To illustrate the results produced by this approach, we apply it to two hypothetical cases: (1) the case of observing one peak for allele xi on a single electropherogram, and (2) the case of observing one peak for allele xi on one replicate, and a pair of peaks for alleles xi and xj, i ≠ j, on a second replicate. Given that the probabilities of allele drop-out are defined as functions of the observed peak heights, the threshold values marking the turning points when the scientist should switch from one designation to another are derived in terms of the observed peak heights. For each case, sensitivity analyses show the impact of the model's parameters on these threshold values. The results support the conclusion that the procedure should not focus on a single threshold value for making this decision for all alleles, all loci and in all laboratories.

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Background: Retrospective analyses suggest that personalized PK-based dosage might be useful for imatinib, as treatment response correlates with trough concentrations (Cmin) in cancer patients. Our objectives were to improve the interpretation of randomly measured concentrations and to confirm its efficiency before evaluating the clinical usefulness of systematic PK-based dosage in chronic myeloid leukemia patients. Methods and Results: A Bayesian method was validated for the prediction of individual Cmin on the basis of a single random observation, and was applied in a prospective multicenter randomized controlled clinical trial. 28 out of 56 patients were enrolled in the systematic dosage individualization arm and had 44 follow-up visits (their clinical follow-up is ongoing). PK-dose-adjustments were proposed in 39% having predicted Cmin significantly away from the target (1000 ng/ml). Recommendations were taken up by physicians in 57%, patients were considered non-compliant in 27%. Median Cmin at study inclusion was 754 ng/ml and differed significantly from the target (p=0.02, Wilcoxon test). On follow-up, Cmin was 984 ng/ml (p=0.82) in the compliant group. CV decreased from 46% to 27% (p=0.02, F-test). Conclusion: PK-based (Bayesian) dosage adjustment is able to bring individual drug exposure closer to a given therapeutic target. Its influence on therapeutic response remains to be evaluated.

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As the evolutionary significance of hybridization is largely dictated by its extent beyond the first generation, we broadly surveyed patterns of introgression across a sympatric zone of two native poplars (Populus balsamifera, Populus deltoides) in Quebec, Canada within which European exotic Populus nigra and its hybrids have been extensively planted since the 1800s. Single nucleotide polymorphisms (SNPs) that appeared fixed within each species were characterized by DNA-sequencing pools of pure individuals. Thirty-five of these diagnostic SNPs were employed in a high-throughput assay that genotyped 635 trees of different age classes, sampled from 15 sites with various degrees of anthropogenic disturbance. The degree of admixture within sampled trees was then assessed through Bayesian clustering of genotypes. Hybrids were present in seven of the populations, with 2.4% of all sampled trees showing spontaneous admixture. Sites with hybrids were significantly more disturbed than pure stands, while hybrids comprised both immature juveniles and trees of reproductive age. All three possible F1s were detected. Advanced-generation hybrids were consistently biased towards P. balsamifera regardless of whether hybridization had occurred with P. deltoides or P. nigra. Gene exchange between P. deltoides and P. nigra was not detected beyond the F1 generation; however, detection of a trihybrid demonstrates that even this apparent reproductive isolation does not necessarily result in an evolutionary dead end. Collectively, results demonstrate the natural fertility of hybrid poplars and suggest that introduced genes could potentially affect the genetic integrity of native trees, similar to that arising from introgression between natives.

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We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

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When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

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Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

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Genetic evaluation using animal models or pedigree-based models generally assume only autosomal inheritance. Bayesian animal models provide a flexible framework for genetic evaluation, and we show how the model readily can accommodate situations where the trait of interest is influenced by both autosomal and sex-linked inheritance. This allows for simultaneous calculation of autosomal and sex-chromosomal additive genetic effects. Inferences were performed using integrated nested Laplace approximations (INLA), a nonsampling-based Bayesian inference methodology. We provide a detailed description of how to calculate the inverse of the X- or Z-chromosomal additive genetic relationship matrix, needed for inference. The case study of eumelanic spot diameter in a Swiss barn owl (Tyto alba) population shows that this trait is substantially influenced by variation in genes on the Z-chromosome (sigma(2)(z) = 0.2719 and sigma(2)(a) = 0.4405). Further, a simulation study for this study system shows that the animal model accounting for both autosomal and sex-chromosome-linked inheritance is identifiable, that is, the two effects can be distinguished, and provides accurate inference on the variance components.

