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Maximum Likelihood Approach (maximum + likelihood_approach)
Selected AbstractsMultivariate Survival Trees: A Maximum Likelihood Approach Based on Frailty ModelsBIOMETRICS, Issue 1 2004Xiaogang Su Summary. A method of constructing trees for correlated failure times is put forward. It adopts the backfitting idea of classification and regression trees (CART) (Breiman et al., 1984, in Classification and Regression Trees). The tree method is developed based on the maximized likelihoods associated with the gamma frailty model and standard likelihood-related techniques are incorporated. The proposed method is assessed through simulations conducted under a variety of model configurations and illustrated using the chronic granulomatous disease (CGD) study data. [source] Haplotype analysis and age estimation of the 113insR CDKN2A founder mutation in Swedish melanoma familiesGENES, CHROMOSOMES AND CANCER, Issue 2 2001Jamileh Hashemi Germline mutations in the CDKN2A tumor suppressor gene located on 9p21 have been linked to development of melanomas in some families. A germline 3-bp insertion in exon 2 of CDKN2A, leading to an extra arginine at codon 113 (113insR), has been identified in 17 Swedish melanoma families. Analysis of 10 microsatellite markers, spanning approximately 1 Mbp in the 9p21 region, showed that all families share a common allele for at least one of the markers closest to the CDKN2A gene, suggesting that the 113insR mutation is an ancestral founder mutation. Differences in the segregating haplotypes, due to meiotic recombinations and/or mutations in the short-tandem-repeat markers, were analyzed further to estimate the age of the mutation. Statistical analysis using a maximum likelihood approach indicated that the mutation arose 98 generations (90% confidence interval: 52,167 generations), or approximately 2,000 years, ago. Thus, 113insR would be expected to have a more widespread geographic distribution in European and North American regions with ancestral connections to Sweden. Alternatively, CDKN2A may lie in a recombination hot spot region, as suggested by the many meiotic recombinations in this narrow ,1-cM region on 9p21. © 2001 Wiley-Liss, Inc. [source] SEMINONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF CONDITIONAL MOMENT RESTRICTION MODELS,INTERNATIONAL ECONOMIC REVIEW, Issue 4 2007Chunrong Ai This article studies estimation of a conditional moment restriction model with the seminonparametric maximum likelihood approach proposed by Gallant and Nychka (Econometrica 55 (March 1987), 363,90). Under some sufficient conditions, we show that the estimator of the finite dimensional parameter , is asymptotically normally distributed and attains the semiparametric efficiency bound and that the estimator of the density function is consistent under L2 norm. Some results on the convergence rate of the estimated density function are derived. An easy to compute covariance matrix for the asymptotic covariance of the , estimator is presented. [source] Dispersal of the emerald ash borer, Agrilus planipennis, in newly-colonized sitesAGRICULTURAL AND FOREST ENTOMOLOGY, Issue 4 2009Rodrigo J. Mercader Abstract 1Emerald ash borer Agrilus planipennis Fairmaire (Coleoptera: Buprestidae) is an invasive forest insect pest threatening more than 8 billion ash (Fraxinus spp.) trees in North America. Development of effective survey methods and strategies to slow the spread of A. planipennis requires an understanding of dispersal, particularly in recently established satellite populations. 2We assessed the dispersal of A. planipennis beetles over a single generation at two sites by intensively sampling ash trees at known distances from infested ash logs, the point source of the infestations. Larval density was recorded from more than 100 trees at each site. 3Density of A. planipennis larvae by distance for one site was fit to the Ricker function, inverse power function, and the negative exponential function using a maximum likelihood approach. The prediction of the best model, a negative exponential function, was compared with the results from both sites. 4The present study demonstrates that larval densities rapidly declined with distance, and that most larvae (88.9 and 90.3%) were on trees within 100 m of the emergence point of the adults at each site. The larval distribution pattern observed at both sites was adequately described by the negative exponential function. [source] A unified maximum likelihood approach to document retrievalJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 10 2001David Bodoff Empirical work shows significant benefits from using relevance feedback data to improve information retrieval (IR) performance. Still, one fundamental difficulty has limited the ability to fully exploit this valuable data. The problem is that it is not clear whether the relevance feedback data should be used to train the system about what the users really mean, or about what the documents really mean. In this paper, we resolve the question using a maximum likelihood framework. We show how all the available data can be used to simultaneously estimate both documents and queries in proportions that are optimal in a maximum likelihood sense. The resulting algorithm is directly applicable to many approaches to IR, and the unified framework can help explain previously reported results as well as guide the search for new methods that utilize feedback data in IR. [source] A MODEL LIFE TABLE FOR BOTTLENOSE DOLPHINS (TURSIOPS TRUNCATUS) FROM THE INDIAN RIVER LAGOON SYSTEM, FLORIDA, U.S.A.MARINE MAMMAL SCIENCE, Issue 4 2003Megan K. Stolen Abstract Data gathered from 220 stranded bottlenose dolphins (Tursiops truncatus) in the Indian River Lagoon system, Florida, were used to derive a life table. Survivorship curves were fit to the data using Siler's competing-risk model and a maximum likelihood approach. Population growth was estimated to be between r= 0.0 and 0.046 based on the observed numbers of stranded dolphins. Variance in survival rates was estimated using an individual-based, age-structured population projection model. We estimate that the overall annual mortality rate for this population was 9.8% per year. Sex-specific differences in survivorship were apparent with females outliving males. The overall mortality curve resembles that of other large