I want to find the moment generating function $M(t)$ for distribution
$$ f(x) =e^{-(ax)^{2}}*(1-e^{-(ax)^{2}})^{b-1}*[-log(1-e^{-(ax)^{2}})]^{r-1} $$
$$ M(t):=E(tX) = \int_0^\infty e^{tx}*f(x)dx \,. $$ But I have a problem.
I want to find the moment generating function $M(t)$ for distribution
$$ f(x) =e^{-(ax)^{2}}*(1-e^{-(ax)^{2}})^{b-1}*[-log(1-e^{-(ax)^{2}})]^{r-1} $$
$$ M(t):=E(tX) = \int_0^\infty e^{tx}*f(x)dx \,. $$ But I have a problem.
The moment generating function is simply the Laplace transform. Since the Laplace transform of a convolution is the product of Laplace transform you simply have to compute the Laplace transform of each term and then multiply them.