美国的国际服务贸易统计

美国的国际服务贸易统计国家统计局赴美培训团美国作为服务贸易自由化的倡导者和世界上服务贸易额最大的国家，它的国际服务贸易的发展速度已经超过了货物贸易的增速。据负责国际服务贸易统计工作的美国商务部经济分析局介绍，多年来美国货物贸易一直处于进大于出的逆差状...     

中国-东盟自贸区建成后广西最先尝到“甜头”

核心提示 还有不到1个多月的时间，中国-东盟自由贸易区（以下简称自贸区）将如期建成。这个拥有世界上消费者最多和覆盖面积最大的经济一体化大市场建成之后是个什么样子？自贸区给广西和东盟各国带来什么样的影响和机遇？区域内的企业和商家都能享受到什么实惠？广西作为自贸区的桥头堡，自贸区的建成，广西老百姓能从中得到什么好处和实惠，人们未来的生活会有哪些变化？     

现代人花钱买什么?

在这个不断发展的社会里，金钱越来越多的介入我们的生活。金钱对人们来说，不仅仅是刷刷响的纸币，更多地是一种感觉。过去金钱欲望曾受压抑的中国人，如今在经济社会转型的时代，又以什么态度去看待金钱？在眼下处处要用钱的环境中，人们又以什么眼光去看待这个对我们生活非常重要的尤物呢？在人们生活水平日益提高，不断追求生活质量的时代，现代人花钱买什么？对此，赤峰市城调队进行了专门的调查，调查情况如下： 一、花钱买时间 随着经济的发展，收入的不断增长，居民的生活水平不断提高，人们不再为温饱问题发愁、奔波。随着人们生活…     

混合动力车在中国具有巨大的市场潜力

中国预期会在十年内成为全球最大的汽车市场，但汽车行业的不断壮大也会不司避免地带来严峻的环境问题。究竟该如何协调行业发展和环境保护之间的矛盾？世界领先市场研究咨询公司TNS中国最新调研揭示，混合动力汽车有望成为中国内地解决汽车行业污染环境问题的领头羊。     

世贸谈判:美国对中国的要价究竟有多高

中国总理朱钅容基访美日程已经结束，他对美国总统克林顿迫于压力不同意中国即时加入世贸非常不满，并在其它场合不断地提醒美国人不要“要价太高”！那么美国到底在此次贸易谈判中，开出什么样的天价呢？据美国媒体１９９９年４月８日公布的《联合声明》及其三个附件中，开列中国加入世贸后市场开放清单是：电讯业：六年内取消传呼机、流动电话进口，及固定电话服务的地域限制；四年内准外资在所有电讯领域中持有四成九股权，在增值服务及传呼服务领域更可持５１％的控股权。保险业：一年后外资可持有合资寿险公司５１％股权；一般保险和再…     

透视中美经济

国家主席胡锦涛今年初的美国之行被美国媒体评价为：打开了两国合作的新篇章。中美之间的经贸关系正迎来新一轮的发展机遇。单是此次访美期间中国向美国采购的产品总额就高达450亿美元，对美国经济复苏起到了积极作用。中国正走在通向崛起的路途上，美国也面临着经济复苏的机遇和挑战。     

华尔街难破的“泡沫”

美国对冲基金接连出事后，全球金融形势发生了根本性的逆转。人们突然发现，美国是世界上金融震荡最大的策源地。日前所披露的美国长期投资公司LTCM在全球金融市场上，特别是通过定息证券所使用的惊人杠杆比率，令人联想到美国铁幕中可怕的情形，但那只是惊鸿一瞥，更大的...     

美汽车生产与消费的比较

一、中美汽车生产比较中国是世界上最大的发展中国家,美国是世界上最大的发达国家。由于工业基础及科学技术发展水平不同等原因,中美两国汽车工业的发展水平也相差甚远。从本世纪初起,美国就一直是世界头号汽车消费大国和重要的生产大国。而中国的汽车工业始于５０年代。经过４０多年的发展、建设,中国汽车工业从无到有,产品趋于多样化。特别是改革开放以来,汽车工业得到了很大的发展。但和美国汽车业相比,中国汽车工业还是一个“幼稚产业”。（一）汽车生产规模合理的经营规模是利润最大化的必要条件。从世界汽车工业发展的状况来看…     

关于建立高技术统计范畴的探讨

关于建立高技术统计范畴的探讨《吉林省高技术统计研究》课题组一、关于高技术统计范畴的认识“高技术”一词，源于美国。高技术领域的形成在２０世纪中叶。高技术是一个相对、发展的概念，由于人们所处的服务部门和所从事的工作不同，在认识和使用高技术概念上也不尽一致...     

我国统计改革的突破口究竟在哪里

我国统计改革的突破口究竟在哪里文／浙江经济高等专科学校贸易经济系马建立随着社会主义市场经济的不断发展和完善，人们对统计的要求越来越高，而当前的统计现状却远远不能满足人们的要求，中国统计应该怎样适应社会主义市场经济的发展？统计改革的突破口究竟在哪里？这...     

