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Empirical Process (empirical + process)
Selected AbstractsThe attitudes to ageing questionnaire (AAQ): development and psychometric propertiesINTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY, Issue 4 2007K. Laidlaw Abstract Objective This paper describes the development of the Attitudes to Ageing Questionnaire (AAQ) which is a self-report measure with which older people themselves can express their attitudes to the process of ageing. Method The development of the AAQ followed a coherent, logical and empirical process taking full account of relevant gerontological knowledge and modern and classical psychometric analytical methods. Pilot testing with 1,356 participants from 15 centres worldwide refined the scale and provided the basis for a field test. A total of 5,566 participants from 20 centres worldwide contributed to the further development of this new scale with the derivation involving both classical and modern psychometric methods. Results The result is a 24-item cross-cultural attitudes to ageing questionnaire consisting of a three-factor model encompassing psychological growth, psychosocial loss, and physical change. The three-factor model suggests a way of conceptualizing and measuring successful ageing in individuals. Conclusions The AAQ provides researchers, clinicians and policy makers with a unique scale to measure the impact of successful ageing interventions. It also provides a vehicle for the measurement of how individuals age across cultures and under different economic, political and social circumstances. Copyright © 2006 John Wiley & Sons, Ltd. [source] On residual empirical processes of GARCH-SM models: application to conditional symmetry testsJOURNAL OF TIME SERIES ANALYSIS, Issue 5 2008Naâmane Laïb 62M10; 62G10 Abstract., Considering the generalized autoregressive conditionally heteroskedastic with stochastic mean (GARCH-SM) model, we establish in this article the consistency and the weak representation of a functional of its residual empirical process. Based on this result, a symmetry test for GARCH-SM model is developed. Simulations are given to show the asymptotic behaviour and normality of the test statistic. [source] Minimum , -divergence estimation for arch modelsJOURNAL OF TIME SERIES ANALYSIS, Issue 1 2006S. Ajay Chandra Abstract., This paper considers a minimum , -divergence estimation for a class of ARCH(p) models. For these models with unknown volatility parameters, the exact form of the innovation density is supposed to be unknown in detail but is thought to be close to members of some parametric family. To approximate such a density, we first construct an estimator for the unknown volatility parameters using the conditional least squares estimator given by Tjøstheim [Stochastic processes and their applications (1986) Vol. 21, pp. 251,273]. Then, a nonparametric kernel density estimator is constructed for the innovation density based on the estimated residuals. Using techniques of the minimum Hellinger distance estimation for stochastic models and residual empirical process from an ARCH(p) model given by Beran [Annals of Statistics (1977) Vol. 5, pp. 445,463] and Lee and Taniguchi [Statistica Sinica (2005) Vol. 15, pp. 215,234] respectively, it is shown that the proposed estimator is consistent and asymptotically normal. Moreover, a robustness measure for the score of the estimator is introduced. The asymptotic efficiency and robustness of the estimator are illustrated by simulations. The proposed estimator is also applied to daily stock returns of Dell Corporation. [source] Some notes on poisson limits for empirical point processesTHE CANADIAN JOURNAL OF STATISTICS, Issue 3 2009André Dabrowski Abstract The authors define the scaled empirical point process. They obtain the weak limit of these point processes through a novel use of a dimension-free method based on the convergence of compensators of multiparameter martingales. The method extends previous results in several directions. They obtain limits at points where the density may be zero, but has regular variation. The joint limit of the empirical process evaluated at distinct points is given by independent Poisson processes. They provide applications both to nearest-neighbour density estimation in high dimensions, and to the asymptotic behaviour of multivariate extremes such as those arising from bivariate normal copulas. The Canadian Journal of Statistics 37: 347,360; 2009 © 2009 Statistical Society of Canada Les auteurs définissent un processus ponctuel empirique normalisé. Ils obtiennent une limite faible de ces processus ponctuels grâce à l'utilisation novatrice d'une méthode indépendante de la dimension basée sur la convergence des compensateurs de martingales à plusieurs paramètres. La méthode généralise des résultats précédents de différentes façons. Ils obtiennent des limites à des points où la densité peut être égale à 0, mais qui est à variation régulière. La