论技术创新测度指标设置

本文依据技术创新活动的商业实质,从其活动过程的投入产出因素入手,阐述了测度技术创新水平的指标设置问题.     

Parameterization and inference for nonparametric regression problems

We consider local likelihood or local estimating equations, in which a multivariate function () is estimated but a derived function () of () is of interest. In many applications, when most naturally formulated the derived function is a non-linear function of (). In trying to understand whether the derived non-linear function is constant or linear, a problem arises with this approach: when the function is actually constant or linear, the expectation of the function estimate need not be constant or linear, at least to second order. In such circumstances, the simplest standard methods in nonparametric regression for testing whether a function is constant or linear cannot be applied. We develop a simple general solution which is applicable to nonparametric regression, varying-coefficient models, nonparametric generalized linear models, etc. We show that, in local linear kernel regression, inference about the derived function () is facilitated without a loss of power by reparameterization so that () is itself a component of (). Our approach is in contrast with the standard practice of choosing () for convenience and allowing ()> to be a non-linear function of (). The methods are applied to an important data set in nutritional epidemiology.     

Measuring longevity achievements under welfare interdependencies: a case for joint life expectancy indicators

Whereas period life expectancy constitutes an intuitive indicator of the survival conditions prevailing at a particular period, this paper argues that, given the existence of welfare interdependencies, that widespread indicator is nonetheless an incomplete measure of the longevity achievements relevant for human well-being. The central importance of coexistence for human-beings implies that usual life expectancy measures should be complemented by joint life expectancy indicators, which measure the average coexistence time under particular survival conditions. After a study of the theoretical foundations of ‘single’ and ‘joint’ life expectancy indicators, it is shown that joint life expectancy measures tend to enrich significantly the comparison of longevity achievements across countries and periods. Moreover, the introduction of joint life expectancy indicators—as a complement to conventional life expectancy measures—into multi-variable indexes such as the United Nations’ HDI is also shown to affect international rankings of standards of living to a non negligible extent.

互感电桥法测量超导临界温度

本文描述了超导体临界温度的一种测量方法方.系统使用相敏深测,仪器成深头形式,可以直接插入杜瓦进行测量.该装置能测量小至12Oμg的超导体样品的临界温度,信噪比为10:1.     

Variable Selection for Semiparametric Varying Coefficient Partially Linear Errors-in-Variables (EV) Model with Missing Response

This paper focuses on the variable selection for semiparametric varying coefficient partially linear model when the covariates are measured with additive errors and the response is missing. An adaptive lasso estimator and the smoothly clipped absolute deviation estimator as a comparison for the parameters are proposed. With the proper selection of regularization parameter, the sampling properties including the consistency of the two procedures and the oracle properties are established. Furthermore, the algorithms and corresponding standard error formulas are discussed. A simulation study is carried out to assess the finite sample performance of the proposed methods.     

Confidence Interval Estimation in Ultrastructural Model

The present article proposes a methodology to construct confidence interval for slope parameter and joint confidence region for intercept term and slope parameter in an ultra-structural model with equation error and correlated measurement errors.     

Prediction and forecasting in linear models with measurement error

We consider measurement error models within the time series unobserved component framework. A variable of interest is observed with some measurement error and modelled as an unobserved component. The forecast and the prediction of this variable given the observed values is given by the Kalman filter and smoother along with their conditional variances. By expressing the forecasts and predictions as weighted averages of the observed values, we investigate the effect of estimation error in the measurement and observation noise variances. We also develop corrected standard errors for prediction and forecasting accounting for the fact that the measurement and observation error variances are estimated by the same sample that is used for forecasting and prediction purposes. We apply the theory to the Yellowstone grizzly bears and US index of production datasets.     

Failure time regression with continuous covariates measured with error

We consider failure time regression analysis with an auxiliary variable in the presence of a validation sample. We extend the nonparametric inference procedure of Zhou and Pepe to handle a continuous auxiliary or proxy covariate. We estimate the induced relative risk function with a kernel smoother and allow the selection probability of the validation set to depend on the observed covariates. We present some asymptotic properties for the kernel estimator and provide some simulation results. The method proposed is illustrated with a data set from an on-going epidemiologic study.     

Inequity at work: Its measurement and association with worker health

Abstract

This paper considers the extent to which stress-induced illness can be regarded as a personal injury that could give rise to civil action for damages against employers in the UK. It outlines the results of a brief survey of personal injury solicitors, which indicates that claims are already being initiated by employees who allege they have suffered a stress-induced illness. The potential for claims within industrial tribunal cases that have already been decided is also examined. Consideration is given to the hurdles that litigants will have to surmount, such as proving that their condition was in fact caused by some feature of their working conditions, showing that it was foreseeable that they would suffer a stress-based injury, and demonstrating that their employer was in some way at fault. This leads to a questioning of what employers can do to protect themselves from such claims, or at least defend them successfully. The paper points out that success is likely to depend heavily upon the quality of expert medical opinion, and also upon policy conditions that may influence those adjudicating on such cases. It is concluded that the cost of losing claims may be significant, and that employees who ignore the warning signs do so at their peril.     

Errors-in-variables regression using estimated latent variables

This note considers a method for estimating regression parameters from the data containing measurement errors using some natural estimates of the unobserved explanatory variables. It is shown that the resulting estimator is consistent not only in the usual linear regression model but also in the probit model and regression models with censoship or truncation. However, it fails to be consistent in nonlinear regression models except for special cases.