Squared Extrapolation Methods (SQUAREM): A New Class of Simple and Efficient Numerical Schemes for Accelerating the Convergence of the EM Algorithm

We derive a new class of iterative schemes for accelerating the convergence of the EM algorithm, by exploiting the connection between fixed point iterations and extrapolation methods. First, we present a general formulation of one-step iterative schemes, which are obtained by cycling with the extrapolation methods. We, then square the one-step schemes to obtain the new class of methods, which we call SQUAREM. Squaring a one-step iterative scheme is simply applying it twice within each cycle of the extrapolation method. Here we focus on the first order or rank-one extrapolation methods for two reasons, (1) simplicity, and (2) computational efficiency. In particular, we study two first order extrapolation methods, the reduced rank extrapolation (RRE1) and minimal polynomial extrapolation (MPE1). The convergence of the new schemes, both one-step and squared, is non-monotonic with respect to the residual norm. The first order one-step and SQUAREM schemes are linearly convergent, like the EM algorithm but they have a faster rate of convergence. We demonstrate, through five different examples, the effectiveness of the first order SQUAREM schemes, SqRRE1 and SqMPE1, in accelerating the EM algorithm. The SQUAREM schemes are also shown to be vastly superior to their one-step counterparts, RRE1 and MPE1, in terms of computational efficiency. The proposed extrapolation schemes can fail due to the numerical problems of stagnation and near breakdown. We have developed a new hybrid iterative scheme that combines the RRE1 and MPE1 schemes in such a manner that it overcomes both stagnation and near breakdown. The squared first order hybrid scheme, SqHyb1, emerges as the iterative scheme of choice based on our numerical experiments. It combines the fast convergence of the SqMPE1, while avoiding near breakdowns, with the stability of SqRRE1, while avoiding stagnations. The SQUAREM methods can be incorporated very easily into an existing EM algorithm. They only require the basic EM step for their implementation and do not require any other auxiliary quantities such as the complete data log likelihood, and its gradient or hessian. They are an attractive option in problems with a very large number of parameters, and in problems where the statistical model is complex, the EM algorithm is slow and each EM step is computationally demanding.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

Percutaneous coronary interventions in Europe: prevalence, numerical estimates, and projections based on data up to 2004

AIMS: A registry mandated by the European Society of Cardiology collects data on trends in interventional cardiology within Europe. Special interest focuses on relative increases and ratios in new techniques and their distributions across Europe. We report the data through 2004 and give an overview of the development of coronary interventions since the first data collection in 1992. METHODS AND RESULTS: Questionnaires were distributed yearly to delegates of all national societies of cardiology represented in the European Society of Cardiology. The goal was to collect the case numbers of all local institutions and operators. The overall numbers of coronary angiographies increased from 1992 to 2004 from 684 000 to 2 238 000 (from 1250 to 3930 per million inhabitants). The respective numbers for percutaneous coronary interventions (PCIs) and coronary stenting procedures increased from 184 000 to 885 000 (from 335 to 1550) and from 3000 to 770 000 (from 5 to 1350), respectively. Germany was the most active country with 712 000 angiographies (8600), 249 000 angioplasties (3000), and 200 000 stenting procedures (2400) in 2004. The indication has shifted towards acute coronary syndromes, as demonstrated by rising rates of interventions for acute myocardial infarction over the last decade. The procedures are more readily performed and perceived safer, as shown by increasing rate of "ad hoc" PCIs and decreasing need for emergency coronary artery bypass grafting (CABG). In 2004, the use of drug-eluting stents continued to rise. However, an enormous variability is reported with the highest rate in Switzerland (70%). If the rate of progression remains constant until 2010 the projected number of coronary angiographies will be over three million, and the number of PCIs about 1.5 million with a stenting rate of almost 100%. CONCLUSION: Interventional cardiology in Europe is ever expanding. New coronary revascularization procedures, alternative or complementary to balloon angioplasty, have come and gone. Only stenting has stood the test of time and matured to the default technique. Facilitated access to PCI, more complete and earlier detection of coronary artery disease promise continued growth of the procedure despite the uncontested success of prevention.

