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首页> 外文会议>2009 International Institute of Applied Statistics Studies(2009 国际应用统计学术研讨会）论文集 >Estimating Index of Population Control (IPC) by Re-sampling Techniques and Its Application to Population Life Table
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Estimating Index of Population Control (IPC) by Re-sampling Techniques and Its Application to Population Life Table

机译：重采样技术估算种群控制指数及其在人口寿命表中的应用

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摘要

By the mathematical model of population trend index developed by Watt (1961, 1963), Pang & Liang (1990) conceptualized the index of population control (IPC), proposed a simple and straightforward mathematical formula calculating this index to evaluate the suppressive effect of pest management agents. But to date there is no publication available focused on its variance estimation for this index, which hinders to draw statistically sound conclusion in screening pest management agents to form pest IPM system. Taking the natural population life table of rice leaf roller (Cnaphalocrocis medinalis, Lepidoptera: Pyralidae) published by Wu, Liang, and Pang (1986) as an example, through estimating IPC and its variance via delta method and re-sampling procedures for bio-agent released and chemical insecticides dusted treatments, whether their IPC truly reflect the control effectiveness of these agents are the topics concerned in this paper. By the large sample theory delta method provides a simple approach to estimate the approximate variance for IPC, but the normality of the IPC estimates and the bias of this estimate cannot be tracked. Among four procedures used with resampling technique, the distribution of the estimates from delete-1 Jackknife does not match the normal pattern because of its small estimates available. And there is a big bias in its mean estimate. Thus, the estimates from this procedure are not applied in further analysis. After logtransformation, the distributions of the estimates from delete-d Jackknife, empirical and theoretical Bootstrap procedures match the corresponding normal patterns. Thus, it is possible using Z-test criterion to conduct hypothesis test to judge if the control agent is better than blank control at generation level. If ignoring the normality of the estimates, the low boundaries of the approximate 95% confidence intervals of delete-d Jackknife and empirical Bootstrap calculated with STD 96 . 1 mean × ± are negative. This shows that the approximate normality is not achieved for IPC estimates from delete-d Jackknife and empirical Bootstrap before logarithm transformation even though 10,000 estimates are produced. Judged by its 95% confidence intervals and the p-value from Z-test, releasing wasp is much better than blank control since its IPC is significantly less than 1 with p-value<0.05, dusting insecticide is worse than blank control but it is not statistically with p-value > 0.2 although its IPC is bigger than 1. The conclusions drawn in this paper are similar to those drawn only by the mean estimates of IPC, but our conclusions supported by statistic principles are more plausible and dependable.
机译：通过Watt（1961，1963）开发的种群趋势指数数学模型，Pang＆Liang（1990）概念化了种群控制指数（IPC），提出了一个简单直接的数学公式来计算该指数以评估害虫的抑制作用。管理代理商。但是迄今为止，尚无出版物致力于该指数的方差估计，这阻碍了在筛选有害生物管理剂以形成有害生物IPM系统时得出统计上合理的结论。以Wu，Liang和Pang（1986）出版的稻纵卷叶natural自然种群生活表（Cnaphalocrocis medinalis，鳞翅目：Pyralidae）为例，通过三角洲方法估算IPC及其方差，并通过生物采样的重新采样程序本文关注的主题是释放的化学杀虫剂和化学杀虫剂除尘剂，其IPC是否真正反映了这些杀虫剂的控制效果。通过大样本理论，增量法提供了一种简单的方法来估计IPC的近似方差，但是无法跟踪IPC估计的正态性和该估计的偏差。在与重采样技术一起使用的四个过程中，来自delete-1折刀的估计值分布与正常模式不匹配，因为它的可用估计值很小。而且其均值估计存在很大偏差。因此，此过程的估计值不应用于进一步分析。对数转换后，delete-d Jackknife，经验和理论Bootstrap过程的估计值分布与相应的正态分布匹配。因此，有可能使用Z检验标准进行假设检验，以判断控制剂在世代水平上是否优于空白对照。如果忽略估计的正态性，则使用STD 96计算出delete-d折刀和经验Bootstrap的大约95％置信区间的低边界。 1个平均值×±均为负。这表明对数转换之前，对于deletec d折刀和经验Bootstrap的IPC估计值，即使产生了10,000个估计值，也无法达到近似正态性。根据其95％的置信区间和Z检验的p值判断，释放黄蜂优于空白对照，因为其IPC显着小于1，p值<0.05，除尘杀虫剂比空白对照差，但尽管IP值大于1，但p值> 0.2时没有统计学意义。本文得出的结论与仅由IPC的均值估算得出的结论相似，但我们的结论受统计原理的支持更为合理和可靠。

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