Lik_Dgsm_cpp: Gaussian likelihood for given data
In PhilippVWC/myBayes: Functions for time series analysis based on Bayesian methods

Description Usage Arguments Details Author(s) References Examples

Generates a time Series generated by the DISCRETIZED version of the general symmetric map (gsm) and computes the likelihood given the data

1	Lik_Dgsm_cpp(alpha, r, x0, Y, sigma, N_discr)

`alpha`	double - exponent of gsm
`r`	double - control parameter of gsm
`x0`	double - initial value of the time series
`Y`	vector of type double - the given data
`sigma`	double - the standard deviation of the gaussian likelihood
`N_discr`	integer - discretization of the state space

This routine is implemented in C++

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

S. Sprott, Chaos and Time-series analysis

//C++ DEFINITION:
double Lik_Dgsm_cpp(double alpha, double r, double x0, Rcpp::NumericVector Y, double sigma, int N_discr){
  int n = Y.size();
  bool skipFirst = true;
  Rcpp::NumericVector X = Dgsm_iter_cpp(n,x0,r,alpha,N_discr,skipFirst);
  double sum = 0;
  for(int i = 0; i<n ; i++){
    sum += pow(Y[i]-X[i],2.0);
  }
  double L = pow(2.0*PI*pow(sigma,2),-0.5*n)*exp(-0.5*sum/pow(sigma,2.0));
  return(L);
}