Derivation of the exponential distribution - that infinitesimal

In summary, the conversation discusses the derivation of the exponential function and its use of little-o notation to represent small terms that are not relevant to the derivation. The use of Taylor expansion is also mentioned as a way to approximate the function to higher orders.
  • #1
thomas49th
655
0
Hello,

I've been looking at the derivation of the exponential function, here
http://www.statlect.com/ucdexp1.htm
amongst other places, but I don't get how, why or what the o(delta t) really does. How does it help?

It's really confusing me, and all the literature I've looked at just seems to quickly dance over it

Thanks
 
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  • #2
##o(\Delta t)## contains all small terms the derivation does not want to (and does not have to) care about. Something like ##(\Delta t)^2##, ##(\Delta t)^3## and so on.

Little-o notation
 
  • #3
why do those terms exist? was there some kind of taylor expansion?
 
  • #4
Exactly. It is a taylor approximation to first order (linear in Δt) and higher orders are neglected.
 
  • #5
what the taylor expansion of? e^x ?
 
  • #6
Should be ##e^x - e^{x+Δt}## with some prefactors I did not check.
 

What is the exponential distribution?

The exponential distribution is a probability distribution that describes the time between events in a Poisson process, where events occur continuously and independently at a constant average rate.

What is the formula for the exponential distribution?

The formula for the exponential distribution is f(x) = λe^(-λx), where λ is the rate parameter and e is the base of the natural logarithm.

How is the exponential distribution derived?

The exponential distribution is derived by considering the time between events in a Poisson process as a continuous random variable and using the properties of the Poisson distribution to calculate its probability density function.

What is the role of infinitesimals in the derivation of the exponential distribution?

The concept of infinitesimals, or infinitely small quantities, is used in the derivation of the exponential distribution to represent the probability of an event occurring at a specific point in time. This allows for the continuous nature of the distribution.

What are some real-world applications of the exponential distribution?

The exponential distribution is commonly used in fields such as finance, engineering, and biology to model events that occur continuously and independently, such as the time between arrivals at a bank, the lifespan of a machine, or the decay of radioactive materials.

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