_C_o_v_a_r_i_a_n_c_e _M_a_t_r_i_c_e_s
	
	     var(x, y=x, na.rm=FALSE, pairwise=FALSE)
	
	_A_r_g_u_m_e_n_t_s:
	
	           x : a matrix or vector.
	
	           y : a matrix or vector.
	
	    pairwise : logical.
	
	       na.rm : logical.
	
	_D_e_s_c_r_i_p_t_i_o_n:
	
	     var computes the variance of x and the covariance of x
	     and y if x and y are vectors. If x and y are matrices
	     then the covariance between the columns of x and the
	     the columns of y are computed.
	
	     If na.rm is TRUE then missing values are removed from
	     the vectors before calculation.  If pairwise is FALSE
	     (the default), missing values in matrices are handled
	     by casewise deletion.  If pairwise is TRUE, all cases
	     which are complete for a pair of variables is used to
	     compute the covariance for that pair of variables.
	     This can result in covariance matrices which are not
	     positive semidefinite.
	
	_E_x_a_m_p_l_e_s:
	
	     var(1:10)
	     # 9.166667
	
	     var(1:5,1:5)
	     # 2.5