📄 logn_pdf.m
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function pdf = logn_pdf (x, a, v)
% PURPOSE: pdf of the lognormal distribution
%--------------------------------------------------------------
% USAGE: pdf = logn_pdf(x,a,v)
% where: x = x = matrix or vector
% a = mean, a = scalar or size(x), default = 1
% v = variance b = scalar or size(x), default = 1
% NOTE: the logarithm of a lognormal random deviate is
% normally distributed with mean = a and variance = v
%--------------------------------------------------------------
% RETURNS: pdf at each element of x of the lognormal distribution
%--------------------------------------------------------------
% SEE ALSO: logn_d, logn_pdf, logn_inv, logn_rnd
% -------------------------------------------------------------
% Written by KH (Kurt.Hornik@ci.tuwien.ac.at)
% Converted to MATLAB by JP LeSage, jpl@jpl.econ.utoledo.edu
if ~((nargin == 1) | (nargin == 3))
error('Wrong # of arguments to logn_pdf');
end
if (nargin == 1)
a = 1;
v = 1;
end
% The following "straightforward" implementation unfortunately does
% not work for the special cases (Inf, ...)
% pdf = (x > 0) ./ x .* normal_pdf (log (x), log (a), v);
% Hence ...
[retval, x, a, v] = com_size(x, a, v);
if (retval > 0)
error('logn_pdf: x, m and v must be of common size or scalars');
end
[r, c] = size (x);
s = r * c;
x = reshape (x, 1, s);
a = reshape (a, 1, s);
v = reshape (v, 1, s);
pdf = zeros (1, s);
k = find(isnan(x) | ~(a > 0) | ~(a < Inf) ...
| ~(v > 0) | ~(v < Inf));
if any(k)
pdf(k) = NaN * ones(1, length (k));
end
k = find((x > 0) & (x < Inf) & (a > 0) & (a < Inf) ...
& (v > 0) & (v < Inf));
if any (k)
pdf(k) = norm_pdf(log(x(k)), log(a(k)), v(k)) ./ x(k);
end
pdf = reshape(pdf, r, c);
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