New packages

Closes #7, #8, #9 by describing and classifying `NetworkDistance`, `graphon` and `VBLPCM`.

Author: FATelarico

NetworkAnalysis.md

@@ -236,17 +236,16 @@ subgraph of a network called a *backbone*.
 
 ## Exploratory Data Analysis
 
-`r pkg ("igraph")`, `r pkg ("sna")`, and `r pkg("manynet")` offer functions for
-a similar set of network-analytic and visualization operations, whereas `r pkg ("tidygraph")` is
-more limited. However, some algorithms differ from each other and from those
-are some specialized packages for their implementation, speed, or defaults.
+Moving to Exploratory Data Analysis (EDA), `r pkg ("igraph")`, `r pkg ("sna")`, and `r pkg("manynet")` offer functions for a similar set of network-analytic and visualization operations, whereas `r pkg ("tidygraph")` is more limited. However, some algorithms differ from each other and from those are some specialized packages for their implementation, speed, or defaults.
 
 ### General
 
 - `r pkg("tsna")` implements a number of methods for exploratory
   analysis and summaries of temporal networks in the `r pkg("networkDynamic")`
   representation.
 
+- Reletadly to EDA, `r pkg("NetworkDistance")` offers many measures to compute the distance between two networks based on centrality, continuous spectral densities, the Euclidean distance between the adjacency matrices' spectra, the Frobenius norm of edge-to-edge difference, exponential kernel matrices, graphons, the discrepancy between two binary networks for each edge (Hamming), a combines the local Hamming distance and the global Ipsen-Mikhailov distance, and the log of graph moments.
+
 ### Visualization
 
 #### Interactive visualization
@@ -487,6 +486,8 @@ models based on `r pkg("igraph")` objects.
 and cluster model using `r pkg("network")` objects and compatibly with
 `r pkg("ergm")` approaches.
 
+- relatedly, `r pkg("VBLPCM")` offers an alternative to `r pkg("latentnet")` for larger networks (on which the latter's package algorithm may be computationally prohibitive). It computes the approximation of the posterior of the `latentnet::ergmm()` function using a Variational Bayesian Expectation Maximisation algorithm. Thus, it is faster than the full-fledged MCMC sampler more accurate than `r pkg("latentnet")`'s two-stage maximum likelihood estimation (MLE). Indeed, Variational Bayes tends to converge quicker than the two-stage MLE, too.
+
 - `r pkg("latenetwork")` implements a method for causal inference with noncompliance
 and network interference of unknown form on average causal using instrumental variables.
 
@@ -636,6 +637,10 @@ contagion processes. It implements algorithms for calculating network diffusion
 statistics such as transmission rate, hazard rates, exposure models, network
 threshold levels, infectiousness (contagion), and susceptibility.
 
+### Others
+
+- `r pkg("graphon") provides methods for estimating the *graphon* of a network based on tis adjacency matrix using empirical degree-sorting for stochastic blockmodel (SBM), SBM approximation, universal singular value thresholding, or neighborhood smoothing. Also, on the basis of the estiamted model, it can complete a matrix from a partially observed data. Additionally, it includes function to generate binary graph given an arbitrary graphon, Erdos-Renyi random graphs, and SBMs. Besides including 10 graphon models for simulation.
+
 ## Field packages
 
 As an interdisciplinary approach, network analysis is used in a number of