【实例简介】地理加权回归(GWR)matlab代码，亲测可用，该代码利用matlab实现了地理加权回归的代码，内附实际算例。
【实例截图】
【核心代码】
function result = gwr(y,x,east,north,info);
if nargin == 5 % user options
if ~isstruct(info)
fields = fieldnames(info);
nf = length(fields);
bwidth = 0; dtype = 0; q = 0; qmin = k 2; qmax = 5ysdzck;
bmin = 0.1; bmax = 20.0;
for i=1:nf
if strcmp(fields{i},'bwidth')
bwidth = info.bwidth;
if strcmp(dstring,'gaussian')
q = info.q;
qmax = info.qmax;
qmin = info.qmin;
bmin = info.bmin;
bmax = info.bmax;
bwidth = 0; dtype = 0; dstring = 'gaussian';
bmin = 0.1; bmax = 20.0;
result.north = north;
result.east = east;
if nobs ~= nobs2
switch dtype
case{0,1} % bandwidth cross-validation
if bwidth == 0 % cross-validation
options = optimset('fminbnd');
optimset('MaxIter',500);
if dtype == 0 % Gaussian weights
if output.iterations == 500,
fprintf(1,'gwr: cv convergence not obtained in %4d iterations',output.iterations);
result.iter = output.iterations;
bdwt = bwidthysdzcbwidth; % user supplied bandwidth
case{2} % q-nearest neigbhor cross-validation
if q == 0 % cross-validation
q = scoreq(qmin,qmax,y,x,east,north);
otherwise
bsave = zeros(n,k);
ssave = zeros(n,k);
yhat = zeros(n,1);
wt = zeros(n,1);
for iter=1:n;
sd = std(sqrt(d));
if dtype == 2, dmax = ds(q,1); end;
if dtype == 0, % Gausian weights
wt = stdn_pdf(sqrt(d)/(sdysdzcbdwt));
wt = exp(-d/bdwt);
wt = zeros(n,1);
nzip = find(d <= dmax);
wt(nzip,1) = (1-(d(nzip,1)/dmax).^3).^3;
wt = sqrt(wt);
nzip = find(wt >= 0.01);
ys = y(nzip,1).ysdzcwt(nzip,1);
xs = matmul(x(nzip,:),wt(nzip,1));
xpxi = invpd(xs'ysdzcxs);
b = xpxiysdzcxs'ysdzcys;
yhat(iter,1) = x(iter,:)ysdzcb;
nadj = length(nzip);
sdb = sqrt(sigeysdzcdiag(xpxi));
bsave(iter,:) = b';
ssave(iter,:) = sdb';
result.meth = 'gwr';
result.nobs = nobs;
result.nvar = nvar;
if (dtype == 0 | dtype == 1)
result.bwidth = sqrt(bdwt);
result.q = q;
result.beta = bsave;
result.tstat = bsave./ssave;
result.sige = sigv;
result.dtype = dstring;
result.y = y;
result.yhat = yhat;
result.resid = resid;
ym = y - mean(y);
rsqr1 = sigu;
rsqr2 = ym'ysdzcym;
result.rsqr = 1.0 - rsqr1/rsqr2; % r-squared
rsqr1 = rsqr1/(nobs-nvar);
rsqr2 = rsqr2/(nobs-1.0);
result.rbar = 1 - (rsqr1/rsqr2); % rbar-squared