Landing page and tiny updates elsewhere

Author: nossleinad

docs/src/index.md

@@ -21,20 +21,16 @@ hero:
       link: https://github.com/MurrellGroup/MolecularEvolution.jl
 features:
   - title: Flexible Model Development
-    details: Create custom evolutionary models with your own data types and probability distributions while leveraging the existing infrastructure for tree operations and likelihood calculations.
+    details: Create custom evolutionary models by defining how your new (or already existing) probability distributions evolve along a branch, and get likelihood calculations (and much more) for free! • Mix and match different models on the same phylogeny.
     link: /framework
   - title: Rich Model Library
-    details: Includes standard models like JC69, K80, GTR for nucleotides, JTT and WAG for amino acids, MG94 and GY94 for codons, plus Brownian motion for continuous traits.
+    details: Codon, AA, nucleotide and generic discrete character models as well as continuous Brownian motion in 1D. Site- and branch-wise mixture models and more.
     link: /models
   - title: Powerful Tree Operations
-    details: Optimize branch lengths, infer ancestral states, perform tree rearrangements (NNI), and sample topologies with MCMC.
+    details: Optimize model parameters, branch lengths and root state/location. Perform tree rearrangements (NNI). The above can also be made in the Bayesian framework by sampling over posterior tree and parameter spaces with MCMC. • Infer ancestral states.
     link: /optimization
   - title: Simulation Tools
-    details: Generate phylogenies using both coalescent and birth-death processes, and simulate sequence evolution on those trees.
+    details: Generate phylogenies using e.g. coalescent and logistic growth processes, and simulate both sequence evolution and continuous trait evolution on those trees.
     link: /simulation
 ---
-```
-
-```@meta
-CurrentModule = MolecularEvolution
-```
+```

docs/src/models.md

@@ -1,6 +1,6 @@
 # Models
 
-We offer a catalogue of frequent models that are already integrated with the framework and ready to be used.
+We offer a catalogue of frequently used models that are already integrated with the framework and ready to be used.
 We maintain that if a model you'd like to use is not included in the list, you can swiftly define one yourself and
 leverage our framework nonetheless.
 
@@ -25,7 +25,7 @@ And then there are two typical `BranchModel`s that will cooperate with this `Par
 !!! note
     The two above can be regarded as special cases of the more general [`PModel`](@ref), which just represents a P matrix.
 
-A typical way of constructing your Q matrix in our ecosystem is by
+A typical way of constructing your Q matrix in our ecosystem is by:
 ```@docs; canonical=false
 reversibleQ
 nonreversibleQ

docs/src/optimization.md

@@ -4,6 +4,9 @@ There are two distinct kinds of optimization: "global" model parameters, and the
 
 The example below will set up and optimize a ["Generalized Time Reversible" nucleotide substitution model](https://en.wikipedia.org/wiki/Substitution_model), where there are 6 rate parameters that govern the symmetric part of a rate matrix, and 4 nucleotide frequencies (that sum to 1, so only 3 underlying parameters).
 
+!!! note
+    For the Bayesian counterpart of this page, we refer you to [Set up a Bayesian model sampler](@ref) and  [Multiple trees](@ref).
+
 ## Optimizing model parameters
 
 We first need to construct an objective function. A very common use case involves parameterizing a rate matrix (along with all the constraints this entails) from a flat parameter vector. `reversibleQ` can be convenient here, which takes a vector of parameters and equilibrium frequencies and returns a reversible rate matrix.
@@ -158,5 +161,6 @@ reversibleQ
 unc2probvec
 branchlength_optim!
 nni_optim!
+root_optim!
 tree_polish!
 ```