In probability theory and statistics, a collection of random variables is independent and identically distributed (i.i.d., iid, or IID) if each random variable has the same probability distribution as the others and all are mutually independent. [1]

Figure 1 illustrates the difference between iid and non-iid data in an example dataset. The concept of entropy, which is part of one of the ideas of information theory, will be used throughout...

Having independent and identically distributed (IID) data is a common assumption for statistical procedures and hypothesis tests. But what does that mouthful of words actually mean? That’s the topic of this post! And, I’ll provide helpful tips for determining whether your data are IID.

2018年10月7日 · 在机器学习中，独立和同分布 （iid） 的概念在数据分析、模型训练和评估的各个方面都起着至关重要的作用。iid 假设是确保许多机器学习算法和统计技术的可靠性和有效性的基础。本文探讨了 iid 在机器学习中的重要性、其假设及其对模型开发和性能的影响。

2024年10月22日 · In the field of Machine Learning and statistics, one of the most commonly used assumptions is that data follows an identically and independently distributed pattern, referred to as IID. This...

独立同分布（independent and identically distributed，i.i.d.）在概率统计理论中，指随机过程中，任何时刻的取值都为 随机变量，如果这些随机变量服从同一分布，并且互相独立，那么这些随机变量是独立同分布。 如果随机变量 X_1 和 X_2 独立，是指 X_1 的取值不影响 X_2 的取值， X_2 的取值也不影响 X_1 的取值且随机变量 X_1 和 X_2 服从同一分布，这意味着 X_1 和 X_2 具有相同的分布形状和相同的分布参数，对离随机变量具有相同的分布律，对连续随机变量具有相同 …

在概率论与统计学中，独立同分布（英語： Independent and identically distributed ，或稱獨立同分配，缩写为iid、 i.i.d.、IID）是指一组随机变量中每个变量的概率分布都相同，且这些随机变量互相独立。

2023年8月19日 · An IID random variable or sequence is an important component of a statistical or machine models, also playing a role in time series analysis. In this post, in an intuitive way, I explain the concept of IID in three different contexts: sampling, modelling, and predictability.

In ML and data analysis, having homogeneous data independent and identically distributed (iid) with the same probability distribution and independent of each other is one of the common...

All formal inference procedures in this course assume or require that the data are, in some manner, IID, where IID stands for Independent and Identically Distributed. Recall that any random sample - such as a simple random sample of size n - is a collection of random variables which we will denote by fX1; X2; : : : ; Xng.