Home About us Contact
|
Home About us Contact | ||
|
|
||
Correlation Parameters (correlation + parameter)
Selected AbstractsSpatial distribution of cloud coverINTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING, Issue 2 2008Pedro Garcia Abstract Satellite systems and high-altitude platform systems working in Ka and V bands require the application of adaptive techniques in order to mitigate link degradations caused by atmospheric impairments such as those due to cloud cover. Among these techniques, resource sharing system techniques and site diversity need information on the spatial distribution of impairments caused by cloud cover, including the probability of simultaneous occurrence of adverse conditions in various regions. A study has been performed in Spain, within the framework of COST Action 280, to investigate the large-scale spatial distribution of cloud cover using synoptic meteorological data. Cloud cover distribution for individual sites and the spatial correlation properties for pairs of sites have been investigated. The geographical distributions of the values obtained from the statistical analysis have been represented in maps of contour lines using standard mapping procedures. Correlation parameters are expected to decrease with distance; however, the maps derived taking a given site as reference reveal a significant influence of climatic and geographic factors such as weather fronts, orography or the proximity to the sea. The statistics and maps obtained can be useful to optimize power sharing in multi-beam satellite systems, as suggested in this paper. Copyright © 2008 John Wiley & Sons, Ltd. [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] A Latent Contingency Table Approach to Dose Finding for Combinations of Two AgentsBIOMETRICS, Issue 3 2009Guosheng Yin Summary Two-agent combination trials have recently attracted enormous attention in oncology research. There are several strong motivations for combining different agents in a treatment: to induce the synergistic treatment effect, to increase the dose intensity with nonoverlapping toxicities, and to target different tumor cell susceptibilities. To accommodate this growing trend in clinical trials, we propose a Bayesian adaptive design for dose finding based on latent 2 × 2 tables. In the search for the maximum tolerated dose combination, we continuously update the posterior estimates for the unknown parameters associated with marginal probabilities and the correlation parameter based on the data from successive patients. By reordering the dose toxicity probabilities in the two-dimensional space, we assign each coming cohort of patients to the most appropriate dose combination. We conduct extensive simulation studies to examine the operating characteristics of the proposed method under various practical scenarios. Finally, we illustrate our dose-finding procedure with a clinical trial of agent combinations at M. D. Anderson Cancer Center. [source] Raman and Rayleigh scattering study of crystalline polyoxyethyleneglycolsCRYSTAL RESEARCH AND TECHNOLOGY, Issue 4-5 2005M. Kozielski Abstract Results of the study of Raman and Rayleigh scattering in crystalline polyoxyethyleneglycols (PEG) and PEG 1500 aqueous solution are reported. The conformational changes of the polymer chain have been studied as a function of PEG water solution concentration and molecular weight. Intensity ratios of the gauche and trans conformation around C,C and C,O bonds have been estimated from the Raman spectra. Moreover, from the Raman band parameters the values of the order parameters versus aqueous solution concentration have been determined. The influence of an external electric field on these parameters has been analysed. Mutual orientation of polyoxyethyleneglycol chains in the crystalline and liquid state has been studied on the basis of the angular correlation parameters obtained from the Rayleigh band intensity as a function of aqueous solution concentration and molecular weight. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Stochastic matrix models for conservation and management: a comparative review of methodsECOLOGY LETTERS, Issue 3 2001John Fieberg Stochastic matrix models are frequently used by conservation biologists to measure the viability of species and to explore various management actions. Models are typically parameterized using two or more sets of estimated transition rates between age/size/stage classes. While standard methods exist for analyzing a single set of transition rates, a variety of methods have been employed to analyze multiple sets of transition rates. We review applications of stochastic matrix models to problems in conservation and use simulation studies to compare the performance of different analytic methods currently in use. We find that model conclusions are likely to be robust to the choice of parametric distribution used to model vital rate fluctuations over time. However, conclusions can be highly sensitive to the within-year correlation structure among vital rates, and therefore we suggest using analytical methods that provide a means of conducting a sensitivity analysis with respect to correlation parameters. Our simulation results also suggest that the precision of population viability estimates can be improved by using matrix models that incorporate environmental covariates in conjunction with experiments to estimate transition rates under a range of environmental conditions. [source] Three-dimensional spatial interpolation of surface meteorological observations from high-resolution local networksMETEOROLOGICAL APPLICATIONS, Issue 3 2008Francesco Uboldi Abstract An objective analysis technique is applied to a local, high-resolution meteorological observation network in the presence