mammals, with high calf mortality and an exponentially increasing risk of senescent mortality. The inclusion of live-capture removals of individuals from this population did not significantly affect the estimation of survival parameters for most age classes. [source] Heterogeneity in dynamic discrete choice modelsTHE ECONOMETRICS JOURNAL, Issue 1 2010Martin Browning Summary, We consider dynamic discrete choice models with heterogeneity in both the levels parameter and the state dependence parameter. We first present an empirical analysis that motivates the theoretical analysis which follows. The theoretical analysis considers a simple two-state, first-order Markov chain model without covariates in which both transition probabilities are heterogeneous. Using such a model we are able to derive exact small sample results for bias and mean squared error (MSE). We discuss the maximum likelihood approach and derive two novel estimators. The first is a bias corrected version of the Maximum Likelihood Estimator (MLE) although the second, which we term MIMSE, minimizes the integrated mean square error. The MIMSE estimator is always well defined, has a closed-form expression and inherits the desirable large sample properties of the MLE. Our main finding is that in almost all short panel contexts the MIMSE significantly outperforms the other two estimators in terms of MSE. A final section extends the MIMSE estimator to allow for exogenous covariates. [source] Examining the extinction risk of specialized folivores: a comparative study of Colobine monkeysAMERICAN JOURNAL OF PRIMATOLOGY, Issue 9 2008Jason M. Kamilar Abstract Species extinctions are nonrandom with some taxa appearing to possess traits that increase their extinction risk. In this study, eight predictors of extinction risk were used as independent variables to predict the IUCN category of a subfamily of specialized folivorous primates, the Colobinae. All data were transformed into phylogenetically independent contrasts and were analyzed using bivariate regressions, multiple regression, and a maximum likelihood approach using Akaike's Information Criterion to assess model performance. Once an outlier was removed from the data set, species that devote a smaller proportion of their diet to mature leaf consumption appear to be at a greater risk of extinction. Also, as female body mass increases, so does extinction risk. In contrast, as maximum latitude and the number of habitat types increase, extinction risk appears to decrease. These findings emphasize the importance of examining detailed dietary variation for predicting extinction risk at a relatively fine taxonomic scale and, consequently, may help improve conservation management. Am. J. Primatol. 70:816,827, 2008. © 2008 Wiley-Liss, Inc. [source] Optimal designs for parameter estimation of the Ornstein,Uhlenbeck processAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 5 2009Maroussa Zagoraiou Abstract This paper deals with optimal designs for Gaussian random fields with constant trend and exponential correlation structure, widely known as the Ornstein,Uhlenbeck process. Assuming the maximum likelihood approach, we study the optimal design problem for the estimation of the trend µ and the correlation parameter , using a criterion based on the Fisher information matrix. For the problem of trend estimation, we give a new proof of the optimality of the equispaced design for any sample size (see Statist. Probab. Lett. 2008; 78:1388,1396). We also show that for the estimation of the correlation parameter, an optimal design does not exist. Furthermore, we show that the optimal strategy for µ conflicts with the one for ,, since the equispaced design is the worst solution for estimating the correlation. Hence, when the inferential purpose concerns both the unknown parameters we propose the geometric progression design, namely a flexible class of procedures that allow the experimenter to choose a suitable compromise regarding the estimation's precision of the two unknown parameters guaranteeing, at the same time, high efficiency for both. Copyright © 2008 John Wiley & Sons, Ltd. [source] Modelling and forecasting vehicle stocks using the trends of stochastic Gompertz diffusion models: The case of SpainAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2009R. Gutiérrez Abstract In the present study, we treat the stochastic homogeneous Gompertz diffusion process (SHGDP) by the approach of the Kolmogorov equation. Firstly, using a transformation in diffusion processes, we show that the probability transition density function of this process has a lognormal time-dependent distribution, from which the trend and conditional trend functions and the stationary distribution are obtained. Second, the maximum likelihood approach is adapted to the problem of parameters estimation in the drift and the diffusion coefficient using discrete sampling of the process, then the approximated asymptotic confidence intervals of the parameter are obtained. Later, we obtain the corresponding inference of the stochastic homogeneous lognormal diffusion process as limit from the inference of SHGDP when the deceleration factor tends to zero. A statistical methodology, based on the above results, is proposed for trend analysis. Such a methodology is applied to modelling and forecasting vehicle stocks. Finally, an application is given to illustrate the methodology presented using real data, concretely the total vehicle stocks in Spain. Copyright © 2008 John Wiley & Sons, Ltd. [source] Semiparametric Transformation Models with Random Effects for Joint Analysis of Recurrent and Terminal EventsBIOMETRICS, Issue 3 2009Donglin Zeng Summary We propose a broad class of semiparametric transformation models with random effects for the joint analysis of recurrent events and a terminal event. The transformation models include proportional hazards/intensity and proportional odds models. We estimate the model parameters by the nonparametric maximum likelihood approach. The estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Simple and stable numerical algorithms are provided to calculate the parameter estimators and to estimate their variances. Extensive simulation studies demonstrate that the proposed inference procedures perform well in realistic settings. Applications to two HIV/AIDS studies are presented. [source] | ||||||||||||||||