limite conjointe du processus empirique évalué à des points distincts est représentée par des processus de Poisson indépendants. Les auteurs présentent deux applications, l'une sur l'estimation de densité de dimension élevée basée sur le plus proche voisin et l'autre sur le comportement asymptotique des extrêmes multidimensionnels provenant de copules normales bidimensionnelles. La revue canadienne de statistique 37: 347,360; 2009 © 2009 Société statistique du Canada [source] THE FAMA-FRENCH MODEL, LEVERAGE, AND THE MODIGLIANI-MILLER PROPOSITIONSTHE JOURNAL OF FINANCIAL RESEARCH, Issue 3 2004Martin Lally Abstract For a cost-of-equity model to conform to the Modigliani-Miller cost-of-capital propositions, any sensitivity coefficients in the model must be related to the firm's leverage. In this paper I apply these principles to the Fama-French model for the cost of equity and develop the relation between its sensitivity coefficients and firm leverage. I then examine an empirical process developed by Fama and French (1997) to model the evolution through time of their sensitivity coefficients and show that this empirical process is inconsistent with the Modigliani-Miller propositions. Separable functions are proposed for these sensitivity coefficients that are consistent with the Modigliani-Miller propositions. [source] Rapid optimization of protein freeze-drying formulations using ultra scale-down and factorial design of experiment in microplatesBIOTECHNOLOGY & BIOENGINEERING, Issue 5 2009Yitzchak Grant Abstract Retaining biopharmaceutical proteins in a stable form is critical to their safety and efficacy, and is a major factor for optimizing the final product. Freeze-dried formulations offer one route for improved stability. Currently the optimization of formulations for freeze-drying is an empirical process that requires many time-consuming experiments and also uses large quantities of product material. Here we describe a generic framework for the rapid identification and optimization of formulation excipients to prevent loss of protein activity during a lyophilization process. Using factorial design of experiment (DOE) methods combined with lyophilization in microplates a range of optimum formulations were rapidly identified that stabilized lactose dehydrogenase (derived from Lactobacillus leichmanii) during freeze-drying. The procedure outlined herein involves two rounds of factorially designed experiments,an initial screen to identify key excipients and potential interactions followed by a central composite face designed optimization experiment. Polyethylene glycol (PEG) and lactose were shown to have significant effects on maintaining protein stability at the screening stage and optimization resulted in an accurate model that was used to plot a window of operation. The variation of freezing temperatures and rates of sublimation that occur across a microplate during freeze-drying have been characterized also. The optimum formulation was then freeze-dried in stoppered vials to verify that the microscale data was relevant to the effects observed at larger pilot scales. This work provides a generic approach to biopharmaceutical formulation screening where possible excipients can be screened for single and interactive effects thereby increasing throughput while reducing costs in terms of time and materials. Biotechnol. Bioeng. 2009; 104: 957,964. © 2009 Wiley Periodicals, Inc. [source] On residual empirical processes of GARCH-SM models: application to conditional symmetry testsJOURNAL OF TIME SERIES ANALYSIS, Issue 5 2008Naâmane Laïb 62M10; 62G10 Abstract., Considering the generalized autoregressive conditionally heteroskedastic with stochastic mean (GARCH-SM) model, we establish in this article the consistency and the weak representation of a functional of its residual empirical process. Based on this result, a symmetry test for GARCH-SM model is developed. Simulations are given to show the asymptotic behaviour and normality of the test statistic. [source] BOOTSTRAP TESTS FOR THE ERROR DISTRIBUTION IN LINEAR AND NONPARAMETRIC REGRESSION MODELSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 2 2006Natalie Neumeyer Summary In this paper we investigate several tests for the hypothesis of a parametric form of the error distribution in the common linear and non-parametric regression model, which are based on empirical processes of residuals. It is well known that tests in this context are not asymptotically distribution-free and the parametric bootstrap is applied to deal with this problem. The performance of the resulting bootstrap test is investigated from an asymptotic point of view and by means of a simulation study. The results demonstrate that even for moderate sample sizes the parametric bootstrap provides a reliable and easy accessible solution to the problem of goodness-of-fit testing of assumptions regarding the error distribution in linear and non-parametric regression models. [source] | ||||||||||