fix docs move infos and warnings for GibbsPolarSlice to docstring

Author: Red-Portal

docs/src/gibbs_polar.md

@@ -40,20 +40,10 @@ The only tunable parameter of the algorithm is the size of the search interval (
 
 ## Interface
 
-!!! info
-    By the nature of polar coordinates, GPSS only works reliably for targets with dimension at least $$d \geq 2$$.
-
 ```@docs
 GibbsPolarSlice
 ```
 
-!!! warning
-    When initializing the chain (*e.g.* the `initial_params` keyword arguments in `AbstractMCMC.sample`), it is necessary to inialize from a point $$x_0$$ that has a sensible norm $$\lVert x_0 \rVert > 0$$, otherwise, the chain will start from a pathologic point in polar coordinates. This might even result in the sampler getting stuck in an infinite loop. (This can be prevented by setting `max_proposals`.) If $$\lVert x_0 \rVert \leq 10^{-5}$$, the current implementation will display a warning. 
-	
-!!! info
-	For Turing users: `Turing` might change `initial_params` to match the support of the posterior. This might lead to $$\lVert x_0 \rVert$$ being small, even though the vector you passed to`initial_params` has a sufficiently large norm. If this is suspected, simply try a different initialization value.
-
-
 ## Demonstration
 As illustrated in the original paper, GPSS shows good performance on heavy-tailed targets despite being a multivariate slice sampler.
 Consider a 10-dimensional Student-$$t$$ target with 1-degree of freedom (this corresponds to a multivariate Cauchy):

src/multivariate/gibbspolar.jl

@@ -10,6 +10,15 @@ Gibbsian polar slice sampling algorithm by P. Schär, M. Habeck, and D. Rudolf [
 # Keyword Arguments
 - `w::Real`: Initial window size for the radius shrinkage procedure
 - `max_proposals::Int`: Maximum number of proposals allowed until throwing an error (default: `10^6`).
+
+!!! info
+    By the nature of polar coordinates, GPSS only works reliably for targets with dimension at least \$\$d \\geq 2\$\$.
+
+!!! warning
+    When initializing the chain (*e.g.* the `initial_params` keyword arguments in `AbstractMCMC.sample`), it is necessary to inialize from a point \$\$x_0\$\$ that has a sensible norm \$\$\\lVert x_0 \\rVert > 0\$\$, otherwise, the chain will start from a pathologic point in polar coordinates. This might even result in the sampler getting stuck in an infinite loop. (This can be prevented by setting `max_proposals`.) If \$\$\\lVert x_0 \\rVert \\leq 10^{-5}\$\$, the current implementation will display a warning. 
+	
+!!! info
+    For Turing users: `Turing` might change `initial_params` to match the support of the posterior. This might lead to \$\$\\lVert x_0 \\rVert\$\$ being small, even though the vector you passed to`initial_params` has a sufficiently large norm. If this is suspected, simply try a different initialization value.
 """
 struct GibbsPolarSlice{W <: Real} <: AbstractMultivariateSliceSampling
     w::W