Semiparametric Theory for Causal Mediation Analysis: efficiency bounds, multiple robustness, and sensitivity analysis

Whilst estimation of the marginal (total) causal effect of a point exposure on an outcome is arguably the most common objective of experimental and observational studies in the health and social sciences, in recent years, investigators have also become increasingly interested in mediation analysis. Specifically, upon establishing a non-null total effect of the exposure, investigators routinely wish to make inferences about the direct (indirect) pathway of the effect of the exposure not through (through) a mediator variable that occurs subsequently to the exposure and prior to the outcome. Although powerful semiparametric methodologies have been developed to analyze observational studies, that produce double robust and highly efficient estimates of the marginal total causal effect, similar methods for mediation analysis are currently lacking. Thus, this paper develops a general semiparametric framework for obtaining inferences about so-called marginal natural direct and indirect causal effects, while appropriately accounting for a large number of pre-exposure confounding factors for the exposure and the mediator variables. Our analytic framework is particularly appealing, because it gives new insights on issues of efficiency and robustness in the context of mediation analysis. In particular, we propose new multiply robust locally efficient estimators of the marginal natural indirect and direct causal effects, and develop a novel double robust sensitivity analysis framework for the assumption of ignorability of the mediator variable.

Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.

Robustness of speckle imaging techniques applied to horizontal imaging scenarios

Atmospheric turbulence near the ground severely limits the quality of imagery acquired over long horizontal paths. In defense, surveillance, and border security applications, there is interest in deploying man-portable, embedded systems incorporating image reconstruction methods to compensate turbulence effects. While many image reconstruction methods have been proposed, their suitability for use in man-portable embedded systems is uncertain. To be effective, these systems must operate over significant variations in turbulence conditions while subject to other variations due to operation by novice users. Systems that meet these requirements and are otherwise designed to be immune to the factors that cause variation in performance are considered robust. In addition robustness in design, the portable nature of these systems implies a preference for systems with a minimum level of computational complexity. Speckle imaging methods have recently been proposed as being well suited for use in man-portable horizontal imagers. In this work, the robustness of speckle imaging methods is established by identifying a subset of design parameters that provide immunity to the expected variations in operating conditions while minimizing the computation time necessary for image recovery. Design parameters are selected by parametric evaluation of system performance as factors external to the system are varied. The precise control necessary for such an evaluation is made possible using image sets of turbulence degraded imagery developed using a novel technique for simulating anisoplanatic image formation over long horizontal paths. System performance is statistically evaluated over multiple reconstruction using the Mean Squared Error (MSE) to evaluate reconstruction quality. In addition to more general design parameters, the relative performance the bispectrum and the Knox-Thompson phase recovery methods is also compared. As an outcome of this work it can be concluded that speckle-imaging techniques are robust to the variation in turbulence conditions and user controlled parameters expected when operating during the day over long horizontal paths. Speckle imaging systems that incorporate 15 or more image frames and 4 estimates of the object phase per reconstruction provide up to 45% reduction in MSE and 68% reduction in the deviation. In addition, Knox-Thompson phase recover method is shown to produce images in half the time required by the bispectrum. The quality of images reconstructed using Knox-Thompson and bispectrum methods are also found to be nearly identical. Finally, it is shown that certain blind image quality metrics can be used in place of the MSE to evaluate quality in field scenarios. Using blind metrics rather depending on user estimates allows for reconstruction quality that differs from the minimum MSE by as little as 1%, significantly reducing the deviation in performance due to user action.

Numerical and granulometric approaches to geophysical granular flows

Volcanic ash clouds can be fed by an upward-directed eruption column (Plinian column) or by elutriation from extensive pyroclastic-flows (coignimbrite cloud). For large-scale eruptions, there is considerable uncertainty about which mechanism is dominant. Here we analyze in a novel way a comprehensive grainsize database for pyroclastic deposits. We demonstrate that the Mount Pinatubo climactic eruption deposits were substantially derived from coignimbrite clouds, and not only by a Plinian cloud as generally thought. Coignimbrite ash-fall deposits are much richer in breathable <10 m ash (5–25 wt%) than pure Plinian ash at most distances from the source volcano. We also show that coignimbrite ash clouds, as at Pinatubo, are expected to be more water rich than Plinian clouds, leading to removal of more HCl prior to stratospheric injection, thereby reducing their atmospheric impact.