[SOLVED] OH 43606

function results=ols(y,x)
% PURPOSE: least-squares regression
%
% USAGE: results = ols(y,x)

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% where: y = dependent variable vector(nobs x 1)
%x = independent variables matrix (nobs x nvar)
%
% RETURNS: a structure
%results.meth= ols
%results.beta= bhat (nvar x 1)
%results.tstat = t-stats(nvar x 1)
%results.bstd= std deviations for bhat (nvar x 1)
%results.yhat= yhat (nobs x 1)
%results.resid = residuals (nobs x 1)
%results.sige= e*e/(n-k) scalar
%results.rsqr= rsquared scalar
%results.rbar= rbar-squared scalar
%results.dw= Durbin-Watson Statistic
%results.nobs= nobs
%results.nvar= nvars
%results.y = y data vector (nobs x 1)
%results.bint= (nvar x2 ) vector with 95% confidence intervals on beta
%
% SEE ALSO: prt(results), plt(results)
%

% written by:
%. LeSage, Dept of Economics
% University of Toledo
% 2801 W.,
% Toledo, OH 43606
% (CICG Equity)
% added the 95% confidence intervals on bhat

if (nargin ~= 2); error(Wrong # of arguments to ols);
[nobs nvar] = size(x); [nobs2 junk] = size(y);
if (nobs ~= nobs2); error(x and y must have same # obs in ols);

results.meth = ols;
results.y = y;
results.nobs = nobs;
results.nvar = nvar;

if nobs < 10000 [q r] = qr(x,0); xpxi = (r’*r)eye(nvar); else % use Cholesky for very large problems xpxi = (x’*x)eye(nvar);results.beta = xpxi*(x’*y); results.yhat = x*results.beta; results.resid = y – results.yhat; sigu = results.resid’*results.resid; results.sige = sigu/(nobs-nvar); tmp = (results.sige)*(diag(xpxi)); sigb=sqrt(tmp); results.bstd = sigb; tcrit=-tdis_inv(.025,nobs); results.bint=[results.beta-tcrit.*sigb, results.beta+tcrit.*sigb]; results.tstat = results.beta./(sqrt(tmp)); ym = y – mean(y); rsqr1 = sigu; rsqr2 = ym’*ym; results.rsqr = 1.0 – rsqr1/rsqr2; % r-squared rsqr1 = rsqr1/(nobs-nvar); rsqr2 = rsqr2/(nobs-1.0); if rsqr2 ~= 0 results.rbar = 1 – (rsqr1/rsqr2); % rbar-squared results.rbar = results.rsqr; ediff = results.resid(2:nobs) – results.resid(1:nobs-1); results.dw = (ediff’*ediff)/sigu;% durbin-watson CS: assignmentchef QQ: 1823890830 Email: [email protected]