betahat_GD_Cpp: betahat_GD_Cpp
In FrancescoBarile/FJLPackage: OurPackage

Estimation Linear Regression model via Gradient Descend method Output: [list] Beta paraameters estimated

`beta`	[numeric] vector containing an initial guess for the beta vector
`X`	[numeric] design matrix
`Y`	[numeric] response variable vector
`tolerance`	[numeric] tolerance level, stopping criteria of the algorithm (error<tolerance: stop)
`maxit`	[numeric] maximum number of iterations, used if the stopping criteria is never matched
`stepsize`	[numeric] learning parameter, to update the parameters at each iteration