Update README.md

Author: linogaliana

README.md

@@ -1,4 +1,4 @@
-## `btbpy`: Kernel Density Estimation for Urban Geography
+# `btbpy`: Kernel Density Estimation for Urban Geography
 
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 [![Documentation Status](https://readthedocs.org/projects/pybtb/badge/?version=latest)](https://pybtb.readthedocs.io/en/latest/?badge=latest)
@@ -9,7 +9,7 @@
 Documentation website: https://pybtb.readthedocs.io/en/latest/
 
 
-### Contributions
+## Contributions
 
 Developer and maintainer of `btbpy` package :
 
@@ -24,11 +24,13 @@ Auriane Renaud [ctb],
 Farida Marouchi [ctb]
 Joachim Timoteo [ctb]
 
-#### What do `btbpy` and `btb` do ?
+## What do `btbpy` and `btb` do ?
 
 The `kernelSmoothing()` function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are only two major call modes of the function. The smoothing with quantiles method is not available on the `btbpy` package.
 The first call mode is `kernelSmoothing(obs, epsg, cellsize, bandwith)` for a classical kernel smoothing and automatic grid.
 The second call mode is `kernelSmoothing(obs, epsg, cellsize, bandwith, centroids)` for a classical kernel smoothing and user grid.
+
+## References
         
 Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) <doi:10.1016/S0198-9715(01)00009-6>, 
 Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) <doi:10.1080/13658816.2014.937718>.