  The projection of sample measurements onto a reconstruction space represented
by a basis on a regular grid is a powerful and simple approach to estimate a
probability density function. In this paper, we focus on Riesz bases and
propose a projection operator that, in contrast to previous works, guarantees
the bona fide properties for the estimate, namely, non-negativity and total
probability mass $1$. Our bona fide projection is defined as a convex problem.
We propose solution techniques and evaluate them. Results suggest an improved
performance, specifically in circumstances prone to rippling effects.
