<Emphasis Type="Italic">L</Emphasis><Subscript>1</Subscript> linear interpolator for missing values in time series

We propose a minimum mean absolute error linear interpolator (MMAELI), based on theL ₁ approach. A linear functional of the observed time series due to non-normal innovations is derived. The solution equation for the coefficients of this linear functional is established in terms of the innovation series. It is found that information implied in the innovation series is useful for the interpolation of missing values. The MMAELIs of the AR(1) model with innovations following mixed normal andt distributions are studied in detail. The MMAELI also approximates the minimum mean squared error linear interpolator (MMSELI) well in mean squared error but outperforms the MMSELI in mean absolute error. An application to a real series is presented. Extensions to the general ARMA model and other time series models are discussed. This research was supported by a CityU Research Grant and Natural Science Foundation of China.     

区域技术创新系统评估体系的研究

技术创新对提升企业竞争力、提高综合国力、促进经济增长和国家持续发展非常重要。本在研究了区域经济发展和国家创新系统的相关献基础上，建立了系统、量化的区域技术创新系统评估指标体系，提出了决定区域创新系统技术创新能力的主要因素，并用TOPSIS方法对指标的量化进行了尝试。     

Solving Nonlinear Programming Problems with Noisy Function Values and Noisy Gradients

An efficient algorithm for solving nonlinear programs with noisy equality constraints is introduced and analyzed. The unknown exact constraints are replaced by surrogates based on the bundle idea, a well-known strategy from nonsmooth optimization. This concept allows us to perform a fast computation of the surrogates by solving simple quadratic optimization problems, control the memory needed by the algorithm, and prove the differentiability properties of the surrogate functions. The latter aspect allows us to invoke a sequential quadratic programming method. The overall algorithm is of the quasi-Newton type. Besides convergence theorems, qualification results are given and numerical test runs are discussed.     

Equality and inequality constrained optimization algorithms with convergent stepsizes

In this paper, we consider two algorithms for nonlinear equality and inequality constrained optimization. Both algorithms utilize stepsize strategies based on differentiable penalty functions and quadratic programming subproblems. The essential difference between the algorithms is in the stepsize strategies used. The objective function in the quadratic subproblem includes a linear term that is dependent on the penalty functions. The quadratic objective function utilizes an approximate Hessian of the Lagrangian augmented by the penalty functions. In this approximation, it is possible to ignore the second-derivative terms arising from the constraints in the penalty functions.The penalty parameter is determined using a strategy, slightly different for each algorithm, that ensures boundedness as well as a descent property. In particular, the boundedness follows as the strategy is always satisfied for finite values of the parameter.These properties are utilized to establish global convergence and the condition under which unit stepsizes are achieved. There is also a compatibility between the quadratic objective function and the stepsize strategy to ensure the consistency of the properties for unit steps and subsequent convergence rates.This research was funded by SERC and ESRC research contracts. The author is grateful to Professors Laurence Dixon and David Mayne for their comments. The numerical results in the paper were obtained using a program written by Mr. Robin Becker.     

Functional Central Limit Theorems for Triangular Arrays of Function-Indexed Processes under Uniformly Integrable Entropy Conditions

Functional central limit theorems for triangular arrays of rowwise independent stochastic processes are established by a method replacing tail probabilities by expectations throughout. The main tool is a maximal inequality based on a preliminary version proved by P. Gaenssler and Th. Schlumprecht. Its essential refinement used here is achieved by an additional inequality due to M. Ledoux and M. Talagrand. The entropy condition emerging in our theorems was introduced by K. S. Alexander, whose functional central limit theorem for so-calledmeasure-like processeswill be also regained. Applications concern, in particular, so-calledrandom measure processeswhich include function-indexed empirical processes and partial-sum processes (with random or fixed locations). In this context, we obtain generalizations of results due to K. S. Alexander, M. A. Arcones, P. Gaenssler, and K. Ziegler. Further examples include nonparametric regression and intensity estimation for spatial Poisson processes.     

