lm_SD_optimizer: Estimating Linear Models via Steepest Descent Optimization...
In FrancescoBarile/FJLPackage: OurPackage

lm_SD_optimizer is used to estimates the parameters of a Linear Regression model via an unconstrained optimization method called Steepest Descent Method. It is in the general version: extract the variables of interest from the dataset and generates the initial values of the coefficients other than the betahat_SD_R functionalities

1	lm_SD_optimizer(formula, df, tolerance, maxit, verbose)

`formula`	[character] a symbolic description of the model to be fitted (as lm), with -1 if the intercept is not included
`df`	[numeric] dataset containing the variables of interest
`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
`verbose`	[logical] indicating if the function write messages during the computation