acos acosh adaptsimp asin asinh atan atan2 atanh betafn BFGS cbind cbrt ceil chol_solve chol_solve cholesky copy copy_recycle copysign cos cosh crossprod dbeta dbinom dchisq det dexp df dgamma diag dlnorm dlogis dnbinom dnorm dpois dt dt1 dunif dweibull eigen epsilon erf erfc exp expm1 eye fabs factorial floor fmod for_each_ij_set gammafn gaxpy gradfdif gradfdifls hesscdif hypot intsimp inv inv invpd invpd j0 j1 jacfdif jn kronecker kurtosis kurtosisc ldexp lgamma linesearch1 linesearch2 lnbetafn lndbeta1 lndmvn lndnorm lndt1 lnfactorial lngammafn log log10 log1p logb lu_decomp lu_solve lu_solve matrix_order matrix_style max maxc maxind maxindc mean meanc median medianc min minc minind minindc mode modec nls_broyden ones operator! operator!= operator% operator& operator* operator* operator+ operator- operator- operator/ operator< operator<< operator<= operator== operator> operator>= operator>> operator^ operator| order pbeta pbinom pchisq pexp pf pgamma plnorm plogis pnbinom pnorm pow ppois prod prodc pt punif pweibull qnorm1 qr_decomp qr_solve qr_solve rbind rint row_interchange sd sd sdc selif seqa sgn sin sinh skew skewc sort sortc sqrt sum sumc svd t tan tanh unique var var varc vech xpnd y0 y1 yn zoom

template<matrix_order RO, matrix_style RS, typename T , matrix_order PO, matrix_style PS> Matrix<T,RO,RS> scythe::meanc ( const Matrix< T, PO, PS > &  A ) Calculate the mean of each column of a Matrix. This function calculates the mean of each column of a matrix by summing all elements of a column in the matrix, divding by the total number of elements in the column, and looping over every column in the matrix. Parameters: A The matrix to be averaged. See also: sumc(const Matrix<T,PO,PS> &A) mean(const Matrix<T,PO,PS> &A) medianc(const Matrix<T,PO,PS> &A) modec(const Matrix<T,PO,PS> &A) variancec(const Matrix<T,PO,PS> &A)