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首页> 外文期刊>Journal of pharmacokinetics and biopharmaceutics >A comparison of methods for estimating individual pharmacokinetic parameters.
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A comparison of methods for estimating individual pharmacokinetic parameters.

机译：估计各个药代动力学参数的方法的比较。

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摘要

Characteristics of the methods for estimating individual pharmacokinetic parameters are compared both theoretically and numerically. The methods examined represent the range of most of modern methods and include the ordinary least squares, iteratively reweighted least squares, extended least squares, generalized least squares, maximum quasi-likelihood and its extended scheme, and minimum relative entropy methods. When the function representing the mean itself is used as a variance function, which may be then related to a Poisson distribution, the iteratively reweighted least squares estimator and maximum quasi-likelihood estimator are both identical to that of the minimum relative entropy method. These methods work by minimizing a kind of relative entropy between observed data and corresponding theoretical values. Furthermore, these methods guarantee agreement between the sum of the observed values and the estimate of the sum. This relation does not hold in general for the other estimators. The sum can, in a sense, be viewed as an approximation of the area under the curve. In addition, it is shown by numerical study that these methods are robust against the misspecification of the variance model and work as effectively as such sophisticated methods as the extended least squares, generalized least squares, and maximum extended quasi-likelihood methods. These sophisticated methods require complicated numerical optimization techniques and should be used only in cases where the estimation of the variance function is demanded. In the other cases, the method of minimum relative entropy or its equivalent is sufficient or even preferable for estimating individual pharmacokinetic parameters.
机译：理论上和数值上都比较了估计各个药代动力学参数的方法的特征。所研究的方法代表了大多数现代方法的范围，包括普通最小二乘法，迭代加权最小二乘，扩展最小二乘，广义最小二乘，最大拟似然及其扩展方案以及最小相对熵方法。当代表平均值本身的函数用作方差函数（可能与泊松分布有关）时，迭代重新加权的最小二乘估计器和最大拟似然估计器均与最小相对熵方法相同。这些方法通过最小化观测数据与相应理论值之间的相对熵来工作。此外，这些方法保证了观测值的总和与总和的估计之间的一致性。对于其他估计量，此关系通常不成立。从某种意义上讲，该总和可以看作是曲线下面积的近似值。另外，通过数值研究表明，这些方法对于方差模型的错误指定具有鲁棒性，并且可以像扩展最小二乘法，广义最小二乘法和最大扩展拟似然法这样的复杂方法一样有效。这些复杂的方法需要复杂的数值优化技术，并且仅应在需要估计方差函数的情况下使用。在其他情况下，最小相对熵或其等效方法对于估计各个药代动力学参数是足够的甚至是优选的。

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