Abstract
Conditional distribution reflects the dependency link among random variables, but two-dimensional random variables Conditional Distribution has some limitations. In order to rich the content of conditional distribution this paper gives the extension of conditional distribution under discrete random variables and some examples. This article obtains the extension strictly in accordance with the definition of two-dimensional random variables. So it can get conditional distributions after changing the condition and get conditional distributions that are extended into n-dimensional random variables, thereby enriching the contents of the conditional distribution.
Highlights
Two-dimensional random variables conditional distribution is the distribution of one variable when another variable is a fixed value
Conditional eigenvalues are mainly pointed to conditional expectation, which is expectation under conditional distribution
In this area the main contributions are Wang Cheng, Zou Hailei gave the definition and researched the characteristics of random variables conditional particular function based on measurement and integral theory; Zhang Mei used minimum mean-squared error to solve one kind problems of best prediction and took examples to analyze the application of conditional expectation in practical prediction problems; Xu hui and Wu Guogeng educed total probability formula of discrete and continuous random variables based on conditional expectation and indicative function IA of random events A
Summary
Two-dimensional random variables conditional distribution is the distribution of one variable when another variable is a fixed value. Conditional eigenvalues are mainly pointed to conditional expectation, which is expectation under conditional distribution In this area the main contributions are Wang Cheng, Zou Hailei gave the definition and researched the characteristics of random variables conditional particular function based on measurement and integral theory; Zhang Mei used minimum mean-squared error to solve one kind problems of best prediction and took examples to analyze the application of conditional expectation in practical prediction problems; Xu hui and Wu Guogeng educed total probability formula of discrete and continuous random variables based on conditional expectation and indicative function IA of random events A. Hansen studied nonparametric estimation of smooth conditional distributions[12]; Persi Diaconis and Bernd Sturmfels analyzed conditional distributions using algebraic algorithms for sampling They have shown that the researches of conditional distribution are multi-faceted and more complex while make against undergraduate teaching. This paper is to solve the conditional distribution of multidimensional random variables under the given conditions and its results can be used for teaching, expending the knowledge of the conditional distribution and facilitating people’s calculations
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