川西化杀杂种小麦的产量优势与产量因素优势分析

分析了川西化杀杂种小麦产量优势与产量因素优势。结果表明 :(1)稀植条件下产量中亲优势与各产量因素中亲优势呈显著 (极显著 )正相关 ,以生物产量、穗粒重与穗粒数的中亲优势尤为密切。在亲本选用上应注意生物产量、穗粒重、穗粒数几个性状。 (2 )不同亲本材料的选用对杂种小麦产量因素超标优势表现有影响。 (3)稀植条件下 ,强优势组合的产量超标优势是在穗、粒、重各因素协调提高下 ,具有较高的生物产量优势与穗粒重 (穗粒数 )优势、或穗数和穗粒数优势的结果。 (4)密植条件下 ,产量超标优势主要来自于穗粒数与千粒重优势 ,而以穗粒数优势占主导作用。 (5 )单株稀植条件下的各产量因素超标杂种优势大于群体密植条件下的超标杂种优势。 (6 )产量超标优势与穗数超标优势在稀、密植条件下的相关性不显著 ,而穗粒数超标优势与千粒重超标优势在两种条件下达极显著相关。研究认为 ,目前川西化杂杂种小麦的选育应在川麦 2 8的基础上 ,稳定穗数与千粒重 ,选育生物产量与穗粒数大的组合     

A Comparison of Some Methods for the Selection of a Common Eigenvector Model for the Covariance Matrices of Two Groups

Two new nonparametric common principal component model selection procedures based on bootstrap distributions of the vector correlations of all combinations of the eigenvectors from two groups are proposed. The performance of these methods is compared in a simulation study to the two parametric methods previously suggested by Flury in 1988, as well as modified versions of two nonparametric methods proposed by Klingenberg in 1996 and then by Klingenberg and McIntyre in 1998. The proposed bootstrap vector correlation distribution (BVD) method is shown to outperform all of the existing methods in most of the simulated situations considered.     

In-Sample Inference and Forecasting in Misspecified Factor Models

This article considers in-sample prediction and out-of-sample forecasting in regressions with many exogenous predictors. We consider four dimension-reduction devices: principal components, ridge, Landweber Fridman, and partial least squares. We derive rates of convergence for two representative models: an ill-posed model and an approximate factor model. The theory is developed for a large cross-section and a large time-series. As all these methods depend on a tuning parameter to be selected, we also propose data-driven selection methods based on cross-validation and establish their optimality. Monte Carlo simulations and an empirical application to forecasting inflation and output growth in the U.S. show that data-reduction methods outperform conventional methods in several relevant settings, and might effectively guard against instabilities in predictors’ forecasting ability.     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

Dynamic factor structure of team performances in Liga MX

Team performance of the Mexican Football League (Liga MX), measured as the percentage of the total points obtained during each short tournament, is analyzed using Dynamic Factor Models (DFMs). The estimation of the common components is carried out with Principal Components and the stochastic nature of the DFM is studied through Panel Analysis of Non-stationarity in Idiosyncratic and Common Components. The results reveal that there are two common factors, one being possibly non-stationary. These factors show an interesting dynamic behavior in the league and allow to split the teams into two groups, namely, top competitors and emerging or relegated teams. Some discussion is given in this direction.     

基金分离下中国股市交易量模型的实证研究

交易量是市场投资者交易的直接产物 ,包含了市场和投资者投资行为的众多特性 ,因此逐渐成为金融实务界和理论界关注的热点 .本文从经典的基金分离假设出发 ,讨论了交易量的理论模型 .通过主成分分析的方法 ,检验了中国股市的交易量模型 ,并进一步分析了交易量变化的基本特性     

基于提前期的多阶通用件库存模型

针对单个企业内部应用通用件的环境,在假定一个多阶生产系统的基础上,对应用通用件的库存量水平及其成本进行了分析,建立了多阶通用件库存模型,提出通过对采用通用件和不采用通用件的成本差异的比较,来决策多阶生产系统中在哪一阶工序采用通用件,并求解出每一阶工序优化的基本库存水平。     

上市公司“庄股跳水”预测模型的实证分析

预防"庄股跳水"是投资者在中国股市中生存的必修课,同时也是股市行为研究的难点之一.本文选取2000年到2003年深市遭遇跳水行情的股票及与之相对应的非跳水股票各31只股票为样本,运用t检验、判别分析和主成分分析等多种计量方法和模型对两类股票的各种重要指标进行了详细分析、比较及预测.实证研究发现两类股票的各种重要指标存在重大差异,并且模型能够以较高的准确率预测"庄股跳水".     

Growth and Heat Resistance Kinetic Variation Among Various Isolates of Salmonella and its Application to Risk Assessment

The abilities of cells of a particular type of bacteria to leave lag phase and begin the process of dividing or surviving heat treatment can depend on the serotypes or strains of the bacteria. This article reports an investigation of serotype-specific differences in growth and heat resistance kinetics of clinical and food isolates of Salmonella. Growth kinetics at 19 degrees C and 37 degrees C were examined in brain heart infusion broth and heat resistance kinetics for 60 degrees C were examined in beef gravy using a submerged coil heating apparatus. Estimates of the parameters of the growth curves suggests a small between-serotype variance of the growth kinetics. However, for inactivation, the results suggest a significant between-serotype effect on the asymptotic D-values, with an estimated between-serotype CV of about 20%. In microbial risk assessment, predictive microbiology is used to estimate growth and inactivation of pathogens. Often the data used for estimating the growth or inactivation kinetics are based on measurements on a cocktail--a mixture of approximately equal proportions of several serotypes or strains of the pathogen being studied. The expected growth or inactivation rates derived from data using cocktails are biased, reflecting the characteristics of the fastest growing or most heat resistant serotype of the cocktail. In this article, an adjustment to decrease this possible bias in a risk assessment is offered. The article also presents discussion of the effect on estimating growth when stochastic assumptions are incorporated in the model. In particular, equations describing the variation of relative growth are derived, accounting for the stochastic variations of the division of cells. For small numbers of cells, the expected value of the relative growth is not an appropriate "representative" value for actual relative growths that might occur.