光谱复杂的稀土基体中稀土杂质ICP光谱测定的一些问题

ICP激发光源以其独特的功能使ICP/AES技术在稀土分析中的应用日益广泛,在一定程度上取代了经典的直流电弧光谱法,但应指出,由于常规雾化器的低雾化效率(≤5％)和试样的高倍稀释,ICP/AES技术的实际检测能力的改善并不明显,本文用ICP光谱法测定了     

Interval estimation of the critical value in a general linear model

Summary This paper concerns interval estimation of the critical value θ which satisfies under the general linear model,Y _i =μ(x _i )+ε _i (i=1,2,···), where for and the functional forms off _j ^′ s are known. From an asymptotic expansion it is shown that, under reasonable conditions, the limiting distribution of is normal. Thus in the large-sample case a confidence interval for θ can be obtained. Such a result is useful when one is interested in carrying out a retrospective analysis rather than designing the experiment (as in the Kiefer-Wolfowitz procedure). In Section 3 a sequential procedure is considered for confidence intervals with fixed width 2d. It is shown that, for a given stopping variableN, is also asymptotically normal asd→0. Thus the coverage probability converges to 1−α (preassigned) asd→0. An example of application in estimating the phase parameter in circadian rhythms is given for the purpose of illustration. Research partially supported by the NSF Grant DMS-8502346.     

芯片式流通池顺序注射可更新表面反射光谱法用于酶反应检测

将芯片式流通池顺序注射可更新表面反射光谱法用于酶反应检测。HRP催化H2O2氧化BPR底物的反应用于对H2O2的检测。此反应体系与葡萄糖氧化酶联用，用于对血清中葡萄糖的检测。     

A multisyringe flow-through sequential extraction system for on-line monitoring of orthophosphate in soils and sediments

A fully automated flow-through microcolumn fractionation system with on-line post-extraction derivatization is proposed for monitoring of orthophosphate in solid samples of environmental relevance. The system integrates dynamic sequential extraction using 1.0 mol l⁻¹ NH₄Cl, 0.1 mol l⁻¹ NaOH and 0.5 mol l⁻¹ HCl as extractants according to the Hieltjes-Lijklema (HL) scheme for fractionation of phosphorus associated with different geological phases, and on-line processing of the extracts via the Molybdenum Blue (MB) reaction by exploiting multisyringe flow injection as the interface between the solid containing microcolumn and the flow-through detector. The proposed flow assembly, capitalizing on the features of the multicommutation concept, implies several advantages as compared to fractionation analysis in the batch mode in terms of saving of extractants and MB reagents, shortening of the operational times from days to hours, highly temporal resolution of the leaching process and the capability for immediate decision for stopping or proceeding with the ongoing extraction. Very importantly, accurate determination of the various orthophosphate pools is ensured by minimization of the hydrolysis of extracted organic phosphorus and condensed inorganic phosphates within the time frame of the assay. The potential of the novel system for accommodation of the harmonized protocol from the Standards, Measurement and Testing (SMT) Program of the Commission of the European Communities for inorganic phosphorus fractionation was also addressed. Under the optimized conditions, the lowest detectable concentration at the 3σ level was ≤0.02 mg P l⁻¹ for both the HL and SMT schemes regardless of the extracting media. The repeatability of the MB assay was better than 2.5% and the dynamic linear range extended up to 7.0 mg P l⁻¹ in NH₄Cl and NaOH media and 15 mg P l⁻¹ whenever HCl is utilized as extractant for both the HL and SMT protocols.     

我国区域绿色技术创新效率的分类测度和提升模式研究——基于非期望产出的SBM-SupSBM模型

本文首先运用考虑非期望产出的SBM-SupSBM模型估计我国各省市绿色技术创新效率并进行分类:稳定上升类、平稳类、大幅度波动类以及下降类。之后从企业内部和外部两方面对绿色技术创新效率提升的影响因素提出假设,着重考虑大幅度波动类别省份的效率提升。运用面板数据模型各影响因素进行验证,结论显示:企业规模对绿色技术创新效率波动较大的省份起到显著的抑制作用,环境规制和技术进步对绿色技术创新效率波动较大的省份作用不明显。针对分析结果,提出结论:在提升绿色技术创新效率的过程中,应注重企业规模和技术进步的协同作用,以及技术的开放程度。