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kappa0

PURPOSE

Compute the constants for `tube-formula' based simultaneous

SYNOPSIS

function kap=kappa0(x,y,varargin)

DESCRIPTION

Compute the constants for `tube-formula' based simultaneous
confidence bands.

Works for regression models only. Density estimation problems
should be converted to counts, and use poisson regression
'family','poisson'.

Essentially, this is a front-end to locfit, and so all optional
arguments to locfit (eg, smoothing parameters) can be provided.

To compute (or plot) the confidence bands, provide the output
of the kappa0() function as the 'kappa' argument to a
predict() or lfband() call.

Example:

fit = locfit(E,NOx,'alpha',0.5)
kap = kappa0(E,NOx,'alpha',0.5)  % give same arguments!
lfplot(fit)
lfband(fit,'kappa',kap)     % plot the simultaneous bands
z = predict(fit,[0.6 0.7 0.8]','kappa',kap,'band','g')
z{3}                        % evaluate the bands.

CROSS-REFERENCE INFORMATION

This function calls:
• locfit Smoothing noisy data using Local Regression and Likelihood.
This function is called by:
• scb Simultaneous Confidence Bands

SOURCE CODE

0001 function kap=kappa0(x,y,varargin)
0002
0003 % Compute the constants for `tube-formula' based simultaneous
0004 % confidence bands.
0005 %
0006 % Works for regression models only. Density estimation problems
0007 % should be converted to counts, and use poisson regression
0008 % 'family','poisson'.
0009 %
0010 % Essentially, this is a front-end to locfit, and so all optional
0011 % arguments to locfit (eg, smoothing parameters) can be provided.
0012 %
0013 % To compute (or plot) the confidence bands, provide the output
0014 % of the kappa0() function as the 'kappa' argument to a
0015 % predict() or lfband() call.
0016 %
0017 %
0018 % Example:
0019 %
0021 % fit = locfit(E,NOx,'alpha',0.5)
0022 % kap = kappa0(E,NOx,'alpha',0.5)  % give same arguments!
0023 % lfplot(fit)
0024 % lfband(fit,'kappa',kap)     % plot the simultaneous bands
0025 % z = predict(fit,[0.6 0.7 0.8]','kappa',kap,'band','g')
0026 % z{3}                        % evaluate the bands.
0027
0028 fit = locfit(x,y,'module','kappa','ev','grid','mg',20,varargin{:});
0029 z = fit.fit_points.kappa;
0030 d = size(fit.data.x,2);
0031 kap = z(1:(d+1));
0032
0033 return;

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