cvsequencial: Sequential method to k-fold crossing validation
In FrancescoBarile/FJLPackage: OurPackage

cvsequencial is used to parallelize the k-fold cross validation

1	cvsequencial(k, formula, df, tolerance, maxit, stepsize, verbose)

`k`	[numeric] number of fold to create
`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
`stepsize`	[numeric] learning parameter, to update the parameters at each iteration
`verbose`	[logical] indicating if the function write messages during the computation