gsm_iter_cpp: Time series creation
In PhilippVWC/myBayes: Functions for time series analysis based on Bayesian methods

Description Usage Arguments Details Value Author(s) Examples

Create time series produced by general symmetric map

1	gsm_iter_cpp(N, x0, r, alpha, N_discr, skipFirst, method)

`N`	integer - Number of iterations
`x0`	double - starting value
`r`	double - controll parameter
`alpha`	double - exponent of general symmetric map
`N_discr`	integer - controlls discretization of state space (zero corresponds to continuous case)
`skipFirst`	Boolean - If set to FALSE, the resulting time series contains the initial value x0
`method`	integer - method of discretization with 1... round routine from base package (fast) or 2... matrix multiplication (slow)

This routine is implemented in C++

vector of type double - the resulting time series

J.C. Lemm, P. v.W. Crommelin

//C++ DEFINITION
Rcpp::NumericVector gsm_iter_cpp(int N, double x0, double r, double alpha, int N_discr,bool skipFirst, int method){
  if(method==1){
    if(N_discr>0){
      N_discr--; //Decrement because the rounding routine maps to N_discr + 1 values
    }
    Rcpp::NumericVector X(N);
    if(skipFirst){
      if(N_discr == 0){
        X[0] = gsm_cpp(x0,r,alpha);
      }else{
        X[0] = round(gsm_cpp(x0,r,alpha)*N_discr)/N_discr;
      }
    }else{
      X[0] = x0;
    }
    if(N>1){
      if(N_discr == 0){
        for(int i=1; i<N ; i++){
          X[i] = gsm_cpp(X[i-1],r,alpha);
        }
      }else{
        for(int i=1; i<N ; i++){
          X[i] = round(gsm_cpp(X[i-1],r,alpha)*N_discr)/N_discr;
        }
      }
    }
    return(X);
  }else{
    return(Dgsm_iter_cpp(N,x0,r,alpha,N_discr,skipFirst));
  }
}