大力发展农产品加工业提高农业市场竞争力

加入WTO后,我省的农业结构调整进入了根本性变革的新阶段,除从农业内部着手外,更需要从农业之外寻找出路.做大做强农产品加工业将提高我省农产品竞争能力,农产品加工业的大发展将担负起优化结构,增加收入的历史重任.而要发展农产品加工业,必须实现六个方面的突破.     

大数据和企业精准营销相关性分析

对大数据和企业精准营销相关性的分析能够为精准营销的实施提供基础和技术平台,为企业对大数据的管理提供一定的方向,将很大程度影响企业的竞争力和发展。在拟定大数据和精准营销指标体系基础上,通过对黑龙江省服务业、商业企业、制造业和现代农业企业进行问卷调查,运用结构方程模型分析其相关性。分析结果显示,大数据与精准营销具有显著相关性,客户数据挖掘对大数据具有显著影响,精准广告投放对精准营销具有显著影响。据此指出,企业应当充分利用大数据技术,注重客户数据挖掘,提高营销的精准性,使其能适应市场竞争带来的机遇与挑战。     

接点治理：论精准扶贫过程中的“村民评议”——对湘西B村的个案研究

作为深入乡土社会的“事件”,精准扶贫触发了国家政权和乡土社会之间的分歧。在数字化治理技术与乡土生活模糊性之间、国家正式权力与农村内生秩序之间、“区分逻辑”与乡土社会“平均主义”之间,两者存在明显差异。面对分歧,农村基层在精准扶贫过程中采取“村民评议”制度形成“接点治理”格局。研究发现,村民评议形成的接点治理主要包括以下治理机制：以熟人社会构成治理的信息机制,以多元主体参与构成治理的权威机制,以协商讨论构成治理的合法化机制。这一制度创造了新型制度场域和治理接点,有利于实现国家政权与乡土社会之间的融合。推进对湘西B村“村民评议”的个案分析,发掘其中的治理机制,完善其中存在的不足,实现从接点分离到接点融合,推进基层社会的有效治理。     

精准扶贫的资源配置逻辑与实践困境

扶贫资源的合理配置是确保精准扶贫战略目标顺利实现的关键所在。然而,当前精准扶贫资源在配置的过程中存在着资源的项目化与社会生活的不规则性、政策执行的科层逻辑之间的张力。这一巨大的张力使极具科学性和合法性的程序受到非正式制度的倒逼,从而产生“反科层”的逻辑,进而使精准扶贫资源的配置面临实践的困境。要走出这种困境,精准扶贫资源配置应着力于增强资源配置的灵活性、增强贫困人口自身能力建设和因地制宜地发掘地方优势资源,以激发扶贫对象为主体的内生动力。     

Testing Inference in Inflated Beta Regressions under Model Misspecification

We consider testing inference in inflated beta regressions subject to model misspecification. In particular, quasi-z tests based on sandwich covariance matrix estimators are described and their finite sample behavior is investigated via Monte Carlo simulations. The numerical evidence shows that quasi-z testing inference can be considerably more accurate than inference made through the usual z tests, especially when there is model misspecification. Interval estimation is also considered. We also present an empirical application that uses real (not simulated) data.     

Adjustment for nonresponse with variables from different sources: Bias correction and precision loss,with application to the Swiss European Social Survey 2012

ABSTRACT

Adjustment for nonresponse should reduce the nonresponse bias without decreasing the precision of the estimates. Adjustment for nonresponses are commonly based on socio-demographic variables, although these variables may be poorly correlated with response propensities and with variables of interest. Such variables nevertheless have the advantage of being available for all sample units, whether or not they are participating in the survey. Alternatively, adjustment for nonresponse can be obtained from a follow-up survey aimed at sample units which did not participate in the survey and from which the variables are designed to be correlated with response propensities. However, information collected through these follow-up surveys is not available for people in the sample who participated neither in the survey nor in its nonresponse follow-up. These two sets of variables when used in a nonresponse model for the Swiss European Social Survey 2012 differ only slightly with regard to their effect on bias correction and on the precision of estimates. The variables from the follow-up are performing slightly better. In both cases, the adjustment for nonresponse performs poorly.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

高精度局域定向定位技术及其精度分析

针对目前自主局域定向定位的需求,文中提出了一种在近场模型下反向利用阵列信号处理相关理论实现阵列自身的高精度定向定位方法,仿真实验表明该方法可以有效实现阵列的高精度定向定位.进一步对该方法的定向定位精度进行了理论分析,通过仿真分析了阵列所处位置、信号源数目、阵列自身天线阵元数目以及信号源位置存在误差时对定向定位精度的影响,相关实验结论具有重要的工程应用指导意义.     

COMPARATIVE CALIBRATION WITH SUBGROUPS

The main object of this paper is to consider structural comparative calibration models under the assumption that the unknown quantity being measured is not identically distributed for all units. We consider the situation where the mean of the unknown quantity being measured is different within subgroups of the population. Method of moments and maximum likelihood estimators are considered for estimating the parameters in the model. Large sample inference is facilitated by the derivation of the asymptotic variances. An application to a data set which indeed motivated the consideration of such general model and was obtained by measuring the heights of a group of trees with five different instruments is considered.