% Calculates the lack-of-fit
function [LOF] = calculateLOF(RSS,N,D,k,RSS0,nbetas)
% RSS0 is equivalent to SS_{all} in thesis, and is basically the RSS with
% only intercept in model.  nbetas is the number of slope parameters in
% the model.

% k is the dimension of y (i.e. number of time points).

T = N*k; % T is number of data points.

LOF = RSS/(1-D/N)^2;
%LOF = 0.5*RSS-D*log(N)/2;

%m-BIC for variance unknown case.
% mainpenaltyterm = -D*log(N)/2;
% firstterm =  ((T-nbetas+1)/2)*log(RSS0/RSS);
% sumsq_overall_term = (nbetas/2)*log(RSS0);
% gamma_term = gammaln((T-nbetas-1)/2) - gammaln((T-1)/2);
% LOF= firstterm+sumsq_overall_term+gamma_term + mainpenaltyterm;
% LOF=-LOF;