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# lf_censor

## SYNOPSIS function fit = lf_censor(x,y,cens,varargin)

## DESCRIPTION ``` Censored local regression using normal assumption.
Must provide x, y and cens.
All other arguments to locfit() can be provided, with the
exception of weights.

NEED: Kaplan Meier Estimate. Iterations are fixed.```

## CROSS-REFERENCE INFORMATION This function calls:
• fitted Fitted values from a locfit object.
• locfit Smoothing noisy data using Local Regression and Likelihood.
• rsum
This function is called by:

## SOURCE CODE ```0001 function fit = lf_censor(x,y,cens,varargin)
0002 %
0003 % Censored local regression using normal assumption.
0004 % Must provide x, y and cens.
0005 % All other arguments to locfit() can be provided, with the
0006 % exception of weights.
0007 %
0008 % NEED: Kaplan Meier Estimate. Iterations are fixed.
0009 %
0010
0011 lfc_y = y;
0012 unc = find(~cens);
0013
0014 for i = 0:3
0015   fit = locfit(x,lfc_y,varargin{:});
0016   fh = fitted(fit);
0017
0018   rs = rsum(fit);
0019   df0 = rs(1);
0020   df1 = rs(2);
0021
0022   rdf = sum(1-cens) - 2*df0 + df1;
0023   sigma = sqrt(sum( (y-fh).*(lfc_y-fh) / rdf));
0024   sr = (y-fh)/sigma;
0025   lfc_y = fh + sigma*normpdf(sr)./normcdf(-sr);
0026   lfc_y(unc) = y(unc);
0027 end;
0028
0029 return;```

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