Derivation of Vasicek Entropy Estimator

In summary, the conversation is about trying to understand the Vasicek entropy estimator and how it relates to the differential entropy of a system. The speaker is struggling with finding the derivative of an inverse function and feeling frustrated with not being able to solve the problem.
  • #1
thrillhouse86
80
0
Hey All - I am trying to solve a problem that should be really easy (at least every paper I read says the step is!)

I'm trying to understand where the Vasicek entropy estimator comes from:

I can write the differential entropy of a system as:
[tex]
H(f) = -\int^{\infty}_{-\infty} f(x)log(f(x))dx
[/tex]

where f(x) is your probability distribution function

Apparently it is an easy step that you can re-write this in the form:
[tex]
H(f) = \int^{1}_{0} log(\frac{d}{dp}F^{-1}(p)) dp
[/tex]

Where [tex] F^{1} [/tex] is the inverse of the culmative distribution function.

I've tried using the derivative of an inverse function that I learned when trying to find the derivative of inverse trig functions but all I got was:

[tex]
\frac{d F^{-1}(p)}{dp} = \frac{1}{f(F^{-1}(p))}
[/tex]

By the way just in case I need to point it out - this isn't homework - its a stupid problem which is making me feel incredibly stupid not being able to solve

Thanks,
Thrillhouse
 
Last edited:
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  • #2
Maybe it's "integration by sustitution" with [itex] x = F^{-1}(p) [/itex]
 

Related to Derivation of Vasicek Entropy Estimator

1. What is the Vasicek Entropy Estimator?

The Vasicek Entropy Estimator is a statistical method used to estimate the entropy of a distribution. It was developed by Oldrich Vasicek in 1976 and is commonly used in finance and risk management.

2. How is the Vasicek Entropy Estimator calculated?

The Vasicek Entropy Estimator is calculated by first estimating the probability density function (PDF) of the data using a nonparametric method such as kernel density estimation. Then, the entropy is calculated using the estimated PDF and a formula derived by Vasicek.

3. What are the assumptions made when using the Vasicek Entropy Estimator?

The Vasicek Entropy Estimator assumes that the data follows a continuous probability distribution and that the data is independent and identically distributed (iid). It also assumes that the data is stationary and ergodic, meaning that the statistical properties of the data do not change over time.

4. What are the applications of the Vasicek Entropy Estimator?

The Vasicek Entropy Estimator has various applications in finance, risk management, and machine learning. It can be used to measure the uncertainty or risk in financial markets, evaluate the performance of investment portfolios, and identify patterns in data for predictive modeling.

5. Are there any limitations of the Vasicek Entropy Estimator?

Like any statistical method, the Vasicek Entropy Estimator has its limitations. It may not perform well with small sample sizes or when the underlying distribution is not well-behaved. It also assumes that the data is independent and identically distributed, which may not always be the case in real-world scenarios.

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