SmoothKernelDistribution (with no options and a single argument — a list of values) to get an approximate reconstruction of a continuous distribution based on a finite sample of values. It is known a priori that the actual distribution is unimodal and its PDF is exactly 0 for x ≤ 0.
Can I provide some options to
SmoothKernelDistribution so that it tries to find an approximate distribution within these constraints?
On the plot below horizontal positions of the vertical gray lines represent the sample values, the blue curve is an approximate distribution returned by
SmoothKernelDistribution, and the orange curve conveys a general idea how the actual distribution may look like; its exact shape, kurtosis, height and position of the peak may vary significantly, so I cannot just fit some known parameterized distribution to the sample using