diff rDiff/src/locfit/m/predict.m @ 0:0f80a5141704

version 0.3 uploaded

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/rDiff/src/locfit/m/predict.m	Thu Feb 14 23:38:36 2013 -0500
@@ -0,0 +1,101 @@
+function [y, se] = predict(varargin)
+
+% Interpolate a fit produced by locfit().
+%
+% predict(fit)    produces the fitted values at locfit's selected points.
+% predict(fit,x)  interpolates the fits to points specified by x.
+%
+% Input arguments:
+%   fit   The locfit() fit.
+%   x     Points to interpolate at. May be a matrix with d columns,
+%         or cell with d components (each a vector). In the former
+%         case, a fitted value is computed for each row of x.
+%         In the latter, the components of x are interpreted as
+%         grid margins.
+%         Can also specify 'data' (evaluate at data points);
+%         or 'fitp' (extract the fitted points).
+%  'band',value
+%         Type of standard errors to compute. Default is 'band','n', for none.
+%         Other choices are 'band','g' (use a global s to estimate the resiudal
+%         standard deviation, so standard errors are s*||l(x)||);
+%         'band','l' (use a local s(x), so std. errors are s(x)*||l(x)||);
+%         'band','p' (prediction errors, so s*sqrt(1+||l(x)||^2).
+%  'direct'
+%         Compute the local fit directly (rather than using local
+%         regression, at each point specified by the x argument.
+%  'kappa',vector
+%         Vector of constants for simultaneous confidence bands,
+%         computed by the kappa0() function.
+%  'level',value
+%         Coverage probability for confidence intervals and bands.
+%         Default is 0.95.
+%
+%  Output is a vector of fitted values (if 'band','n'), or a cell
+%  with fitted value, standard error vectors, and matrix of lower
+%  and upper confidence limits.
+%
+%  Note that for local likelihood fits, back-transformation is
+%  not performed, so that (e.g.) for Poisson regression with the
+%  log-link, the output estimates the log-mean, and its standard errors.
+%  Likewise, for density estimation, the output is log(density).
+%
+%  Author: Catherine Loader.
+
+if (nargin<1)
+    error('predict requires fit argument');
+end;
+
+fit = varargin{1};
+
+if (nargin==1) x = 'fitp'; else x = varargin{2}; end;
+
+band = 'n';
+what = 'coef';
+rest = 'none';
+dir  = 0;
+level = 0.95;
+d = size(fit.data.x,2);
+kap = [zeros(1,d) 1];
+
+na = 3;
+while na <= nargin
+  inc = 0;
+  if strcmp(varargin{na},'band')
+    band = varargin{na+1};
+    inc = 2;
+  end;
+  if strcmp(varargin{na},'what')
+    what = varargin{na+1};
+    inc = 2;
+  end;
+  if strcmp(varargin{na},'restyp')
+    rest = varargin{na+1};
+    inc = 2;
+  end;
+  if strcmp(varargin{na},'direct')
+    dir = 1;
+    inc = 1;
+  end;
+  if strcmp(varargin{na},'kappa')
+    kap = varargin{na+1};
+    inc = 2;
+  end;
+  if strcmp(varargin{na},'level')
+    level = varargin{na+1};
+    inc = 2;
+  end;
+  if (inc == 0)
+    disp(varargin{na});
+    error('Unknown argument');
+  end;
+  na = na+inc;
+end;
+
+[y se cb] = mexpp(x,fit,band,what,rest,dir,kap,level);
+if (band=='n')
+    y = y;
+else
+    y = {y se cb};
+end;
+
+return;