How to generate conditional probability from a algebric equation ?

Click For Summary

Discussion Overview

The discussion revolves around generating the conditional probability density function (pdf) of a dependent variable Y given a set of independent variables X. Participants explore the relationship between Y and X, particularly in the context of deterministic functions and the influence of random errors or noise represented by e. The conversation includes theoretical considerations and specific examples, with a focus on different scenarios regarding the nature of X and e.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant asks how to find the conditional pdf P(Y|X) when Y is a deterministic function of X plus an error term e.
  • Another participant provides a formulation for H(y) based on the distribution of e, suggesting that if e has a known distribution G, then H(y|X) can be expressed in terms of G.
  • A participant requests an example using a specific equation for Y, questioning how the pdf of Y|X would be derived if X has a probability distribution.
  • There is a clarification about whether the X variables are constants or random variables, indicating a potential misunderstanding in the assumptions made.
  • One participant emphasizes the need for specific information about the X variables, such as independence and distribution, to provide a concrete answer.
  • Another participant discusses the implications of X being ordinary variables versus random variables, and how this affects the calculation of P(Y|X).
  • A later reply interprets P(Y|X) as the density of Y given specific values of X, suggesting a formula for the density based on the relationship established in the equation for Y.
  • Concerns are raised about the applicability of certain density functions, particularly when they are defined only on specific subsets of the real numbers.

Areas of Agreement / Disagreement

Participants express differing views on the nature of the variables involved (constants vs. random variables) and the implications for calculating conditional probabilities. There is no consensus on a definitive approach or solution, as multiple competing views remain regarding the conditions under which the calculations are made.

Contextual Notes

Limitations include the need for clarity on the independence and distribution of the X variables and the error term e. The discussion also highlights the importance of specifying whether the X variables are treated as constants or random variables, which affects the resulting conditional probability calculations.

viperkill
Messages
4
Reaction score
0
How can I find the conditional probability density function of a dependent variable given the independent variable set. Say, Y is some deterministic function of a set of variables X , or Y=f(X)+e.

How can I fine the conditional pdf or P(Y|X) ?
 
Physics news on Phys.org
If [tex]\mathbf{X}[/tex] a set of constants? Then, assuming [tex]e[/tex] has distribution function [tex]G[/tex],

[tex] H(y) \equiv \Pr(Y \le y) = \Pr(e \le y - f(\mathbf{X})) = G(y-f(\mathbf{X})[/tex]

If [tex]G[/tex] has a density then

[tex] h(y) = g(y-f(\mathbf{X}))[/tex]

If [tex]\mathbf{X}[/tex] is random with joint distribution function [tex]W[/tex], as long as they are independent of [tex]e[/tex], you can argue this way. If the [tex]\mathbf{X}[/tex]
are given (fixed), then you are in the case discussed above, and

[tex] H(y \mid \mathbf{X}) = G(y - \mathbf{X}), \quad h(y-\mathbf{X}) = h(y- \mathbf{X})[/tex]
 
Thank you for your reply. Can you exemplify your explanation.

Suppose, y=0.25x1+5.32x2+0.356x3+e.
where e is normally distributed or poisson distributed.
What will be the pdf of Y|X ?

if X has some probability distribution, then what will be the solution?
 
viperkill said:
if X has some probability distribution, then what will be the solution?

Whoa! I thought you said the [tex]X_i[/tex] were constants. Are they now random variables?
 
if X were ordinary variables then what will be the solutions and what if X are random variable ?
 
If you want specific answers, you'll have to give specific information. For example, are the [tex]X_i[/tex] mutually independent? Are they identically distributed?

Are you familiar with convolutions of distributions?
 
If Xi are ordinary variables, like y=0.25x1+5.32x2+0.356x3+e. then what will be the solution ??

if Xi are mutually independent and identically distributed (iid) random variables. Then what will be the P(Y|X) for both cases ?
 
Let's say that e is independent of the [tex]X_i[/tex] and has density [tex]f(e)[/tex]. I'll interpret [tex]P(y|x)[/tex] to mean the density of [tex]y[/tex]. For given numerical values of the [tex]X_i[/tex], the density of [tex]y[/tex] is [tex]f( y - (0.25 x_1 + 5.32 x_2 + 0.356 x_3) )[/tex].

A density [tex]f(e)[/tex] is sometimes given by formula that only applies on some subset of the real numbers (e.g. the poission). It is understood that on numbers outside of this subset, the density is defined to be zero So if you are writing a computer program, you should test whether the value y - (0.25 x_1 + 5.32 x_2 + 0.356 x_3) is in the subset where the formula applies.
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
Replies
4
Views
3K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 12 ·
Replies
12
Views
5K
  • · Replies 1 ·
Replies
1
Views
3K