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991.
《Omega》2015
Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks. 相似文献
992.
993.
Li Yan 《Statistics》2015,49(5):978-988
Empirical likelihood inference for generalized linear models with fixed and adaptive designs is considered. It is shown that the empirical log-likelihood ratio at the true parameters converges to the standard chi-square distribution. Furthermore, we obtain the maximum empirical likelihood estimate of the unknown parameter and the resulting estimator is shown to be asymptotically normal. Some simulations are conducted to illustrate the proposed method. 相似文献
994.
This paper considers the search for locally and maximin optimal designs for multi-factor nonlinear models from optimal designs for sub-models of a lower dimension. In particular, sufficient conditions are given so that maximin D-optimal designs for additive multi-factor nonlinear models can be built from maximin D-optimal designs for their sub-models with a single factor. Some examples of application are models involving exponential decay in several variables. 相似文献
995.
In this note, we show how specify cointegrated vector autoregressive-moving average models and how they can be used to generate cointegrated time series. 相似文献
996.
997.
Carles Serrat Montserrat Rué Carmen Armero Xavier Piulachs Hèctor Perpiñán Anabel Forte 《Journal of applied statistics》2015,42(6):1223-1239
The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian inference highlight the potential of joint models to guide personalized risk-based screening strategies. 相似文献
998.
Climate is an essential component in site suitability for agriculture in general, and specifically in viticulture. With the recent increase in vineyards on the East Coast, an important climactic consideration in site suitability is extreme winter temperature. Often, maps of annual minimum temperatures are used to determine cold hardiness. However, cold hardiness of grapes is a more complicated process, since the temperature that grapes are able to withstand without damage is not constant. Rather, recent temperature cause acclimation or deacclimation and hence, have a large influence on cold hardiness. By combining National Oceanic and Atmospheric Administration (NOAA) weather station data and leveraging recently created cold hardiness models for grapes, we develop a dynamic spatio-temporal model to determine the risk of winter damage due to extreme cold for several grape varieties commonly grown in the eastern United States. This analysis provides maps of winter damage risk to three grape varieties, Chardonnay, Cabernet Sauvignon, and Concord. 相似文献
999.
Partially linear models are extensions of linear models that include a nonparametric function of some covariate allowing an adequate and more flexible handling of explanatory variables than in linear models. The difference-based estimation in partially linear models is an approach designed to estimate parametric component by using the ordinary least squares estimator after removing the nonparametric component from the model by differencing. However, it is known that least squares estimates do not provide useful information for the majority of data when the error distribution is not normal, particularly when the errors are heavy-tailed and when outliers are present in the dataset. This paper aims to find an outlier-resistant fit that represents the information in the majority of the data by robustly estimating the parametric and the nonparametric components of the partially linear model. Simulations and a real data example are used to illustrate the feasibility of the proposed methodology and to compare it with the classical difference-based estimator when outliers exist. 相似文献
1000.
Marco Bee 《统计学通讯:模拟与计算》2015,44(8):2040-2060
This article deals with the estimation of the lognormal-Pareto and the lognormal-generalized Pareto distributions, for which a general result concerning asymptotic optimality of maximum likelihood estimation cannot be proved. We develop a method based on probability weighted moments, showing that it can be applied straightforwardly to the first distribution only. In the lognormal-generalized Pareto case, we propose a mixed approach combining maximum likelihood and probability weighted moments. Extensive simulations analyze the relative efficiencies of the methods in various setups. Finally, the techniques are applied to two real datasets in the actuarial and operational risk management fields. 相似文献