function [H, H_lb, H_ub] = calc_H(fname, level, method, biasCorrected, diagnosticPlot, opt1, opt2);

% Hurst index estimate and confidence interval
%
% fname: base file name
% level: >= 1, level of crossings used
% method: 'iid' for iid Z_i, 'srd' for correlated short-range dept Z_i,
%     'lrd for long-range dept Z_i
% biasCorrected: if 1 then bias correction for log transform is included
% diagnosticPlot: if 1 then diagnostic plot required for methods srd or lrd
% opt1, opt2: option parameters, passed to calc_subX_stats
%
% requires functions calc_subX_stats and calc_alpha_exponent
%
% Y.Shen 12.2002, O.D.Jones 7.2003

% calc_subXstats returns mean, variance and 95% CI for subcrossing distribution
if nargin == 5
    [m, m_var, m_lb, m_ub] = calc_subX_stats(fname, level, method, diagnosticPlot);
elseif nargin == 6
    [m, m_var, m_lb, m_ub] = calc_subX_stats(fname, level, method, diagnosticPlot, opt1);
elseif nargin == 7
    [m, m_var, m_lb, m_ub] = calc_subX_stats(fname, level, method, diagnosticPlot, opt1, opt2);
end

if biasCorrected == 1
	% H = log 2/ log mu = f(mu)
	% m is estimator of mu, bias corrected estimator of H is f(m) - f''(m)*m_var/2
	correction = m_var*log(2)/2/(m*log(m))^2*(1 + 2/log(m));
	correction_lb = m_var*log(2)/2/(m_ub*log(m_ub))^2*(1 + 2/log(m_ub));
	correction_ub = m_var*log(2)/2/(m_lb*log(m_lb))^2*(1 + 2/log(m_lb));
else
	correction = 0;
	correction_lb = 0;
	correction_ub = 0;
end
H = 1/log2(m) - correction;
H_lb = 1/log2(m_ub) - correction_ub;
H_ub = 1/log2(m_lb) - correction_lb;