Fast tensorial JADE

We propose a novel method for tensorial‐independent component analysis. Our approach is based on TJADE and k‐JADE, two recently proposed generalizations of the classical JADE algorithm. Our novel method achieves the consistency and the limiting distribution of TJADE under mild assumptions and at the same time offers notable improvement in computational speed. Detailed mathematical proofs of the statistical properties of our method are given and, as a special case, a conjecture on the properties of k‐JADE is resolved. Simulations and timing comparisons demonstrate remarkable gain in speed. Moreover, the desired efficiency is obtained approximately for finite samples. The method is applied successfully to large‐scale video data, for which neither TJADE nor k‐JADE is feasible. Finally, an experimental procedure is proposed to select the values of a set of tuning parameters. Supplementary material including the R‐code for running the examples and the proofs of the theoretical results is available online.     

Fast and robust bootstrap

In this paper we review recent developments on a bootstrap method for robust estimators which is computationally faster and more resistant to outliers than the classical bootstrap. This fast and robust bootstrap method is, under reasonable regularity conditions, asymptotically consistent. We describe the method in general and then consider its application to perform inference based on robust estimators for the linear regression and multivariate location-scatter models. In particular, we study confidence and prediction intervals and tests of hypotheses for linear regression models, inference for location-scatter parameters and principal components, and classification error estimation for discriminant analysis.     

Fast Censored Linear Regression

Weighted log‐rank estimating function has become a standard estimation method for the censored linear regression model, or the accelerated failure time model. Well established statistically, the estimator defined as a consistent root has, however, rather poor computational properties because the estimating function is neither continuous nor, in general, monotone. We propose a computationally efficient estimator through an asymptotics‐guided Newton algorithm, in which censored quantile regression methods are tailored to yield an initial consistent estimate and a consistent derivative estimate of the limiting estimating function. We also develop fast interval estimation with a new proposal for sandwich variance estimation. The proposed estimator is asymptotically equivalent to the consistent root estimator and barely distinguishable in samples of practical size. However, computation time is typically reduced by two to three orders of magnitude for point estimation alone. Illustrations with clinical applications are provided.     

Fast simulation of truncated Gaussian distributions

We consider the problem of simulating a Gaussian vector X, conditional on the fact that each component of X belongs to a finite interval [a _i ,b _i ], or a semi-finite interval [a _i ,+??). In the one-dimensional case, we design a table-based algorithm that is computationally faster than alternative algorithms. In the two-dimensional case, we design an accept-reject algorithm. According to our calculations and numerical studies, the acceptance rate of this algorithm is bounded from below by 0.5 for semi-finite truncation intervals, and by 0.47 for finite intervals. Extension to three or more dimensions is discussed.     

农业及粮食安全问题

一、农业安全是经济安全的基础农业安全是指农业能基本满足社会日益增长的食品需求 ,具有较强的竞争能力和创收能力 ,处于可持续发展状态。农业不安全是指农业不能够提供社会需要的初级产品 ,或无力抵御外界农产品的竞争而处于市场萎缩和收入下降的状态。从理论上讲 ,农业是国民经济的基础 ,这决定了农业安全是经济安全的基础。农业是我们的衣食之源、生存之本 ;农业是工业原料的来源并为工业发展提供积累 ;农民的收入主要来源于农业并成为工业产品的重要购买力。农业出了问题 ,整个国民经济肯定会出问题。但是 ,随着经济的发展 ,特别是工业…     

劳动力转移与粮食安全

中国快速城市化和工业化导致的大量农村劳动力向城市转移引起了决策者和学术界对粮食安全问题的担忧,但本文利用县级和农户面板数据研究发现：首先,即使到2010年,农村劳动力转移对粮食总产量的影响并不大,对主产区的粮食总产量的影响更小,这背后的机制是主产区农户会通过更多地增加其他农业生产要素来替代劳动力投入的减少;其次,劳动力转移对主产区和非主产区农户的粮食生产行为的影响以及对主要粮食作物和次要粮食作物的影响都有所不同。总之,农村劳动力迁移尚未严重威胁到中国的粮食安全,当然,政府应针对粮食主产区和非主产区实施不同的政策以保持粮食总产量的稳定,特别是要鼓励主产区的耕地流转以降低劳动力迁移的负面影响。     

Fast nonparametric classification based on data depth

A new procedure, called D D α-procedure, is developed to solve the problem of classifying d-dimensional objects into q ≥ 2 classes. The procedure is nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0,1] ^q . Specifically, the depth is the zonoid depth, and the algorithm is the α-procedure. In case of more than two classes several binary classifications are performed and a majority rule is applied. Special treatments are discussed for ‘outsiders’, that is, data having zero depth vector. The D Dα-classifier is applied to simulated as well as real data, and the results are compared with those of similar procedures that have been recently proposed. In most cases the new procedure has comparable error rates, but is much faster than other classification approaches, including the support vector machine.     

Fast covariance estimation for sparse functional data

Smoothing of noisy sample covariances is an important component in functional data analysis. We propose a novel covariance smoothing method based on penalized splines and associated software. The proposed method is a bivariate spline smoother that is designed for covariance smoothing and can be used for sparse functional or longitudinal data. We propose a fast algorithm for covariance smoothing using leave-one-subject-out cross-validation. Our simulations show that the proposed method compares favorably against several commonly used methods. The method is applied to a study of child growth led by one of coauthors and to a public dataset of longitudinal CD4 counts.