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

Computing Values For The CDF in R

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• To compute CDF values for distributions in R remember 'p' for probability function

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

  • For $\;T \sim Exponential(\lambda)$
    $F(t)=$ pexp(q = quantile, rate = rate parameter)

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

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

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

Auburngrads/teachingApps documentation built on June 17, 2020, 4:57 a.m.