iOLS_path {IOLS}

iOLS_path

Description

iOLS regression repeated for several values of the hyper-parameter delta.

Usage

iOLS_path(
  y,
  X,
  deltainf = 10^-5,
  deltasup = 10^4,
  nbre_delta = 20,
  epsi = 10^-3,
  b_init,
  error_type = "HC0"
)

Arguments

y

the dependent variable, a vector.

X

the regressors matrix x with a column of ones added.

deltainf

numeric, the lowest hyper-parameter delta we want to apply iOLS with. The default value is 10^-5.

deltasup

numeric, the highest hyper-parameter delta we want to apply iOLS with. The default value is 10000.

nbre_delta

integer, the number of hyper-parameters delta we want between deltainf and deltasup.

epsi

since the estimated parameters are obtained by converging, we need a convergence criterion epsi (supposed to be small, usually around 10^-5), to make the program stop once the estimations are near their limits. A numeric.

b_init

the point from which the solution starts its converging trajectory. A vector that has the same number of elements as there are parameters estimated in the model.

error_type

a character string specifying the estimation type of the covariance matrix. Argument of the vcovHC function, then click this link for details. "HC0" is the default value, this the White's estimator.

Value

an iOLS_path fitted model object.

Examples

data(DATASET)
y = DATASET$y
x = as.matrix(DATASET[,c("X1","X2")])
lm = lm(log(y+1) ~ x)
lm_coef = c(coef(lm))
X = cbind(rep(1, nrow(x)), x)
k = iOLS_path(y, X, b_init = lm_coef,
deltainf = 10^-5, deltasup = 10^4, nbre_delta = 20,
epsi = 10^-3, error_type = "HC0")