Uncertainty estimation.
Uncertainty estimation.
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DOI：
10.1007/978-94-007-7606-7_5
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发表时间：
2014
影响因子：
--
通讯作者：
F. Noé;J. Chodera
中科院分区：
文献类型：
--
作者：
F. Noé;J. Chodera
马尔可夫模型为描述生物分子的长期统计进化提供了一种有用的简化表示，这种方式允许与实验直接比较，以及阐明固有随机过程的机制途径。与实验进行有意义的比较的一个重要部分是对预测的实验测量中的统计不确定性的表征，这种不确定性可以采取对某些光谱信号的平衡测量的形式，该信号在扰动后的时间演化，或对某些统计量的观察，如单个分子平衡动力学的相关函数。如果没有由近似误差和统计误差产生的有意义的误差条，就无法确定模型与实验之间的偏差是否具有统计意义。在本章中，我们描述了几种计算估计转移矩阵的统计不确定性的方法和由此计算的数量。转载经Prinz等人许可（分子动力学的马尔可夫模型：生成和验证）。j .化学。（物理学报，134:174,105,2011），no<s:1>（用马尔可夫模型计算分子可观测值的概率分布）。化学物理学报，128:244,103,2008)，Chodera和no<s:1>（用马尔可夫模型计算分子可观测值的概率分布）。ii：可观测物的不确定性及其时间演化。化学学报（自然科学版），2010)。美国物理学会版权所有。
Markov models provide a useful simplified representation for characterizing the long-time statistical evolution of biomolecules in a manner that allows direct comparison with experiments as well as the elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful comparison with experiment is the characterization of the statistical uncertainty in the predicted experimental measurement, which may take the form of an equilibrium measurement of some spectroscopic signal, the time-evolution of this signal following a perturbation, or the observation of some statistic such as the correlation function of the equilibrium dynamics of a single molecule. Without meaningful error bars which arise from both approximation and statistical error, there is no way to determine whether the deviations between model and experiment are statistically meaningful. In this chapter, we describe several approaches for computing statistical uncertainty of the estimated transition matrix and quantities calculated from it.Reprinted with permission from Prinz et al. (Markov models of molecular kinetics: Generation and validation. J. Chem. Phys. 134:174,105, 2011), Noé (Probability Distributions of Molecular Observables computed from Markov Models. J Chem Phys 128:244,103, 2008), Chodera and Noé (Probability distributions of molecular observables computed from Markov models. ii: Uncertainties in observables and their time-evolution. J Chem Phys 133:105,102, 2010). Copyright 2008, 2010, 2011, American Institute of Physics.