probability density function
121Inverse-chi-square distribution — Probability distribution name =Inverse chi square type =density pdf cdf parameters = u > 0! support =x in (0, infty)! pdf =frac{2^{ u/2{Gamma( u/2)},x^{ u/2 1} e^{ 1/(2 x)}! cdf =Gamma!left(frac{ u}{2},frac{1}{2x} ight)igg/, Gamma!left(frac{… …
122Half-logistic distribution — Probability distribution name =Half logistic distribution type =density pdf cdf parameters = support =k in [0;infty)! pdf =frac{2 e^{ k{(1+e^{ k})^2}! cdf =frac{1 e^{ k{1+e^{ k! mean =log e(4)=1.386ldots median =log e(3)=1.0986ldots mode =0… …
123Rice distribution — Probability distribution name =Rice type =density pdf Rice probability density functions for various nu; with σ = 0.25. cdf Rice cumulative distribution functions for various nu; with σ = 0.25. parameters = uge 0, sigmage 0, support =xin… …
124Cantor distribution — Probability distribution name =Cantor type =mass pdf cdf parameters =none support =Cantor set pdf =none cdf =Cantor function mean =1/2 median =anywhere in [1/3, 2/3] mode =n/a variance =1/8 skewness =0 kurtosis = 8/5 entropy = mgf =e^{t/2} prod… …
125Scale-inverse-chi-square distribution — Probability distribution name =Scale inverse chi square type =density pdf cdf parameters = u > 0, sigma^2 > 0, support =x in (0, infty) pdf =frac{(sigma^2 u/2)^{ u/2{Gamma( u/2)} frac{expleft [ frac{ u sigma^2}{2 x} ight] }{x^{1+ u/2 cdf… …
126Inverse Gaussian distribution — Probability distribution name =Inverse Gaussian type =density pdf | cdf parameters =lambda > 0 mu > 0 support = x in (0,infty) pdf = left [frac{lambda}{2 pi x^3} ight] ^{1/2} exp{frac{ lambda (x mu)^2}{2 mu^2 x cdf = Phileft(sqrt{frac{lambda}{x… …
127Raised cosine distribution — Probability distribution name =Raised cosine type =density pdf | cdf parameters =mu,(real) s>0,(real) support =x in [mu s,mu+s] , pdf =frac{1}{2s}left [1+cosleft(frac{x! !mu}{s},pi ight) ight] , cdf =frac{1}{2}left [1!+!frac{x!… …
128Type-2 Gumbel distribution — Probability distribution name =Type 2 Gumbel| type =density pdf cdf parameters =a! (real) b! shape (real) support = pdf =a b x^{ a 1} e^{ b x^{ a! cdf =e^{ b x^{ a! mean = median = mode = variance = skewness = kurtosis = entropy = mgf = char = In …
