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Joint Estimation (joint + estimation)
Selected AbstractsContinuity and change in social and physical aggression from middle childhood through early adolescenceAGGRESSIVE BEHAVIOR, Issue 5 2009Marion K. Underwood For a sample followed from age 9,13 (N=281), this investigation examined developmental trajectories for social and physical aggression as measured by teacher ratings. Trajectories for both forms of aggression were estimated first separately, then jointly. Mean levels of both social and physical aggression decreased over time for the overall sample, but with high variability of individual trajectories. Subgroups followed high trajectories for both social and physical aggression. Joint estimation yielded six trajectories: low stable, low increasers, medium increasers, medium desisters, high desisters, and high increasers. Membership in the high increaser group was predicted by male gender, unmarried parents, African American ethnicity, and maternal authoritarian and permissive parenting. Permissive parenting also predicted membership in the medium increaser group. This is one of the first studies to examine social aggression longitudinally across this developmental period. Though the results challenge the claim that social aggression is at its peak in early adolescence, the findings emphasize the importance of considering different developmental trajectories in trying to understand origins and outcomes of aggression. Aggr. Behav. 35:357,375, 2009. © 2009 Wiley-Liss, Inc. [source] Joint estimation of information acquisition and adoption of new technologies under uncertainty,JOURNAL OF INTERNATIONAL DEVELOPMENT, Issue 4 2008Awudu Abdulai Abstract This article develops a framework to examine households' joint decision to acquire information on new technologies and the adoption of the technology in the presence of uncertainty. The empirical application involved a sample of 406 dairy farmers in Tanzania. Education, scale of production, household size, age, and liquidity constraints are hypothesized to be the determinants of information acquisition and adoption decisions. The empirical evidence indicates that information acquisition and adoption decisions are made jointly. The findings also show that human capital and scale of operation positively and significantly affect the decision to acquire information and to adopt the technology, while liquidity constraints negatively impact on the decision to adopt, as well as the extent of adoption. Copyright © 2008 John Wiley & Sons, Ltd. [source] Feedforward joint phase and timing estimation for MSK,type signalsEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 4 2001Michele Morelli Novel non data,aided (NDA) algorithms are proposed for joint estimation of timing and carrier phase in MSK,type modulations. They are based on maximum likelihood methods and have a feedforward structure which is suitable to fully digital implementation. Performance with MSK and Gaussian MSK. (GMSK) is assessed by computer simulations and compared with that of other existing estimation schemes. [source] Sequential Monte Carlo methods for multi-aircraft trajectory prediction in air traffic managementINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2010I. Lymperopoulos Abstract Accurate prediction of aircraft trajectories is an important part of decision support and automated tools in air traffic management. We demonstrate that by combining information from multiple aircraft at different locations and time instants, one can provide improved trajectory prediction (TP) accuracy. To perform multi-aircraft TP, we have at our disposal abundant data. We show how this multi-aircraft sensor fusion problem can be formulated as a high-dimensional state estimation problem. The high dimensionality of the problem and nonlinearities in aircraft dynamics and control prohibit the use of common filtering methods. We demonstrate the inefficiency of several sequential Monte Carlo algorithms on feasibility studies involving multiple aircraft. We then develop a novel particle filtering algorithm to exploit the structure of the problem and solve it in realistic scale situations. In all studies we assume that aircraft fly level (possibly at different altitudes) with known, constant, aircraft-dependent airspeeds and estimate the wind forecast errors based only on ground radar measurements. Current work concentrates on extending the algorithms to non-level flights, the joint estimation of wind forecast errors and the airspeed and mass of the different aircraft and the simultaneous fusion of airborne and ground radar measurements. Copyright © 2010 John Wiley & Sons, Ltd. [source] Moment independent and variance-based sensitivity analysis with correlations: An application to the stability of a chemical reactorINTERNATIONAL JOURNAL OF CHEMICAL KINETICS, Issue 11 2008E. Borgonovo Recent works have attracted interest toward sensitivity measures that use the entire model output distribution, without dependence on any of its particular moments (e.g., variance). However, the computation of moment-independent importance measures in the presence of dependencies among model inputs has not been dealt with yet. This work has two purposes. On the one hand, to introduce moment independent techniques in the analysis of chemical reaction models. On the other hand, to allow their computation in the presence of correlations. To do so, a new approach based on Gibbs sampling is presented that allows the joint estimation of variance-based and moment independent sensitivity measures in the presence of correlations. The application to the stability of a chemical reactor is then discussed, allowing full consideration of historical data that included a correlation coefficient of 0.7 between two of the model parameters. © 2008 Wiley Periodicals, Inc. Int J Chem Kinet 40: 687,698, 2008 [source] COMBINING REVEALED AND STATED PREFERENCE DATA TO ESTIMATE THE NONMARKET VALUE OF ECOLOGICAL SERVICES: AN ASSESSMENT OF THE STATE OF THE SCIENCEJOURNAL OF ECONOMIC SURVEYS, Issue 5 2008John C. Whitehead Abstract This paper reviews the marketing, transportation and environmental economics literature