function [bootstat, bootsam] = parm_bootstrap(nboot, bootfun, data)
% PARM_BOOTSTRAP - one dimensional normal (gaussian) parametric bootstrap samples
%   
% Input: 
%   data: is a one dimensional matrix (i.e. a vector of lenth ndata) 
% Output: 
%   bootstat: a one dimensional matrix (a vector of length nboot)
%   bootsam: the bootstrap samples used (a matrix of size [ndata,nboot])
% 
% Written by:
% -- 
% John L. Weatherwax                2008-02-20
% 
% email: wax@alum.mit.edu
% 
% Please send comments and especially bug reports to the
% above email address.
% 
%-----

% get the number of data points: 
ndata = length(data);

% estimate the population mean: 
mu = mean( data ); 
% estimate the population standard deviation: 
st = std( data ); 

% draw "nboot" bootstrap samples from the above hypothesized (a Gaussian) density: 
bootsam = normrnd(mu,st,ndata,nboot); 

% evaluate our "bootfun" on these samples (assume the function operates down COLUMNS): 
bootstat = bootfun( bootsam );