WRAYLSTAT Mean and variance for the Rayleigh distribution. CALL: [m,v] = wraylstat(b) m, v = the mean and variance, respectively b = parameter of the Rayleigh distribution (see wraylcdf) Mean (m) and variance (v) for the Rayleigh distribution is m=b*(pi/2)^(1/2) and v=(2-pi/2)*b^2; Example: [m,v] = wraylstat(1/(pi/2)^(1/2)) See also wraylcdf
Joint 2D CDF computed as int F(X1 | |
Mean and variance for the DIST2D distribution | |
Mean and variance for the MDIST2D distribution. |
001 function [m,v]= wraylstat(b); 002 %WRAYLSTAT Mean and variance for the Rayleigh distribution. 003 % 004 % CALL: [m,v] = wraylstat(b) 005 % 006 % m, v = the mean and variance, respectively 007 % b = parameter of the Rayleigh distribution (see wraylcdf) 008 % 009 % Mean (m) and variance (v) for the Rayleigh distribution is 010 % 011 % m=b*(pi/2)^(1/2) and v=(2-pi/2)*b^2; 012 % 013 % Example: 014 % [m,v] = wraylstat(1/(pi/2)^(1/2)) 015 % 016 % See also wraylcdf 017 018 % Reference: Cohen & Whittle, (1988) "Parameter Estimation in Reliability 019 % and Life Span Models", p. 181 ff, Marcel Dekker. 020 021 %tested on: matlab 5.3 022 % history 023 % revised pab 24.10.2000 024 % Added checks on b 025 026 027 028 error(nargchk(1,1,nargin)) 029 030 % Initialize Mean and Variance to zero. 031 m = zeros(size(b)); 032 v = zeros(size(b)); 033 034 ok = (b > 0); 035 k = find(ok); 036 if any(k) 037 m(k) = b(k) * sqrt(pi/2); 038 v(k) = (2 - pi/2) * b(k) .^ 2; 039 end 040 041 k1 = find(~ok); 042 if any(k1) 043 tmp = NaN; 044 m(k1) = tmp(ones(size(k1))); 045 v(k1) = m(k1); 046 end 047 048 049 050 051 052
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