Analysis of trigonometric implicit Runge-Kutta methods

Using generalized collocation techniques based on fitting functions that are trigonometric (rather than algebraic as in classical integrators), we develop a new class of multistage, one-step, variable stepsize, and variable coefficients implicit Runge-Kutta methods to solve oscillatory ODE problems. The coefficients of the methods are functions of the frequency and the stepsize. We refer to this class as trigonometric implicit Runge-Kutta (TIRK) methods. They integrate an equation exactly if its solution is a trigonometric polynomial with a known frequency. We characterize the order and A-stability of the methods and establish results similar to that of classical algebraic collocation RK methods. (c) 2006 Elsevier B.V. All rights reserved.

On functionally-fitted Runge-Kutta methods

Functionally-fitted methods are generalizations of collocation techniques to integrate an equation exactly if its solution is a linear combination of a chosen set of basis functions. When these basis functions are chosen as the power functions, we recover classical algebraic collocation methods. This paper shows that functionally-fitted methods can be derived with less restrictive conditions than previously stated in the literature, and that other related results can be derived in a much more elegant way. The novelty in our approach is to fully retain the collocation framework without reverting back into derivations based on cumbersome Taylor series expansions.

Capturing the complexity of women's experiences: A mixed-method approach to studying incontinence in older women

Capturing the voices of women when the issue is of a sensitive nature has been a major concern of feminist researchers. It has often been argued that interpretive methods are the most appropriate way to collect such information, but there are other appropriate ways to approach the design of research. This article explores the use of a mixed-method approach to collect data on incontinence in older women and argues for the use of a variety of creative approaches to collect and analyze data.

Hydrothermal Synthesis of Layered Double Hydroxides (LDHs) from Mixed MgO and Al2O3: LDH Formation Mechanism

The formation of MgA1 layered double hydroxide (LDH) from physically mixed MgO and Al2O3 oxides upon hydrothermal treatment has been extensively investigated, and a formation mechanism has been proposed. We observed that the formation of LDH from the oxide mixture occurs upon heating at 110 degreesC. In general, LDH is the major component while the minor phases are mainly determined by the initial pH of the oxide suspension as well as the MgO/Al2O3 ratio. The neutrality in the initial suspension results in a minor Mg(OH)(2) as the impure phase, while the alkalinity in the suspension keeps some MgO unreacted throughout the whole hydrothermal treatment. We suggest that MgO and Al2O3 be hydrated into Mg(OH)(2) and Al(OH)(3), respectively, in the initial stage for all samples. We further Suggest that in the neutral condition Mg(OH)2 be quickly dissociated to Mg2+ and OH- which then deposit on the surface of Al(OH)(3)/Al2O3 to form a M-Al pre-LDH material. Al(OH)(4)(-), ionized from Al(OH)(3) in the basic solution, deposits on the surface of Mg(OH)(2)/MgO to result in a similar MgAl pre-LDH material. Such a pre-LDH material is then well crystallized upon continuous heating via the diffusion of metal ions in the solid lattice. Such a dissociation-deposition-diffusion mechanism via two pathways has been supported by the phase composition, morphological features of crystallites, and [Mg]/[Al] ratios on the crystallite surface. and presumably applied to the general formation of LDHs with various synthetic methods. Such as coprecipitation, homogeneous preparation, and reconstruction.

Large scale experiments on gravel and mixed beaches: Experimental procedure, data documentation and initial results

This paper provides information on the experimental set-up, data collection methods and results to date for the project Large scale modelling of coarse grained beaches, undertaken at the Large Wave Channel (GWK) of FZK in Hannover by an international group of researchers in Spring 2002. The main objective of the experiments was to provide full scale measurements of cross-shore processes on gravel and mixed beaches for the verification and further development of cross-shore numerical models of gravel and mixed sediment beaches. Identical random and regular wave tests were undertaken for a gravel beach and a mixed sand/gravel beach set up in the flume. Measurements included profile development, water surface elevation along the flume, internal pressures in the swash zone, piezometric head levels within the beach, run-up, flow velocities in the surf-zone and sediment size distributions. The purpose of the paper is to present to the scientific community the experimental procedure, a summary of the data collected, some initial results, as well as a brief outline of the on-going research being carried out with the data by different research groups. The experimental data is available to all the scientific community following submission of a statement of objectives, specification of data requirements and an agreement to abide with the GWK and EU protocols. (C) 2005 Elsevier B.V. All rights reserved.

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.