> Thus, the real information is still strongly dominated by beliefs about the width and centering of the distributions, which we still don't know, and as long a

> Thus, the real information is still strongly dominated by beliefs about the width and centering of the distributions, which we still don't know, and as long as enough of the parameters have high uncertainty with some potentially having near-zero values, the result will always tend towards zero. You state this like it is a problem. I think it's more like a feature? My take on the main point of the paper: it is commonplace to derive probabilities for being alone in the universe by plugging in point estimates into Drake Equation, but one should take into account that, in fact, we have lots uncertainty in our estimates for the parameters, and without quantifying that uncertainty, the Drake's Equation indeed will produce biased estimates. And if we quantify the uncertainty, we end up with wide distributions (that have some of their mass near zero). edit. Your point about N = 1 is interesting, though. edit2. Concerning N = 1: They don't elaborate on it in writing, but if I'm reading the sec 4.0.2 correctly, they do account for our existence in their spatial Poisson update: P(no detection | N, d) = 1 - exp(-(4/3) pi d^3 lambda) = 1 - P("number of civilizations in sphere of radius d when rate is lambda" = 0) = P("number of civilizations in sphere ..." > 0). edit3. wait, that does not make sense, does it. shouldn't P( no detection | N, d) be P("number of civilizations in sphere when rate is lambda" = 1) = (4/3) pi d^3 lambda exp(-(4/3) pi d^3 lambda), as per spatial Poisson process P(K = 1). now I'm just confused.