For more information about the functions see the documentation of GSL.
Function | Description |
---|---|
gaussian(x,sigma) | probability density p(x) at X for a Gaussian distribution with standard deviation SIGMA |
ugaussian(x) | unit Gaussian distribution. They are equivalent to the functions above with a standard deviation of one, SIGMA = 1 |
gaussian_tail(x,a,sigma) | probability density p(x) at X for a Gaussian tail distribution with standard deviation SIGMA and lower limit A |
ugaussian_tail(x,a) | tail of a unit Gaussian distribution. They are equivalent to the functions above with a standard deviation of one, SIGMA = 1 |
bivariate_gaussian(x,y,sigma_x,sigma_y,rho) | probability density p(x,y) at (X,Y) for a bivariate gaussian distribution with standard deviations SIGMA_X, SIGMA_Y and correlation coefficient RHO |
exponential(x,mu) | probability density p(x) at X for an exponential distribution with mean MU |
laplace(x,a) | probability density p(x) at X for a Laplace distribution with mean A |
exppow(x,a,b) | probability density p(x) at X for an exponential power distribution with scale parameter A and exponent B |
cauchy(x,a) | probability density p(x) at X for a Cauchy distribution with scale parameter A |
rayleigh(x,sigma) | probability density p(x) at X for a Rayleigh distribution with scale parameter SIGMA |
rayleigh_tail(x,a,sigma) | probability density p(x) at X for a Rayleigh tail distribution with scale parameter SIGMA and lower limit A |
landau(x) | probability density p(x) at X for the Landau distribution |
gamma_pdf(x,a,b) | probability density p(x) at X for a gamma distribution with parameters A and B |
flat(x,a,b) | probability density p(x) at X for a uniform distribution from A to B |
lognormal(x,zeta,sigma) | probability density p(x) at X for a lognormal distribution with parameters ZETA and SIGMA |
chisq(x,nu) | probability density p(x) at X for a chi-squared distribution with NU degrees of freedom |
fdist(x,nu1,nu2) | probability density p(x) at X for an F-distribution with NU1 and NU2 degrees of freedom |
tdist(x,nu) | probability density p(x) at X for a t-distribution with NU degrees of freedom |
beta_pdf(x,a,b) | probability density p(x) at X for a beta distribution with parameters A and B |
logistic(x,a) | probability density p(x) at X for a logistic distribution with scale parameter A |
pareto(x,a,b) | probability density p(x) at X for a Pareto distribution with exponent A and scale B |
weibull(x,a,b) | probability density p(x) at X for a Weibull distribution with scale A and exponent B |
gumbel1(x,a,b) | probability density p(x) at X for a Type-1 Gumbel distribution with parameters A and B |
gumbel2(x,a,b) | probability density p(x) at X for a Type-2 Gumbel distribution with parameters A and B |
poisson(k,mu) | probability p(k) of obtaining K from a Poisson distribution with mean mu |
bernoulli(k,p) | probability p(k) of obtaining K from a Bernoulli distribution with probability parameter P |
binomial(k,p,n) | probability p(k) of obtaining K from a binomial distribution with parameters P and N |
negative_binomial(k,p,n) | probability p(k) of obtaining K from a negative binomial distribution with parameters P and N |
pascal(k,p,n) | probability p(k) of obtaining K from a Pascal distribution with parameters P and N |
geometric(k,p) | probability p(k) of obtaining K from a geometric distribution with probability parameter P |
hypergeometric(k,n1,n2,t) | probability p(k) of obtaining K from a hypergeometric distribution with parameters N1, N2, N3 |
logarithmic(k,p) | probability p(k) of obtaining K from a logarithmic distribution with probability parameter P |