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相关概念视频

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
86
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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相关实验视频

Updated: Sep 11, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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估计结构模型的准最大概率.

Malek Ben-Abdellatif1, Hatem Ben-Ameur2, Rim Chérif3

  • 1Department of Finance, School of Business, ESLSCA University, Giza 12511, Egypt.

Studies in nonlinear dynamics and econometrics
|August 18, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种扩展的结构模型,用于估计不可观察的公司资产价值. 这种新的方法使用动态编程和准最大概率估计来准确估计参数和提取资产价值.

关键词:
信用差的拼图 - 信用差的拼图估计估计估计的估计.跳转扩散过程中的过程.几乎最大的可能性.结构模型是一个结构模型.

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相关实验视频

Last Updated: Sep 11, 2025

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科学领域:

  • 量化金融 量化金融
  • 金融计量经济学 金融计量经济学
  • 企业金融公司财务

背景情况:

  • 由于无法观察到的公司资产价值,估计结构模型具有挑战性.
  • 现有的模式往往缺乏灵活性来整合复杂的金融结构.

研究的目的:

  • 开发一个扩展的结构模型来估计公司资产价值.
  • 为了适应多种金融特征,如多种资产类别和债务结构.
  • 提供灵活有效的估计方法.

主要方法:

  • 使用观察到的公司股权价值来推导概率函数.
  • 动态编程用于模型解决方案和资产价值提取的应用.
  • 概率函数的近似和优化用于准最大概率 (QML) 估计.

主要成果:

  • 成功提取了公司资产价值的时间序列 (伪观察).
  • 对未知的模型参数实现了准最大概率 (QML) 估计.
  • 证明了QML方法的灵活性和有效性.

结论:

  • 拟议的扩展结构模型和QML估计提供了一个强大的框架.
  • 该模型提供了对信用差距难题的洞察,并通过跳跃和破产成本提出了补救措施.