Math 2.0

Statistics Definition

Survival function

Builds on Random variableCumulative distribution functionExponential distribution

Definition

Let TT be a random variable with values in [0,∞)[0, \infty), and let FF be its cumulative distribution function. The survival function of TT is the function S ⁣:[0,∞)→[0,1]S \colon [0, \infty) \to [0, 1] given by S(t)=P(T>t)=1−F(t).S(t) = P(T > t) = 1 - F(t).

Remarks

The function SS is nonincreasing and right-continuous, and S(t)→0S(t) \to 0 as t→∞t \to \infty. If TT has a density ff, then S(t)=∫t∞f(u) duS(t) = \int_t^\infty f(u) \, du and f=−S′f = -S' wherever ff is continuous. The mean of TT is E[T]=∫0∞S(t) dtE[T] = \int_0^\infty S(t) \, dt. Some authors use P(T≥t)P(T \ge t) instead; the two agree at every tt with P(T=t)=0P(T = t) = 0.

Example: if TT has the exponential distribution with rate λ>0\lambda > 0, then S(t)=e−λtS(t) = e^{-\lambda t}. Indeed P(T>t)=∫t∞λe−λu du=e−λtP(T > t) = \int_t^\infty \lambda e^{-\lambda u} \, du = e^{-\lambda t}, and ∫0∞e−λt dt=1/λ\int_0^\infty e^{-\lambda t} \, dt = 1/\lambda is the mean.

Non-example: the function G(t)=e−tcos⁡2tG(t) = e^{-t} \cos^2 t takes values in [0,1][0, 1], has G(0)=1G(0) = 1 and tends to 00, but it is not a survival function. It satisfies G(π/2)=0<e−π=G(π)G(\pi/2) = 0 < e^{-\pi} = G(\pi), so it is not nonincreasing, while P(T>t)P(T > t) can only decrease as tt grows.

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To understand this page from the ground up, read these 4 pages in order. The foundations come first.

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  1. Cumulative distribution function concept
  2. Exponential distribution concept
  3. Random variable concept
  4. Survival function definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Survival_function
About this page
TagNG2QE06MP1
URIm2://NG2QE06MP1
Kinddefinition
WritingW0 stub
MSC62N05, 62N01, 60E05
DefinesSurvival function
UsesRandom variable, Cumulative distribution function, Exponential distribution

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