波兰表达式构成图的最大最小度

本文主要研究了波兰表达式构成图顶点的最大最小度.通过对三个扰动条件的分析计算出此图所能达到的最大度。     

对数正态分布的几个性质及其参数估计

给出对数正态分布的几个性质,分别利用矩估计法和最大似然估计法求出对数正态分布参数的点估计,并讨论其参数的区间估计。     

渭南市渭河筑堤土料工程特性试验研究

依托于渭南渭河堤防工程,对十个标段料场取样,进行工程特性试验分析,通过对土料的基本性能实验,划分土料的种类,得到土料的最大干密度和最优含水率,最终作为现场施工质量的控制指标。本文具体讨论了影响土料室内击实试验的因素,提出控制室内击实试验准确性的方法,及室内试验结果在现场施工中的应用及修正方法。     

一种基于BKF模型的双树复小波图像去噪算法

文章介绍了双树复小波变换,根据BKF模型,采用贝叶斯最大后验估计,给出了一种基于双树复小波变换的图像去噪算法。在仿真实验中,该算法与经典ProbShrink算法相比能提高峰值信噪比,改善视觉效果与去噪效果。     

四川盆地1961～2000年气温的变化分析

选取四川盆地19个地面气象站1961～2000年气温（平均气温、最高气温和最低气温）的逐日观测资料,运用最小二乘法计算气候倾向率和年代际变化的方法,对近40年来四川盆地气温的季节、年际和年代际变化进行了诊断分析,结果表明：（1）从年平均气温来看,三种气温的年平均值,四川盆地都以增温的趋势为主,增幅分别是0.027℃/10a、0.007℃/10a和0.036℃/10a,最低气温增幅大于最高气温.（2）在20世纪60、70年代气温逐渐降低,80年代是气温的低值区,80年代后期气温逐渐升高,90年代升温明显;而降水60、70年代降水量较多,但已经出现了逐渐减少的变化趋势,80年代至90年代降水量减少.（3）从季平均气温来看,春夏季三种气温呈下降趋势,其中季平均气温的下降幅度最大为-0.08℃/10a;秋冬季三种气温呈上升趋势,其中季平均最高气温的增幅最大为0.15℃/10a.     

Implementing Restricted Maximum Likelihood Estimation in Structural Equation Models

Structural equation modeling (SEM) is now a generic modeling framework for many multivariate techniques applied in the social and behavioral sciences. Many statistical models can be considered either as special cases of SEM or as part of the latent variable modeling framework. One popular extension is the use of SEM to conduct linear mixed-effects modeling (LMM) such as cross-sectional multilevel modeling and latent growth modeling. It is well known that LMM can be formulated as structural equation models. However, one main difference between the implementations in SEM and LMM is that maximum likelihood (ML) estimation is usually used in SEM, whereas restricted (or residual) maximum likelihood (REML) estimation is the default method in most LMM packages. This article shows how REML estimation can be implemented in SEM. Two empirical examples on latent growth model and meta-analysis are used to illustrate the procedures implemented in OpenMx. Issues related to implementing REML in SEM are discussed.     

Graphical Representation of Missing Data Problems

Rubin’s classic missingness mechanisms are central to handling missing data and minimizing biases that can arise due to missingness. However, the formulaic expressions that posit certain independencies among missing and observed data are difficult to grasp. As a result, applied researchers often rely on informal translations of these assumptions. We present a graphical representation of missing data mechanism, formalized in Mohan, Pearl, and Tian (2013). We show that graphical models provide a tool for comprehending, encoding, and communicating assumptions about the missingness process. Furthermore, we demonstrate on several examples how graph-theoretical criteria can determine if biases due to missing data might emerge in some estimates of interests and which auxiliary variables are needed to control for such biases, given assumptions about the missingness process.     

A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables

A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a familiar function while being only marginally less efficient than the full information ML (FIML) approach. Additional advantages of the TS approach include that it allows for easy incorporation of auxiliary variables and that it is more stable in smaller samples. The main disadvantage is that the standard errors and test statistics provided by the complete data routine will not be correct. Empirical approaches to finding the right corrections for the TS approach have failed to provide unequivocal solutions. In this article, correct standard errors and test statistics for the TS approach with missing completely at random and missing at random normally distributed data are developed and studied. The new TS approach performs well in all conditions, is only marginally less efficient than the FIML approach (and is sometimes more efficient), and has good coverage. Additionally, the residual-based TS statistic outperforms the FIML test statistic in smaller samples. The TS method is thus a viable alternative to FIML, especially in small samples, and its further study is encouraged.     

万年油对果蝇的急性与慢性毒性效应

本实验初步研究万年油对红眼果蝇的7天急性毒性效应及对红眼雌性处女蝇的22天慢性毒性效应。采用野生型黑腹红眼果蝇,在其培养基中加入浓度分别为2%、20%的万年油,以2%的未加热食用油作为阴性对照组,计算平均寿命,最高平均寿命和死亡率,作为3个毒性指标。结果显示通过急性毒性试验计算出万年油的半数致死剂量为2.86%。慢性实验结果显示,与对照组相比,2%组3个毒性指标有显著性差异;20%万年油组3个毒性指标存在极显著性差异。结果说明万年油对红眼果蝇有较强毒性,且含油量越高,其毒性效应越大。     

渔业资源的变动模型与捕捞策略

为描述鱼群中鱼量在复杂因素影响下的变动规律,建立了定量化的数学模型,并给出定率捕捞、分段减率、集中峰率等3种可操作的捕捞策略,提供了在可持续生产的条件下,寻求最大收获量及其决策数据的计算公式与搜索算法。该算法简便易行,既适用于单年生产,也适用于多年承包。最后,对各种捕捞策略做出了定性评价。