of complex topography. The choice of optimal interpolation (OI) makes it possible to implement a standard spatial interpolation algorithm efficiently. At the same time OI constitutes a basis to develop, in perspective, a full multivariate data assimilation scheme. In the absence of a background model field, a simple and effective de-trending procedure is implemented. Three-dimensional correlation functions are used to account for the orographic distribution of observing stations. Minimum-scale correlation parameters are estimated by means of the integral data influence (IDI) field. Hourly analysis fields of temperature and relative humidity are routinely produced at the Regional Weather Service of Lombardia. The analysis maps show significant informational content even in the presence of strong gradients and infrequent meteorological situations. Quantitative evaluation of the analysis fields is performed by systematically computing their cross validation (CV) scores and by estimating the analysis bias. Further developments concern the implementation of an automatic quality control procedure and the improvement of error covariance estimation. Copyright © 2008 Royal Meteorological Society [source] Analysis of Misclassified Correlated Binary Data Using a Multivariate Probit Model when Covariates are Subject to Measurement ErrorBIOMETRICAL JOURNAL, Issue 3 2009Surupa Roy Abstract A multivariate probit model for correlated binary responses given the predictors of interest has been considered. Some of the responses are subject to classification errors and hence are not directly observable. Also measurements on some of the predictors are not available; instead the measurements on its surrogate are available. However, the conditional distribution of the unobservable predictors given the surrogate is completely specified. Models are proposed taking into account either or both of these sources of errors. Likelihood-based methodologies are proposed to fit these models. To ascertain the effect of ignoring classification errors and /or measurement error on the estimates of the regression and correlation parameters, a sensitivity study is carried out through simulation. Finally, the proposed methodology is illustrated through an example. [source] Incorporating Correlation for Multivariate Failure Time Data When Cluster Size Is LargeBIOMETRICS, Issue 2 2010L. Xue Summary We propose a new estimation method for multivariate failure time data using the quadratic inference function (QIF) approach. The proposed method efficiently incorporates within-cluster correlations. Therefore, it is more efficient than those that ignore within-cluster correlation. Furthermore, the proposed method is easy to implement. Unlike the weighted estimating equations in Cai and Prentice (1995,,Biometrika,82, 151,164), it is not necessary to explicitly estimate the correlation parameters. This simplification is particularly useful in analyzing data with large cluster size where it is difficult to estimate intracluster correlation. Under certain regularity conditions, we show the consistency and asymptotic normality of the proposed QIF estimators. A chi-squared test is also developed for hypothesis testing. We conduct extensive Monte Carlo simulation studies to assess the finite sample performance of the proposed methods. We also illustrate the proposed methods by analyzing primary biliary cirrhosis (PBC) data. [source] Estimating a Multivariate Familial Correlation Using Joint Models for Canonical Correlations: Application to Memory Score Analysis from Familial Hispanic Alzheimer's Disease StudyBIOMETRICS, Issue 2 2009Hye-Seung Lee Summary Analysis of multiple traits can provide additional information beyond analysis of a single trait, allowing better understanding of the underlying genetic mechanism of a common disease. To accommodate multiple traits in familial correlation analysis adjusting for confounders, we develop a regression model for canonical correlation parameters and propose joint modeling along with mean and scale parameters. The proposed method is more powerful than the regression method modeling pairwise correlations because it captures familial aggregation manifested in multiple traits through maximum canonical correlation. [source] Variable morphology of the sacrum in a Chinese populationCLINICAL ANATOMY, Issue 5 2009Li-Ping Wu Abstract Although several morphological variations of sacrum have been reported in western populations, little attention has been paid to this anatomic issue in eastern people, and classification of sacral variability in particular. In this research of sacral morphology in Chinese people, we investigated and measured thoroughly and systematically 203 specimens of intact dry Chinese adult sacra. Morphological features of sacral variations were observed by visual inspection, and correlation parameters of variability were measured with a vernier caliper. The incidence of sacral variations was calculated. We found that the overall rate of sacral variations was 58.1% (male: 57.4%; female: 59.5%). The anatomical variants that we observed fell into the following five categories: accessory auricular surface (25 specimens, 12.3%); sacral skewness (48 specimens, 23.6%); transitional vertebra (34 specimens, 16.7%); sacral spina bifida occulta (57 specimens, 28.1%), Degrees I, II, and III of which were 36, 14, and 7 specimens, respectively; multiple variations (42 specimens, 20.7%), the types of which were diversified. This study reveals that sacral variations are common in Chinese population. The sacral variants in anatomic morphology should be taken into consideration when diagnosing and treating sacrum-related diseases. Clin. Anat. 22:619,626, 2009. © 2009 Wiley-Liss, Inc. [source] | |||||||||||||