Exponential CDF
p = distfun_expcdf ( x , mu ) p = distfun_expcdf ( x , mu , lowertail )
a matrix of doubles
a matrix of doubles, the average. mu>0
a 1-by-1 matrix of booleans, the tail (default lowertail=%t). If lowertail is true (the default), then considers P(X<=x) otherwise P(X>x).
a matrix of doubles, the probability
This function computes the Exponential CDF.
Any scalar input argument is expanded to a matrix of doubles of the same size as the other input arguments.
Any optional input argument equal to the empty matrix will be set to its default value.
x = 2 mu = 1/3 computed = distfun_expcdf ( x , mu ) expected = 9.975212478233337e-1 // http://en.wikipedia.org/wiki/Exponential_distribution scf(); x = linspace(0,5,1000); p = distfun_expcdf ( x , 2 ); plot(x,p, "r-" ); p = distfun_expcdf ( x , 1 ); plot(x,p, "m-" ); p = distfun_expcdf ( x , 2/3 ); plot(x,p, "c-" ); xtitle("Exponential CDF","x","$P(X\leq x)$"); legend(["mu=2","mu=1","mu=2/3"]); // See upper tail p = distfun_expcdf ( 2 , 1/3 ) q = distfun_expcdf ( 2 , 1/3 , %f ) p+q // See accuracy for small x p = distfun_expcdf ( 1.e-20 , 1 ) expected = 1.e-20 // For negative inputs, the probability is // zero distfun_expcdf(-10,2) | ![]() | ![]() |
Wikipedia, Exponential distribution function, http://en.wikipedia.org/wiki/Exponential_distribution