• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Dose-Response >Optimal Design for Estimating Parameters of the 4-Parameter Hill Model
【2h】

Optimal Design for Estimating Parameters of the 4-Parameter Hill Model

机译：四参数希尔模型参数估计的优化设计

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Many drug concentration-effect relationships are described by nonlinear sigmoid models. The 4-parameter Hill model, which belongs to this class, is commonly used. An experimental design is essential to accurately estimate the parameters of the model. In this report we investigate properties of D-optimal designs. D-optimal designs minimize the volume of the confidence region for the parameter estimates or, equivalently, minimize the determinant of the variance-covariance matrix of the estimated parameters. It is assumed that the variance of the random error is proportional to some power of the response. To generate D-optimal designs one needs to assume the values of the parameters. Even when these preliminary guesses about the parameter values are appreciably different from the true values of the parameters, the D-optimal designs produce satisfactory results. This property of D-optimal designs is called robustness. It can be quantified by using D-efficiency. A five-point design consisting of four D-optimal points and an extra fifth point is introduced with the goals to increase robustness and to better characterize the middle part of the Hill curve. Four-point D-optimal designs are then compared to five-point designs and to log-spread designs, both theoretically and practically with laboratory experiments.D-optimal designs proved themselves to be practical and useful when the true underlying model is known, when good prior knowledge of parameters is available, and when experimental units are dear. The goal of this report is to give the practitioner a better understanding for D-optimal designs as a useful tool for the routine planning of laboratory experiments.
机译：非线性乙状结肠模型描述了许多药物浓度-效应关系。通常使用此类的4参数Hill模型。实验设计对于准确估算模型参数至关重要。在此报告中，我们研究了D最佳设计的属性。 D最优设计可最小化参数估计的置信区域的体积，或者等效地，最小化估计参数的方差-协方差矩阵的行列式。假定随机误差的方差与响应的某些幂成比例。为了产生D最优设计，需要假设参数的值。即使有关参数值的这些初步猜测与参数的真实值明显不同，D最佳设计仍可得出令人满意的结果。 D最佳设计的这种特性称为鲁棒性。可以通过D效率进行量化。引入了由四个D最佳点和一个额外的第五点组成的五点设计，目的是提高鲁棒性并更好地表征Hill曲线的中间部分。然后将四点D最优设计与五点设计和对数展开设计进行比较，无论是在理论上还是在实验室实验中，在实际实验中，D最优设计都证明了它们的实用性和实用性。在没有实验单元的情况下，可以获得很好的参数先验知识。本报告的目的是使从业人员更好地理解D最优设计，将其作为实验室实验常规计划的有用工具。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号