From 55ecf3477bcdc126cb39d210e4c2f96a1715bc58 Mon Sep 17 00:00:00 2001
From: ShouvikGhosh2048 <shouvikg.cal@gmail.com>
Date: Mon, 9 Dec 2024 14:08:30 +0000
Subject: [PATCH] Update docs

---
 docs/src/api/bayesian_regression.md | 22 +++++++++++++++-------
 1 file changed, 15 insertions(+), 7 deletions(-)

diff --git a/docs/src/api/bayesian_regression.md b/docs/src/api/bayesian_regression.md
index 018096c..c9e9ad2 100644
--- a/docs/src/api/bayesian_regression.md
+++ b/docs/src/api/bayesian_regression.md
@@ -4,34 +4,42 @@
 BayesianRegression
 ```
 
+## Bayesian Algorithms
+
+```@docs
+BayesianAlgorithm
+MCMC
+VI
+```
+
 ## Linear Regression
 
 ### Linear Regression with User Specific Gaussian Prior
 ```@docs
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Gauss, alpha_prior_mean::Float64, beta_prior_mean::Vector{Float64}, sim_size::Int64 = 1000)
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Gauss, alpha_prior_mean::Float64, alpha_prior_sd::Float64, beta_prior_mean::Vector{Float64}, beta_prior_sd::Vector{Float64}, sim_size::Int64 = 1000)
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Gauss, alpha_prior_mean::Float64, beta_prior_mean::Vector{Float64}, algorithm::BayesianAlgorithm = MCMC())
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Gauss, alpha_prior_mean::Float64, alpha_prior_sd::Float64, beta_prior_mean::Vector{Float64}, beta_prior_sd::Vector{Float64}, algorithm::BayesianAlgorithm = MCMC())
 ```
 
 ### Linear Regression with Ridge Prior
 ```@docs
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Ridge, h::Float64 = 0.01, sim_size::Int64 = 1000)
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Ridge, algorithm::BayesianAlgorithm = MCMC(), h::Float64 = 0.01)
 ```
 
 ### Linear Regression with Laplace Prior
 ```@docs
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Laplace, h::Float64 = 0.01, sim_size::Int64 = 1000)
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Laplace, algorithm::BayesianAlgorithm = MCMC(), h::Float64 = 0.01)
 ```
 ### Linear Regression with Cauchy Prior
 ```@docs
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Cauchy, sim_size::Int64 = 1000)
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_Cauchy, algorithm::BayesianAlgorithm = MCMC())
 ```
 ### Linear Regression with T-distributed Prior
 ```@docs
-fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_TDist, h::Float64 = 2.0, sim_size::Int64 = 1000)
+fit(formula::FormulaTerm, data::DataFrame, modelClass::LinearRegression, prior::Prior_TDist, algorithm::BayesianAlgorithm = MCMC(), h::Float64 = 2.0)
 ```
 ### Linear Regression with Horse Shoe Prior
 ```@docs
-fit(formula::FormulaTerm,data::DataFrame,modelClass::LinearRegression,prior::Prior_HorseShoe,sim_size::Int64 = 1000)
+fit(formula::FormulaTerm,data::DataFrame,modelClass::LinearRegression,prior::Prior_HorseShoe,algorithm::BayesianAlgorithm = MCMC())
 ```
 
 ## Logistic Regression