Deriving the Hazard Rate Formula for F(t) = 1-Exp -((t-γ)/n))^β

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SUMMARY

The discussion focuses on deriving the hazard rate formula from the cumulative distribution function F(t) = 1 - Exp(-((t-γ)/n)^β). The correct hazard rate is established as h(t) = β(t-y)^(β-1)/n^β. Participants analyze the derivative f(t) = dF(t)/dt and apply the chain rule to clarify the derivation process. The final formula is confirmed as accurate, addressing concerns about the initial derivation steps.

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  • Familiarity with the chain rule in calculus
  • Knowledge of exponential functions and their derivatives
  • Basic concepts of hazard rates in survival analysis
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Buchanskii
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F(t) = 1-Exp -((t-γ)/n))^β

f(t) = dF(t)/dt = Exp/n[(t-x)/n]^β-1

h(t) = f(t)/1-F(t)

h(t)= β(t-y)^β-1/n^β



The final answer: h(t)= β(t-y)β-1/n^β, Is the correct answer.

But, I can't for the life of me work out why. Have I made a mistake in the f(t) derivation.

Can anyone help?
 
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its a bit hard to read, but you derivative doesn't look right

so let's start with the chain rule
[tex] \frac{d}{dt} g(h(t))= g'(h(t))h'(t)[/tex]

applying to our case
[tex] F(t) = 1-e^{-(\frac{t-γ}{n})^\beta}[/tex]

so let
[tex] g(x) = 1-e^{x}[/tex]
[tex] g'(x) = e^{x}[/tex]
[tex] h(t) = -(\frac{t-γ}{n})^\beta[/tex]
[tex] h'(t) = -\frac{d}{dt}(\frac{t-γ}{n})^\beta[/tex]


which gives
[tex] f(t) = \frac{F(t)}{dt} = e^{-(\frac{t-γ}{n})^\beta}(-\frac{d}{dt}(\frac{t-γ}{n})^\beta)[/tex]
 

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