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view rDiff/src/locfit/m/predict.m @ 0:0f80a5141704
version 0.3 uploaded
author | vipints |
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date | Thu, 14 Feb 2013 23:38:36 -0500 |
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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;