A Bayesian Analysis of Unobserved Component Models Using Ox

This article details a Bayesian analysis of the Nile river flow data, using a similar state space model as other articles in this volume. For this data set, Metropolis-Hastings and Gibbs sampling algorithms are implemented in the programming language Ox. These Markov chain Monte Carlo methods only provide output conditioned upon the full data set. For filtered output, conditioning only on past observations, the particle filter is introduced. The sampling methods are flexible, and this advantage is used to extend the model to incorporate a stochastic volatility process. The volatility changes both in the Nile data and also in daily S&P 500 return data are investigated. The posterior density of parameters and states is found to provide information on which elements of the model are easily identifiable, and which elements are estimated with less precision.

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algoritms for this type of model are ineffective, but that this problem can be removed by reparameterising the model. We illustrate our results on an example from financial economics and one from the nonparametric regression literature. We also develop an effective particle filter for this model which is useful to assess the fit of the model.Markov chain Monte Carlo, particle filter, cubic spline, state space form, stochastic volatility.

Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain efficient estimates of the parameters using a monthly data-set of core inflation for which we consider different subsamples of varying size. Based on the new modelling framework and the associated estimation technique, we find remarkable changes in the variance, in the order of integration, in the short memory characteristics and in the volatility of volatility

Daily Exchange Rate Behaviour and Hedging of Currency Risk

Exchange rates typically exhibit time-varying patterns in both means and variances. The histograms of such series indicate heavy tails. In this paper we construct models which enable a decision-maker to analyze the implications of such time series patterns for currency risk management. Our approach is Bayesian where extensive use is made of Markov chain Monte Carlo methods. The effects of several model characteristics (unit roots, GARCH, stochastic volatility, heavy tailed disturbance densities) are investigated in relation to the hedging decision strategies. Consequently, we can make a distinction between statistical relevance of model specifications, and the economic consequences from a risk management point of view. The empirical results suggest that econometric modelling of heavy tails and time-varying means and variances pays off compared to a efficient markets model. The different ways to measure persistence and changing volatilities appear to strongly influence the hedging decision the investor faces.

Study of Zγ events and limits on anomalous ZZγ and Zγγ couplings in pp̄ collisions at s=1.96TeV

We present a measurement of the Zγ production cross section and limits on anomalous ZZγ and Zγγ couplings for form-factor scales of Λ=750 and 1000 GeV. The measurement is based on 138 (152) candidates in the eeγ (μμγ) final state using 320(290)pb-1 of pp̄ collisions at s=1.96TeV. The 95% C.L. limits on real and imaginary parts of individual anomalous couplings are |h10,30Z|<0.23, |h20,40Z|<0.020, |h10,30γ|<0.23, and |h20,40γ|<0.019 for Λ=1000GeV. © 2005 The American Physical Society

Factors influencing the decision to start renal replacement therapy: results of a survey among European nephrologists

Background: Little is known about the criteria nephrologists use in the decision of when to start renal replacement therapy (RRT) in early referred adult patients. We evaluated opinions of European nephrologists on the decision for when to start RRT. Study Design: European web-based survey. Predictors: Patient presentations described as uncomplicated patients, patients with unfavorable clinical and unfavorable social conditions, or patients with specific clinical, social, and logistical factors. Setting & Participants: Nephrologists from 11 European countries. Outcomes & Measurements: We studied opinions of European nephrologists about the influence of clinical, social, and logistical factors on decision making regarding when to start RRT, reflecting practices in place in 2009. Questions included target levels of kidney function at the start of RRT and factors accelerating or postponing RRT initiation. Using linear regression, we studied determinants of target estimated glomerular filtration rate (eGFR) at the start of RRT. Results: We received 433 completed surveys. The median target eGFR selected to start RRT in uncomplicated patients was 10.0 (25th-75th percentile, 8.0-10.0) mL/min/1.73 m(2). Level of excretory kidney function was considered the most important factor in decision making regarding uncomplicated patients (selected by 54% of respondents); in patients with unfavorable clinical versus social conditions, this factor was selected by 24% versus 32%, respectively. Acute clinical factors such as life-threatening hyperkalemia refractory to medical therapy (100%) and uremic pericarditis (98%) elicited a preference for an immediate start, whereas patient preference (69%) and vascular dementia (66%) postponed the start. Higher target eGFRs were reported by respondents from high-versus low-RRT-incidence countries (10.4 [95% CI, 9.9-10.9] vs 9.1 mL/min/1.73 m(2)) and from for-profit versus not-for-profit centers (10.1 [95% CI, 9.5-10.7] vs 9.5 mL/min/1.73 m(2)). Limitations: We were unable to calculate the exact response rate and examined opinions rather than practice for 433 nephrologists. Conclusions: Only for uncomplicated patients did half the nephrologists consider excretory kidney function as the most important factor. Future studies should assess the weight of each factor affecting decision making. Am J Kidney Dis. 60(6): 940-948. (C) 2012 by the National Kidney Foundation, In

Search for right-handed W bosons in top quark decay

We present a measurement of the fraction f+ of right-handed W bosons produced in top quark decays, based on a candidate sample of $t\bar{t}$ events in the lepton+jets decay mode. These data correspond to an integrated luminosity of 230pb^-1, collected by the DO detector at the Fermilab Tevatron $p\bar{p}$ Collider at sqrt(s)=1.96 TeV. We use a constrained fit to reconstruct the kinematics of the $t\bar{t}$ and decay products, which allows for the measurement of the leptonic decay angle $\theta^*$ for each event. By comparing the $\cos\theta^*$ distribution from the data with those for the expected background and signal for various values of f+, we find f+=0.00+-0.13(stat)+-0.07(syst). This measurement is consistent with the standard model prediction of f+=3.6x10^-4.Comment: Submitted to Physical Review D Rapid Communications 7 pages, 3 figure

Measurement of Semileptonic Branching Fractions of B Mesons to Narrow D** States

Using the data accumulated in 2002-2004 with the DO detector in proton-antiproton collisions at the Fermilab Tevatron collider with centre-of-mass energy 1.96 TeV, the branching fractions of the decays B -> \bar{D}_1^0(2420) \mu^+ \nu_\mu X and B -> \bar{D}_2^{*0}(2460) \mu^+ \nu_\mu X and their ratio have been measured: BR(\bar{b}->B) \cdot BR(B-> \bar{D}_1^0 \mu^+ \nu_\mu X) \cdot BR(\bar{D}_1^0 -> D*- pi+) = (0.087+-0.007(stat)+-0.014(syst))%; BR(\bar{b}->B)\cdot BR(B->D_2^{*0} \mu^+ \nu_\mu X) \cdot BR(\bar{D}_2^{*0} -> D*- \pi^+) = (0.035+-0.007(stat)+-0.008(syst))%; and (BR(B -> \bar{D}_2^{*0} \mu^+ \nu_\mu X)BR(D2*0->D*- pi+)) / (BR(B -> \bar{D}_1^{0} \mu^+ \nu_\mu X)\cdot BR(\bar{D}_1^{0}->D*- \pi^+)) = 0.39+-0.09(stat)+-0.12(syst), where the charge conjugated states are always implied.Comment: submitted to Phys. Rev. Let