#include<RcppArmadillo.h>

// [[Rcpp::depends(RcppArmadillo)]]

#include"dmcp.h"

#include<Rmath.h>

#include<iostream>

#include<stdio.h>

using namespace Rcpp;

using namespace arma;

using namespace R;

//' This function obtains the first derivative function of MCP (Minimax Concave Penalty)

//' @param theta a coefficient vector.

//' @param lambda the tuning parameter.

//' @param gamma the regularization parameter in MCP (Minimax Concave Penalty).

//' It balances between the unbiasedness and concavity of MCP.

//' @return the first derivative of MCP function.

//' @details

//' Rigorously speaking, the regularization parametre \eqn{\gamma} needs to be obtained via a data-driven approach.

//' Published studies suggest experimenting with a few values, such as 1.8, 3, 4.5, 6, and 10, then fixing its value. In our numerical

//' study, we have examined this sequence and found that the results are not sensitive to the choice of value of \eqn{\gamma},

//' and set the value at 3. In practice, to be prudent, values other than 3 should also be investigated.

//'

//' @examples

//' theta=runif(20,-5,5)

//' lambda=1

//' gamma=3

//' dmcp(theta,lambda,gamma)

//' @export

// [[Rcpp::export()]]

arma::vec dmcp(arma::vec& theta, double lambda, double gamma){

int p=theta.size();

arma::vec b(p,arma::fill::zeros),

b1(p,arma::fill::zeros);

for(int i=0; i<p; i++){

if(std::abs(theta(i))<=lambda*gamma){

b1(i)=1;

}

b(i)=(lambda-std::abs(theta(i))/gamma)*b1(i);

}

return b;

}