Extension of Two-Dimensional Discrete Random Variables Conditional Distribution

نویسنده

  • Feixue Huang
چکیده

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.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Promote the Use of Two-dimensional Continuous Random Variables Conditional Distribution

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 and examples in the case of continuous random variables. For the given definition of conditional distribution of three-...

متن کامل

Extension of Three-Variable Counterfactual Casual Graphic Model: from Two-Value to Three-Value Random Variable

The extension of counterfactual causal graphic model with three variables of vertex set in directed acyclic graph (DAG) is discussed in this paper by extending twovalue distribution to three-value distribution of the variables involved in DAG. Using the conditional independence as ancillary information, 6 kinds of extension counterfactual causal graphic models with some variables are extended f...

متن کامل

Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks

The curse of dimensionality is severe when modeling high-dimensional discrete data: the number of possible combinations of the variables explodes exponentially. In this paper we propose a new architecture for modeling high-dimensional data that requires resources (parameters and computations) that grow only at most as the square of the number of variables, using a multi-layer neural network to ...

متن کامل

Taking on the curse of dimensionality in joint distributions using neural networks

The curse of dimensionality is severe when modeling high-dimensional discrete data: the number of possible combinations of the variables explodes exponentially. In this paper, we propose a new architecture for modeling high-dimensional data that requires resources (parameters and computations) that grow at most as the square of the number of variables, using a multilayer neural network to repre...

متن کامل

The One - way Fubini Property and Conditional Independence : An Equivalence Result

A general parameter process defined by a continuum of random variables is not jointly measurable with respect to the usual product σ-algebra. For the case of independent random variables, a one-way Fubini extension of the product space was constructed in [11] to satisfy a limited form of joint measurability. For the general case we show that this extension exists if and only if there is a count...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010