高校图书馆馆员学术成果应多元化

本文从图书馆的职能、馆员的整体知识结构、人员结构、读者的需求、馆藏文献的要求、课题跟踪服务的需要等几个方面阐述了高校图书馆馆员的学术成果应该多元化。     

A method for approximate fully bayesian analysis of parameters

Stochastic modeling of the geology in petroleum reservoirs has become an important tool in order to investigate flow properties in the reservoir. The stochastic models used contain parameters which must be estimated based on observations and geological knowledge. The amount of data available is however quite limited due to high drilling costs etc., and the lack of data prevents the use of many of the standard data driven approaches to the parameter estimation problem. Modern simulation based methods using Markov chain Monte Carlo simulation, can however be used to do fully Bayesian analysis with respect to parameters in the reservoir model, with the drawback of relatively high computational costs. In this paper, we propose a simple, relatively fast approximate method for fully Bayesian analysis of the parameters. We illustrate the method on both simulated and real data using a two-dimensional marked point model for reservoir characterization.     

何干之参与“中国社会性质问题论战”的学术成就及影响

何干之大约于1933年参与了当时思想界正在进行的"中国社会性质论战"。在"论战"中,他运用大量的经济史资料力证中国社会的半殖民地半封建性特征,提出了"新的民主革命"思想,并对参与"论战"主要派别的观点进行了较为科学的评述。何干之参与"论战"取得的学术成就,对新民主主义理论和毛泽东思想的形成产生了积极深远的影响。     

Influence curve of the monotonic dependence function for binormal distributions

Explicit formulae are derived for the influence curve of the monotonic dependence function in the case of binormal distributions, and are compared with those for the correlation coefficient. The interpretation of the comparison is given.     

Maximum likelihood and optimum location of observation sites in geodetic and spatial surveying

In geodetic and spatial surveying, accurate statistical es-timates of the Cartesian coordinates of a stationary target depend, in general, on such factors as target position, number and type of instruments, their location, their accuracy, and their mix. Direct measurements are assumed to be made in elevation, azimuth, and range with errors independently and normally distributed. For a mix of instruments, theoretical arguments are established using maximum likelihood estimation to determine the optimal siting of the instruments which minimizes (GDOP)² or the square of the geo-metric dilution of precision = sum of the variances of the estimates in the three orthogonal directions.     

Some asymptotic properties of point estimation with n-dimensional fuzzy data

Some asymptotic properties of point estimation with n-dimensional fuzzy data with respect to a special L ₂-metric ρ are investigated in this article. It is shown that the collection of all n-dimensional fuzzy data endowed with the ρ-metric is a complete and separable space. Some criterions for point estimation in such fuzzy environments are proposed, and the sample mean, variance and covariance with n-dimensional fuzzy data under these criteria are further studied.     

Calibration of predictions in regression

A regression predictor is well-calibrated if the predictions it gives are equal to the average responses that would be observed in an independent sample. The usual least squares predictor does not have this property, but its calibration can be improved by shrinking the predictions by a factor which depends on the signal-to-noise ratio of the regression model. We suggest a semi-Bayesian approach to estimating this factor, giving an estimate closely related to the so-called Stein Shririkasre Factor. The results are illustrated on a large medical data set.     

A non-inferiority test for diagnostic accuracy in the absence of the golden standard test based on the paired partial areas under receiver operating characteristic curves

Non-inferiority tests are often measured for the diagnostic accuracy in medical research. The area under the receiver operating characteristic (ROC) curve is a familiar diagnostic measure for the overall diagnostic accuracy. Nevertheless, since it may not differentiate the diverse shapes of the ROC curves with different diagnostic significance, the partial area under the ROC (PAUROC) curve, another summary measure emerges for such diagnostic processes that require the false-positive rate to be in the clinically interested range. Traditionally, to estimate the PAUROC, the golden standard (GS) test on the true disease status is required. Nevertheless, the GS test may sometimes be infeasible. Besides, in a lot of research fields such as the epidemiology field, the true disease status of the patients may not be known or available. Under the normality assumption on diagnostic test results, based on the expectation-maximization algorithm in combination with the bootstrap method, we propose the heuristic method to construct a non-inferiority test for the difference in the paired PAUROCs without the GS test. Through the simulation study, although the proposed method might provide a liberal test, as a whole, the empirical size of the proposed method sufficiently controls the size at the significance level, and the empirical power of the proposed method in the absence of the GS is as good as that of the non-inferiority in the presence of the GS. The proposed method is illustrated with the published data.     

A new weighted distribution as an extension of the generalized half-normal distribution with applications

In this study, a new extension of generalized half-normal (GHN) distribution is introduced. Since this new distribution can be viewed as weighted version of GHN distribution, it is called as weighted generalized half-normal (WGHN) distribution. It is shown that WGHN distribution can be observed as a single constrained and hidden truncation model. Therefore, the new distribution is more flexible than the GHN distribution. Some statistical properties of the WGHN distribution are studied, i.e. moments, cumulative distribution function, hazard rate function are derived. Furthermore, maximum likelihood estimation of the parameters is considered. Some real-life data sets taken from the literature are modelled using the WGHN distribution. It is seen that for these data sets the WGHN distribution provides better fitting than the GHN and slashed generalized half-normal (SGHN) distributions.     

A nonparametric inverse probability weighted estimation for functional data with missing response data at random

This paper considers the nonparametric inverse probability weighted estimation for functional data with missing response data at random. Under mild conditions, the asymptotic properties of the proposed estimation method are established. Based on the resampling method, the estimation of the asymptotic variance of the proposed estimator is obtained. Finally, the finite sample properties of the proposed estimation method are investigated via Monte Carlo simulation studies. A real data analysis is given to illustrate the use of the proposed method.