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// N length of the input data // Normal Distribution assumed.
double mean(double* vec, int N); // Returns mean
double var(double* vec, int N);// Returns Variance
// M Length of the covariance/correlation vector. The maximum lag is M-1 or N-1 , whichever is smaller.
void autocovar(double* vec, int N, double* acov, int M); // Returns autocovariance vector of length min(M-1,N-1) // If M > N , the program will indicate the new length of the returned vector
void autocorr(double* vec, int N, double* acorr, int M); // Returns autocovariance vector of length min(M-1,N-1) // If M > N , the program will indicate the new length of the returned vector
double normalpdf(double x, double mu, double sigma);
double normalcdf(double x, double mu, double sigma);
double normalinv(double p, double mu, double sigma);
double tpdf(double t, int df);
double tcdf(double t, int df);
double tinv_appx(double p, int df);
double tinv(double p, int df);
double fpdf(double x, int k1, int k2);
double fcdf(double x, int k1, int k2);
double finv(double p, int k1, int k2);
double gammapdf(double x, double k, double th);
double gammacdf(double x, double k, double th);
double gammainv(double p, double k, double th);
double chipdf(double x, int df);
double chicdf(double x, int df);
double chiinv(double p, int df);
Reference : Milton Abramowitz, I.A. Stegun, Handbook of Mathematical Functions. (Dover Books on Mathematics)