📄 bayes3.m
字号:
% Minimax decision for Gaussian
% Copyright 1999 by Todd K. Moon
f = 1; c = 10; mu = 1; % some starting value
for k=1:20
newmu = qfinv(1/c*(1-qf(mu-f)))
if(abs(newmu - mu) < 1.e-4) break; end;
mu = newmu;
end
eta = f*mu - d^2/2;
% find the value of the game (L10=1) (both ways to verify minimax)
L10 = 1;
r1 = L10*(1-qf(mu-f));
r2 = c*L10*qf(mu);
% find the lfp (method 1)
s = c * (exp(-(mu)^2/2) / exp(-(mu-f)^2/2));
p0 = 1/(s+1)
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -