The SurvivalFunction function computes the survival function of the random variable X at the point t, which is defined as the probability that X takes a value greater than t. In other words, if $S\left(t\right)$ denotes the survival function of X and $F\left(t\right)$ denotes the cumulative distribution function of X, then $S\left(t\right)=1-F\left(t\right)$ for all real values of t.

The first parameter can be a distribution (see Statistics[Distribution]), a random variable, or an algebraic expression involving random variables (see Statistics[RandomVariable]).

By default, all computations involving random variables are performed symbolically (see option numeric below).

For more information about computation in the Statistics package, see the Statistics[Computation] help page.

The options argument can contain one or more of the options shown below. More information for some options is available in the Statistics[RandomVariables] help page.

numeric=truefalse -- By default, the survival function is computed using exact arithmetic. To compute the survival function numerically, specify the numeric or numeric = true option.

$\mathrm{with}\left(\mathrm{Statistics}\right)\:$

$\mathrm{SurvivalFunction}\left('\mathrm{{\rm B}}'\left(p\,q\right)\,t\right)$

$1-\left(\left\{\begin{array}{cc}0& t<0\\ \frac{t^p\mathrm{hypergeom}\left(\left[p\&comma;1-q\right]\&comma;\left[1+p\right]\&comma;t\right)}{\mathrm{{\rm B}}\left(p\&comma;q\right)p}& t<1\\ 1& \mathrm{otherwise}\end{array}\right.\right)$

$\mathrm{plot}\left(\mathrm{SurvivalFunction}\left('\mathrm{{\rm B}}'\left(3\&comma;5\right)\&comma;t\right)\&comma;t=0..1\right)$

$\mathrm{SurvivalFunction}\left('\mathrm{{\rm B}}'\left(3\&comma;5\right)\&comma;\frac{1}{2}\right)$

$1-\frac{35\mathrm{hypergeom}\left(\left[\mathrm{-4}\&comma;3\right]\&comma;\left[4\right]\&comma;\frac{1}{2}\right)}{8}$

$\mathrm{simplify}\left(\right)$

$\frac{29}{128}$

$\mathrm{SurvivalFunction}\left('\mathrm{{\rm B}}'\left(3\&comma;5\right)\&comma;\frac{1}{2}\&comma;\mathrm{numeric}\right)$

$0.226562500000000$

$T≔\mathrm{Distribution}\left(\mathrm{`=`}\left(\mathrm{PDF}\&comma;t\mapsto \frac{1}{\mathrm{\pi }\cdot \left(t^2+1\right)}\right)\right)\&colon;$

$X≔\mathrm{RandomVariable}\left(T\right)\&colon;$

$\mathrm{CDF}\left(X\&comma;t\right)$

$\frac{\mathrm{\pi }+2\arctan \left(t\right)}{2\mathrm{\pi }}$

$\mathrm{SurvivalFunction}\left(X\&comma;t\right)$

$1-\frac{\mathrm{\pi }+2\arctan \left(t\right)}{2\mathrm{\pi }}$

$\mathrm{plot}\left(\&comma;t=-10..10\right)$

$U≔\mathrm{Distribution}\left(\mathrm{`=`}\left(\mathrm{CDF}\&comma;t\mapsto F\left(t\right)\right)\&comma;\mathrm{`=`}\left(\mathrm{PDF}\&comma;t\mapsto f\left(t\right)\right)\right)\&colon;$

$Y≔\mathrm{RandomVariable}\left(U\right)\&colon;$

$\mathrm{CDF}\left(Y\&comma;t\right)$

$F\left(t\right)$

$\mathrm{SurvivalFunction}\left(Y\&comma;t\right)$

$1-F\left(t\right)$

Stuart, Alan, and Ord, Keith. Kendall's Advanced Theory of Statistics. 6th ed. London: Edward Arnold, 1998. Vol. 1: Distribution Theory.