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相关概念视频

Sampling Plans01:23

Sampling Plans

866
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
866
Cluster Sampling Method01:20

Cluster Sampling Method

13.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.9K
Sampling Methods: Overview01:06

Sampling Methods: Overview

2.1K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
2.1K
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

1.1K
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...
1.1K
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

657
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
657
Stratified Sampling Method01:16

Stratified Sampling Method

14.4K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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相关实验视频

Updated: Jan 9, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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在R中进行自适应多波采样的最佳分配:R包是最优的.

Jasper B Yang1, Bryan E Shepherd2, Thomas Lumley3

  • 1University of Washington.

Journal of statistical software
|December 5, 2025
PubMed
概括
此摘要是机器生成的。

最佳R包简化了调查采样设计. 它有助于定义层,使用尼曼或赖特方法分配样本,并为高效的调查实施选择单位.

关键词:
尼曼的分配额度.在这个过程中,R是R.多波采样采样多波采样采样最优的设计最优的设计

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科学领域:

  • 统计 统计 统计 统计
  • 调查方法 调查方法
  • 计算统计学 计算统计学

背景情况:

  • 设计复杂的调查需要高效和适应性的工具.
  • 传统的调查设计方法可能耗时且缺乏灵活性.
  • 实施分层采样设计带来了独特的挑战.

研究的目的:

  • 引入最佳的R包,以简化调查采样设计.
  • 为交互式层定义和样本分配提供功能.
  • 在现实世界流行病学调查中展示最佳的实用性.

主要方法:

  • 使用R编程进行统计分析和调查设计.
  • 实现用于交互层间切割点调整的功能.
  • 应用尼曼和赖特的分配方法来确定最佳的样本大小.
  • 在R环境中展示分层抽样单元的选择.

主要成果:

  • 最优的包为调查设计提供了高效的功能.
  • 基于辅助共变量的层切割点的交互调整得到支持.
  • 已启用适应计算每个层的最佳样本分配.
  • 该套件有助于设计和实施复杂的调查采样.

结论:

  • 最佳R包为调查采样设计提供了一个全面的解决方案.
  • 它提高了定义层和分配样本的效率和灵活性.
  • Optimall对于各种调查类型非常有价值,包括多波和多相设计.