We recommend reading this documentation on pkgdown which renders math nicely.
https://pkg.mitchelloharawild.com/distributional/reference/dist_percentile.html
In the following, let \(X\) be a Percentile random variable defined by
values \(x_1, x_2, \ldots, x_n\) at percentiles
\(p_1, p_2, \ldots, p_n\) where \(0 \le p_i \le 100\).
Support: \([\min(x_i), \max(x_i)]\) if \(\min(p_i) > 0\) or
\(\max(p_i) < 100\), otherwise support is approximated from the
specified percentiles.
Mean: Approximated numerically using spline interpolation and
numerical integration:
$$
E(X) \approx \int_0^1 Q(u) du
$$
where \(Q(u)\) is a spline function interpolating the percentile values.
Variance: Approximated numerically.
Probability density function (p.d.f): Approximated numerically using
kernel density estimation from generated samples.
Cumulative distribution function (c.d.f): Defined by linear
interpolation:
$$
F(t) = \begin{cases}
p_1/100 & \text{if } t < x_1 \\
p_i/100 + \frac{(t - x_i)(p_{i+1} - p_i)}{100(x_{i+1} - x_i)} & \text{if } x_i \le t < x_{i+1} \\
p_n/100 & \text{if } t \ge x_n
\end{cases}
$$
Quantile function: Defined by linear interpolation:
$$
Q(u) = x_i + \frac{(100u - p_i)(x_{i+1} - x_i)}{p_{i+1} - p_i}
$$
for \(p_i/100 \le u \le p_{i+1}/100\).