| p_laplace {errint} | R Documentation |
Probability Density Functions
Description
p_laplace computes the probability density function
of a random variable that has a Laplace distribution with parameters \mu and
\sigma.
p_gaussian computes the probability density function
of a random variable that has a Gaussian distribution with parameters \mu and
{\sigma}^2.
p_beta computes the probability density function
of a random variable that has a Beta distribution with parameters \alpha and
\beta.
p_weibull computes the probability density function
of a random variable that has a Weibull distribution with parameters \kappa
and \lambda.
p_moge computes the probability density function
of a random variable that has a MOGE distribution with parameters \lambda,\alpha
and \theta.
Usage
p_laplace(x, mu = 0, sigma = 1)
p_gaussian(x, mu = 0, sigma_cuad = 1)
p_beta(x, alpha = 1, beta = 1)
p_weibull(x, k = 1, lambda = 1)
p_moge(x, lambda = 1, alpha = 1, theta = 1)
Arguments
x |
vector of points which values we want to compute. |
mu |
location or mean parameter of the Laplace or Gaussian distribution, respectively. |
sigma |
scale parameter of the Laplace distribution. |
sigma_cuad |
variance parameter of the Gaussian distribution. |
alpha |
shape1 parameter of the Beta distribution or second parameter of the MOGE distribution. |
beta |
shape2 parameter of the Beta distribution. |
k |
shape parameter of the Weibull distribution. |
lambda |
scale parameter of the Weibull distribution or first parameter of the MOGE distribution. |
theta |
third parameter of the MOGE distribution. |
Value
Returns a numeric object corresponding to the value
of the probability density function for the given x and distribution parameters.
Author(s)
Jesus Prada, jesus.prada@estudiante.uam.es
References
Link to the scientific paper
Prada, Jesus, and Jose Ramon Dorronsoro. "SVRs and Uncertainty Estimates in Wind Energy Prediction." Advances in Computational Intelligence. Springer International Publishing, 2015. 564-577,
with theoretical background for this package is provided below.
http://link.springer.com/chapter/10.1007/978-3-319-19222-2_47
See Also
Examples
p_laplace(0.3)
p_laplace(0.3,mu=0.35,sigma=0.2)
p_gaussian(0.3)
p_gaussian(0.3,mu=0.35,sigma_cuad=0.2)
p_beta(0.3)
p_beta(0.3,alpha=0.35,beta=0.2)
p_weibull(0.3)
p_weibull(0.3,k=0.35,lambda=0.2)
p_moge(0.3)
p_moge(0.3,lambda=0.2,alpha=0.3,theta=0.4)