 $\unicode[STIX]{x1D6FD}$-transformations
$\unicode[STIX]{x1D6FD}$-transformationsPublished online by Cambridge University Press: 07 September 2017
We consider the random  $\unicode[STIX]{x1D6FD}$-transformation
$\unicode[STIX]{x1D6FD}$-transformation  $K_{\unicode[STIX]{x1D6FD}}$ introduced by Dajani and Kraaikamp [Random
$K_{\unicode[STIX]{x1D6FD}}$ introduced by Dajani and Kraaikamp [Random  $\unicode[STIX]{x1D6FD}$-expansions. Ergod. Th. & Dynam. Sys.23 (2003), 461–479], which is defined on
$\unicode[STIX]{x1D6FD}$-expansions. Ergod. Th. & Dynam. Sys.23 (2003), 461–479], which is defined on  $\{0,1\}^{\mathbb{N}}\times [0,[\unicode[STIX]{x1D6FD}]/(\unicode[STIX]{x1D6FD}-1)]$. We give an explicit formula for the density function of a unique
$\{0,1\}^{\mathbb{N}}\times [0,[\unicode[STIX]{x1D6FD}]/(\unicode[STIX]{x1D6FD}-1)]$. We give an explicit formula for the density function of a unique  $K_{\unicode[STIX]{x1D6FD}}$-invariant probability measure absolutely continuous with respect to the product measure
$K_{\unicode[STIX]{x1D6FD}}$-invariant probability measure absolutely continuous with respect to the product measure  $m_{p}\otimes \unicode[STIX]{x1D706}_{\unicode[STIX]{x1D6FD}}$, where
$m_{p}\otimes \unicode[STIX]{x1D706}_{\unicode[STIX]{x1D6FD}}$, where  $m_{p}$ is the
$m_{p}$ is the  $(1-p,p)$-Bernoulli measure on
$(1-p,p)$-Bernoulli measure on  $\{0,1\}^{\mathbb{N}}$ and
$\{0,1\}^{\mathbb{N}}$ and  $\unicode[STIX]{x1D706}_{\unicode[STIX]{x1D6FD}}$ is the normalized Lebesgue measure on
$\unicode[STIX]{x1D706}_{\unicode[STIX]{x1D6FD}}$ is the normalized Lebesgue measure on  $[0,[\unicode[STIX]{x1D6FD}]/(\unicode[STIX]{x1D6FD}-1)]$. We apply the explicit formula for the density function to evaluate its upper and lower bounds and to investigate its continuity as a function of the two parameters
$[0,[\unicode[STIX]{x1D6FD}]/(\unicode[STIX]{x1D6FD}-1)]$. We apply the explicit formula for the density function to evaluate its upper and lower bounds and to investigate its continuity as a function of the two parameters  $p$ and
$p$ and  $\unicode[STIX]{x1D6FD}$.
$\unicode[STIX]{x1D6FD}$.