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In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

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Background: It is suggested that a low dose of valganciclovir can be equally effective than a standard dose for cytomegalovirus (CMV) prophylaxis after kidney transplantation. The aim of our study was to determine the ganciclovir exposure observed under a routine daily dosage of 450 mg valganciclovir in kidney transplant recipients with a wide range of renal function. Methods: In this prospective study, kidney transplant recipients with a GFR MDRD above 25 mL/min at risk for CMV (donor or recipient seropositive for CMV) received a dose of valganciclovir (450 mg daily) prophylaxis for 3 months. Ganciclovir levels at trough (Ctrough) and at peak (C3h) were measured monthly. Ganciclovir exposure (AUC0-24) was estimated using Bayesian non-linear mixed-effect modelling (NONMEM) and compared between 3 groups of patients according to their kidney function: GFRMDRD 26-39 mL/min (Group 1), GFRMDRD 40-59 mL/min (Group 2) and GFRMDRD 60-90 mL/min (Group 3). CMV DNAemia was assessed during and after prophylaxis using PCR. Results: Thirty-six patients received 450 mg daily of valganciclovir for 3 months. Median ganciclovir C3h was 3.9 mg/L (range: 1.3-7.1) and Ctrough was 0.4 mg/L (range 0.1-2.7). Median (range) AUC0-24 of ganciclovir was 59.3 mg.h/L (39.0-85.3) in Group 1 patients, 35.8 mg.h/L (24.9-55.8) in Group 2 patients and 29.6 mg.h/L (22.0- 43.2) in Group 3 patients (p<0.001). Anemia was more common in Group 1 patients compared to patients on the other groups (p=0.01). No differences in other adverse events according to ganciclovir exposure were observed. CMV DNAemia was not detected during prophylaxis. After discontinuing prophylaxis, CMV DNAemia was seen in 8/34 patients (23.5%) and 4/36 patients (11%) developed CMV disease. Conclusion: A routine dosage of valganciclovir achieved plasma levels of ganciclovir in patients with GFR>60 mL/min similar to those previously reported using oral ganciclovir. A daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.

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This paper addresses the issue of policy evaluation in a context in which policymakers are uncertain about the effects of oil prices on economic performance. I consider models of the economy inspired by Solow (1980), Blanchard and Gali (2007), Kim and Loungani (1992) and Hamilton (1983, 2005), which incorporate different assumptions on the channels through which oil prices have an impact on economic activity. I first study the characteristics of the model space and I analyze the likelihood of the different specifications. I show that the existence of plausible alternative representations of the economy forces the policymaker to face the problem of model uncertainty. Then, I use the Bayesian approach proposed by Brock, Durlauf and West (2003, 2007) and the minimax approach developed by Hansen and Sargent (2008) to integrate this form of uncertainty into policy evaluation. I find that, in the environment under analysis, the standard Taylor rule is outperformed under a number of criteria by alternative simple rules in which policymakers introduce persistence in the policy instrument and respond to changes in the real price of oil.

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Objectives: Imatinib has been increasingly proposed for therapeutic drug monitoring (TDM), as trough concentrations (Cmin) correlate with response rates in CML patients. This analysis aimed to evaluate the impact of imatinib exposure on optimal molecular response rates in a large European cohort of patients followed by centralized TDM.¦Methods: Sequential PK/PD analysis was performed in NONMEM 7 on 2230 plasma (PK) samples obtained along with molecular response (PD) data from 1299 CML patients. Model-based individual Bayesian estimates of exposure, parameterized as to initial dose adjusted and log-normalized Cmin (log-Cmin) or clearance (CL), were investigated as potential predictors of optimal molecular response, while accounting for time under treatment (stratified at 3 years), gender, CML phase, age, potentially interacting comedication, and TDM frequency. PK/PD analysis used mixed-effect logistic regression (iterative two-stage method) to account for intra-patient correlation.¦Results: In univariate analyses, CL, log-Cmin, time under treatment, TDM frequency, gender (all p<0.01) and CML phase (p=0.02) were significant predictors of the outcome. In multivariate analyses, all but log-Cmin remained significant (p<0.05). Our model estimates a 54.1% probability of optimal molecular response in a female patient with a median CL of 14.4 L/h, increasing by 4.7% with a 35% decrease in CL (percentile 10 of CL distribution), and decreasing by 6% with a 45% increased CL (percentile 90), respectively. Male patients were less likely than female to be in optimal response (odds ratio: 0.62, p<0.001), with an estimated probability of 42.3%.¦Conclusions: Beyond CML phase and time on treatment, expectedly correlated to the outcome, an effect of initial imatinib exposure on the probability of achieving optimal molecular response was confirmed in field-conditions by this multivariate analysis. Interestingly, male patients had a higher risk of suboptimal response, which might not exclusively derive from their 18.5% higher CL, but also from reported lower adherence to the treatment. A prospective longitudinal study would be desirable to confirm the clinical importance of identified covariates and to exclude biases possibly affecting this observational survey.