Difference between revisions of "Probability density function"

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Let $\mathbb{T}$ be a [[time scale]] with $0 \in \mathbb{T}$ and $\sup \mathbb{T} = \infty$. A function $f \colon \mathbb{T} \rightarrow \mathbb{R}$ is called a probability density function if $f(t) \geq 0$ for all $t \in \mathbb{T}$ and  
 
Let $\mathbb{T}$ be a [[time scale]] with $0 \in \mathbb{T}$ and $\sup \mathbb{T} = \infty$. A function $f \colon \mathbb{T} \rightarrow \mathbb{R}$ is called a probability density function if $f(t) \geq 0$ for all $t \in \mathbb{T}$ and  
 
$$\displaystyle\int_0^{\infty} f(t) \Delta t = 1.$$
 
$$\displaystyle\int_0^{\infty} f(t) \Delta t = 1.$$
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=References=
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[https://mospace.umsystem.edu/xmlui/bitstream/handle/10355/29595/Matthews_2011.pdf?sequence=1 Probability theory on time scales and applications to finance and inequalities by Thomas Matthews]

Revision as of 17:26, 23 November 2014

Let $\mathbb{T}$ be a time scale with $0 \in \mathbb{T}$ and $\sup \mathbb{T} = \infty$. A function $f \colon \mathbb{T} \rightarrow \mathbb{R}$ is called a probability density function if $f(t) \geq 0$ for all $t \in \mathbb{T}$ and $$\displaystyle\int_0^{\infty} f(t) \Delta t = 1.$$

References

Probability theory on time scales and applications to finance and inequalities by Thomas Matthews