耐用消费品的逐年统计实时预测方法

本文介绍一种耐用消费品市场的预测方法。该方法利用家庭开支的最优效益原理,因而可以避免在市场引入竞争机制而耐用消费品又非每家每户平均消耗的特定条件下,单纯利用趋势外推预测可能导致的失误。文中还介绍了此法的具体应用。     

解析几何中的轨迹问题

本文举例说明各种轨迹问题的解法,并对参数解法的合理性给以证明.     

用光学仪器测量表面粗糙度参数的微机处理方法

本文利用ＢＡＳＩＣ语言编制了一套应用程序，可利用光切显微镜实测的数据，得到国家标准规定的六个参数。     

智力资源的两个特殊的思维模式——关于形象思维有限量问题的探索

以现代认知科学与思维科学为背景,通过对形象思维有限量化问题中的G·米勒参数和A·西蒙参数进行比较和分析,建构出形象思维有限量化Ⅰ、Ⅱ级模式,并指出了相应的应用前景.     

Small-Sample Comparisons for Goodness-of-Fit Statistics in One-Way Multinomials with Composite Hypotheses

The small-sample behaviour of power-divergence goodness-of-fit statistics with composite hypotheses was evaluated with multinomial models of up to five cells and up to three parameters. Their performance was assessed by comparing asymptotic test sizes with exact test sizes obtained by enumeration in the near right tail, where 1-?∈?(0.90,?0.95], and in the far right tail, where 1-?∈?(0.95,?0.99]. The study addressed all combinations of power-diparse JAS312HH01.sgmvergence estimates of indices ν?∈?{-1/2,?0,?1/3,?1/2,?2/3,?1,?3/ 2} and power-divergence statistics of indices λ?∈?{-1/2,?0,?1/3,?1/2,?2/3,?1,?3/2}. The results indicate that the asymptotic approximation is sufficiently accurate (by the criterion that the average exact size is no larger than ±10% of the nominal asymptotic test size) in the near right tail when ν=0 and λ=1/2, and in the far right tail when ν=0 and λ=1/3, in both cases providing that the smallest expectation in the composite hypothesis exceeds 5. The only exception to this rule is the case of models that render a near-equiprobable composite hypothesis on the boundaries of the parameter space, where average exact sizes are usually quite different from nominal sizes despite the fact that the smallest expectation in these conditions is usually well above 5.     

稀土氨基酸在混合溶剂中的配位常数测定及热力学常数计算

用ｐＨ法测定了镧和天门冬氨酸在水—二甲基亚砜、钕和甘氨酸在水—二氧六环混合溶剂中的配位常数．测定精度为±０．０１ｐＨ单位．通过加入一定量硝酸钾溶液维持溶液的离子强度（０．１０ｍｏｌ／Ｌ）．测定时采用氮气氛保护并保持温度变化不超过±０．２Ｋ．利用配位常数计算了这些配合物在混合溶液中的△Ｇ°、△Ｈ°和△Ｓ°．     

New honorary member of the statistical society of Canada

Approximations to exact conditional inference for location familles are considered. Methods which improve the standard normal and chi-squared approximations to the conditional distributions of pivots arising in standard large-sample theory are discussed, including the use of parameter transformations for parametrization-dependent pivots, and the use of scaling factors for the likelihood-ratio statistic. The methods are illustrated and compared in a series of examples.     

A remark on self-similar processes with stationary increments

The upper bound of the parameter of self-similar processes with stationary increments is given in terms of the moment condition.     

基于极限环法的PID快速自整定的一种实现

探讨了基于极限环法的ＰＩＤ在线快速自整定理论和实现问题,提出采用满足度－零度继电特性生成极限环,并应用自振荡自适应理论和离散Ｆｏｕｒｉｅｒ级数变换滤波算法进行临界参数估计,还引入自适应预调点概念处理自整定的安全性问题。     

Estimation of the Predictive Ability of Ecological Models

The conventional criteria for predictive model selection do not indicate the absolute goodness of models. For example, the quantity of Akaike Information Criterion (AIC) has meanings only when we compare AIC of different models for a given amount of data. Thus, the existing criteria do not tell us whether the quantity and quality of data is satisfactory, and hence we cannot judge whether we should collect more data to further improve the model or not. To solve such a practical problem, we propose a criterion R_D that lies between 0 and 1. R_D is an asymptotic estimate of the proportion of improvement in the predictive ability under a given error structure, where the predictive ability is defined by the expected logarithmic probability by which the next dataset (2nd dataset) occurs under a model constructed from the current dataset (1st dataset). That is, the predictive ability is defined by the expected logarithmic probability of the 2nd dataset evaluated at the model constructed from the 1st dataset. Appropriate choice of error structures is important in the calculation of R_D. We illustrate examples of calculations of R_D by using a small dataset about the moth abundance.