Semi-Parametric Maximum Likelihood Estimates for ROC Curves of Continuous-Scale Tests

In this paper, we propose a new semi-parametric maximum likelihood (ML) estimate of an ROC curve that satisfies the property of invariance of the ROC curve and is easy to compute. We show that our new estimator is [Formula: see text]-consistent and has an asymptotically normal distribution. Our extensive simulation studies show the proposed method is efficient, robust, and simple to compute. Finally, we illustrate the application of the proposed estimator in a real data set

A Semi-Parametric Two-Part Mixed-Effects Heteroscedastic Transformation Model for Correlated Right-Skewed Semi-Continuous Data

In longitudinal or hierarchical structure studies, we often encounter a semi-continuous variable that has a certain proportion of a single value and a continuous and skewed distribution among the rest of values. In the paper, we propose a new semi-parametric two-part mixed-effects transformation model to fit correlated skewed semi-continuous data. In our model, we allow the transformation to be non-parametric. Fitting the proposed model faces computational challenges due to intractable numerical integrations. We derive the estimates for the parameter and the transformation function based on an approximate likelihood, which has high order accuracy but less computational burden. We also propose an estimator for the expected value of the semi-continuous outcome on the original-scale. Finally, we apply the proposed methods to a clinical study on effectiveness of a collaborative care treatment on late life depression on health care costs

Semi-Parametric Maximum Likelihood Estimates for ROC Curves of Continuous-Scale Tests

In this paper, we propose a semi-parametric maximum likelihood estimate of an ROC curve that satisfies the property of invariance of the ROC curve. In our simulation studies, we demonstrate that the proposed estimator has the best performance among all the existing semi-parametric estimators considered here. Finally, we illustrate the application of the proposed estimator using a real data set

The Photometric Investigation of V921 Her using the Lunar-based Ultraviolet Telescope of Chang'e-3 mission

The light curve of V921 Her in ultraviolet band observed by the Lunar-based Ultraviolet Telescope (LUT) is analyzed by the Wilson-Devinney code. Our solutions conclude that V921 Her is an early type marginal contact binary system with an additional close-in component. The binary system is under poor thermal contact with a temperature difference of nearly $700K$ between the two components. The close-in component contributes about $19\,\%$ of the total luminosity in the triple system. Combining the radial velocity study together with our photometric solutions, the mass of the primary star and secondary one are calculated to be $M_1 = 1.784(\pm0.055)M_\odot$, $M_2 = 0.403(\pm0.012)M_\odot$. The evolutionary scenario of V921 Her is discussed. All times of light minimum of V921 Her available in the bibliography are taken into account and the $O - C$ curve is analyzed for the first time. The most probable fitting results are discussed in the paper, which also confirm the existence of a third component ($P_3=10.2$ year) around the binary system. The period of V921 Her is also undergoing a continuously rapid increase at a rate of $dP/dt=+2.79\times{10^{-7}}day\cdot year^{-1}$, which may due to mass transfer from the less massive component to the more massive one