This article$^1$ on p.16 specifies Haldane's prior as:

$$p(theta) = frac{1}{θ(1−θ)}$$.

However, other$^2$ source on p.6 specifies Haldane's prior as proportional to $frac{1}{θ(1−θ)}$, i.e.

$$p(theta) propto frac{1}{θ(1−θ)}$$.

Could anyone clarify which expression is the accurate one.

1. Approximation of improper priors

2. Bayesian Analysis of Some Common Distributions

**Contents**hide

#### Best Answer

Haldane prior is beta distribution with parameters $alpha = beta = 0$. So it is

$$ f(p) = frac{p^{alpha-1} (1-p)^{beta-1}}{B(alpha, beta)} = frac{p^{-1}(1-p)^{-1}}{B(0, 0)} $$

where $B(0, 0)$ is the normalizing constant that *is infinite* as described in Wikipedia:

The function $p^{-1}(1-p)^{-1}$ can be viewed as the limit of the numerator of the beta distribution as both shape parameters approach zero: $alpha, beta to 0$. The Beta function (in the denominator of the beta distribution) approaches infinity, for both parameters approaching zero, $alpha, beta to 0$. Therefore, $p^{-1}(1-p)^{-1}$ divided by the Beta function approaches a 2-point Bernoulli distribution with equal probability $1/2$ at each Dirac delta function end, at $0$ and $1$, and nothing in between, as $alpha, beta to 0$.

So Haldane prior is not a proper distribution. It is an abstract idea of what would be the beta distribution be if it had $alpha = beta = 0$ parameters. As a distribution, it is rather not usable, yet it can be used as an "uninformative" prior for binomial distribution. It is often described in it's approximate form $f(p) propto p^{-1}(1-p)^{-1}$, since the normalizing constant is meaningless.