Let $Z\sim SN(\lambda)$ where SN means skew-normal. Then a random variable $Z$ have density function given by $$\phi(z;\lambda)=2\phi(z)\Phi(\lambda z)\qquad -\infty<z<\infty$$
where $\phi$ and $\Phi$ are the standard normal density and function. One of the properties of this density is
Property: The density of $Z$ is strongly unimodal, i.e log $\phi(z;\lambda)$ is a concave function.
I want to make a proof of this property
Calling $f= \log \phi(z;\lambda)$ I want to show that for any $x$,$y$ and $a$,$b\in(0,1)$ with $a+b=1$ that $$f(ax+by)\leq a f(x)+b f(y)$$
I have that $$\Phi(z;\lambda)=\int_{-\infty}^z\int_{-\infty}^{\lambda t}\phi(t)\phi(u)du dt$$
and $$\phi(z;\lambda)=2\frac{1}{\sqrt{2\pi}} \exp \Big(-\frac{1}{2}z^2\Big)\int_{-\infty}^{\lambda z} \frac{1}{\sqrt{2\pi}} \exp\Big(-\frac{1}{2}u^2\Big)du$$
Making some research I found this remark
Remark: Log-concavity of a function $g$ on $(a,b)$ is equivalent to each of the following two conditions.
i) $\frac{g'(x)}{g(x)}$ is monotone decreasing on $(a,b)$.
ii) $ \log (g(x))''<0$
But I don't know how I can use it.