on the joint estimation of revealed preference (RP) and stated preference (SP) data. The RP and SP approaches are first described with a focus on the strengths and weaknesses of each. Recognizing these strengths and weaknesses, the potential gains from combining data are described. A classification system for combined data that emphasizes the type of data combination and the econometric models used is proposed. A methodological review of the literature is pursued based on this classification system. Examples from the environmental economics literature are highlighted. A discussion of the advantages and disadvantages of each type of jointly estimated model is then presented. Suggestions for future research, in particular opportunities for application of these models to environmental quality valuation, are presented. [source] Joint generalized estimating equations for multivariate longitudinal binary outcomes with missing data: an application to acquired immune deficiency syndrome dataJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2009Stuart R. Lipsitz Summary., In a large, prospective longitudinal study designed to monitor cardiac abnormalities in children born to women who are infected with the human immunodeficiency virus, instead of a single outcome variable, there are multiple binary outcomes (e.g. abnormal heart rate, abnormal blood pressure and abnormal heart wall thickness) considered as joint measures of heart function over time. In the presence of missing responses at some time points, longitudinal marginal models for these multiple outcomes can be estimated by using generalized estimating equations (GEEs), and consistent estimates can be obtained under the assumption of a missingness completely at random mechanism. When the missing data mechanism is missingness at random, i.e. the probability of missing a particular outcome at a time point depends on observed values of that outcome and the remaining outcomes at other time points, we propose joint estimation of the marginal models by using a single modified GEE based on an EM-type algorithm. The method proposed is motivated by the longitudinal study of cardiac abnormalities in children who were born to women infected with the human immunodeficiency virus, and analyses of these data are presented to illustrate the application of the method. Further, in an asymptotic study of bias, we show that, under a missingness at random mechanism in which missingness depends on all observed outcome variables, our joint estimation via the modified GEE produces almost unbiased estimates, provided that the correlation model has been correctly specified, whereas estimates from standard GEEs can lead to substantial bias. [source] METHODS FOR JOINT INFERENCE FROM MULTIPLE DATA SOURCES FOR IMPROVED ESTIMATES OF POPULATION SIZE AND SURVIVAL RATESMARINE MAMMAL SCIENCE, Issue 3 2004Daniel Goodman Abstract Critical conservation decisions often hinge on estimates of population size, population growth rate, and survival rates, but as a practical matter it is difficult to obtain enough data to provide precise estimates. Here we discuss Bayesian methods for simultaneously drawing on the information content from multiple sorts of data to get as much precision as possible for the estimates. The basic idea is that an underlying population model can connect the various sorts of observations, so this can be elaborated into a joint likelihood function for joint estimation of the respective parameters. The potential for improved estimates derives from the potentially greater effective sample size of the aggregate of data, even though some of the data types may only bear directly on a subset of the parameters. The achieved improvement depends on specifics of the interactions among parameters in the underlying model, and on the actual content of the data. Assuming the respective data sets are unbiased, notwithstanding the fact that they may be noisy, we may gauge the average improvement in the estimates of the parameters of interest from the reduction, if any, in the standard deviations of their posterior marginal distributions. Prospective designs may be evaluated from analysis of simulated data. Here this approach is illustrated with an assessment of the potential value in various ways of merging mark-resight and carcass-survey data for the Florida manatee, as could be made possible by various modifications in the data collection protocols in both programs. [source] A robust method for the joint estimation of yield coefficients and kinetic parameters in bioprocess modelsBIOTECHNOLOGY PROGRESS, Issue 3 2009V. Vastemans Abstract Bioprocess model structures that require nonlinear parameter estimation, thus initialization values, are often subject to poor identification performances because of the uncertainty on those initialization values. Under some conditions on the model structure, it is possible to partially circumvent this problem by an appropriate decoupling of the linear part of the model from the nonlinear part of it. This article provides a procedure to be followed when these structural conditions are not satisfied. An original method for decoupling two sets of parameters, namely, kinetic parameters from maximum growth, production, decay rates, and yield coefficients, is presented. It exhibits the advantage of requiring only initialization of the first subset of parameters. In comparison with a classical nonlinear estimation procedure, in which all the parameters are freed, results show enhanced robustness of model identification with regard to parameter initialization errors. This is illustrated by means of three simulation case studies: a fed-batch Human Embryo Kidney cell cultivation process using a macroscopic reaction scheme description, a process of cyclodextrin-glucanotransferase production by Bacillus circulans, and a process of simultaneous starch saccharification and glucose fermentation to lactic acid by Lactobacillus delbrückii, both based on a Luedeking-Piret model structure. Additionally, perspectives of the presented procedure in the context of systematic bioprocess modeling are promising. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009 [source] | |||||||||||||