In teachingApps: Apps for Teaching Statistics, R Programming, and Shiny App Development

Computing Values For the Cumulative Hazard Function in R

• No predefined R function exists for $H(t)$, but we can take advantage of the fact that $$H(t)=-\ln[1-F(t)]$$

  • For $\;T \sim Weibull(\beta,\theta)$
    $H(t)=$ -log(1 - pweibull(q = quantile, shape = shape param, scale = scale param))

  • For $\;T \sim Exponential(\lambda)$
    $H(t)=$ -log(1 - pexp(q = quantile, rate = rate parameter))

  • For $\;T \sim Normal(\mu,\sigma)$
    $H(t)=$ -log(1 - pnorm(q = quantile, mean = mean, sd = standard deviation))

  • For $\;T \sim Lognormal(\mu,\sigma)$
    $H(t)=$ -log(1 - plnorm(q = quantile, meanlog = log(mean), sdlog = log(stdev)))

  • For $T \sim Gamma(\kappa,\beta)$
    $H(t)=$ -log(1-pgamma(q = quantile, shape = shape param, scale = scale param))

teachingApps documentation built on July 1, 2020, 5:58 p.m.