_j_a_c_k_k_n_i_f_e _e_s_t_i_m_a_t_i_o_n
	
	     jackknife(x,theta,...)
	
	_A_r_g_u_m_e_n_t_s:
	
	            x: a vector containing the data. To jackknife
	               more complex data structures (e.g bivariate
	               data) see the last example below.
	
	        theta: function to be jackknifed. Takes x as an
	               argument, and may take additional arguments
	               (see below and last example).
	
	_V_a_l_u_e_s:
	
	     list with the following components
	
	 jack.se: The jackknife estimate of standard error of theta.
	          The leave-one out jackknife is used.
	
	jack.bias: The jackknife estimate of bias of theta.  The
	          leave-one out jackknife is used.
	
	jack.values: The n leave-one-out values of theta, where n is
	          the number of observations.  That is, theta
	          applied to x with the 1st observation deleted,
	          theta applied to x with the 2nd observation
	          deleted, etc.
	
	_R_e_f_e_r_e_n_c_e_s:
	
	     Efron, B. and   Tibshirani, R. (1986).  The Bootstrap
	     Method for standard errors, confidence intervals, and
	     other measures of   statistical accuracy.  Statistical
	     Science, Vol 1., No. 1, pp 1-35.
	
	     Efron, B. and Tibshirani, R. (1993) An Introduction to
	     the Bootstrap.  Chapman and Hall, New York, London.
	
	_E_x_a_m_p_l_e_s:
	
	     # jackknife values for the sample mean
	     # (this is for illustration;  # since "mean" is  a
	     #  built in function,  jackknife(x,mean) would be simpler!)
	     x <- rnorm(20)
	     theta <- function(x)mean(x)
	
	     results <- jackknife(x,theta)
	
	     # To jackknife functions of more  complex data structures,
	     # write theta so that its argument x
	     #  is the set of observation numbers
	     #  and simply  pass as data to jackknife the vector 1,2,..n.
	     # For example, to jackknife
	     # the correlation coefficient from a set of 15 data pairs:
	
	     xdata <- matrix(rnorm(30),ncol=2)
	     n <- 15
	     theta <- function(x,xdata) cor(xdata[x,1],xdata[x,2])
	     results <- jackknife(1:n,theta,xdata)