| operators-methods {distr} | R Documentation |
operator-methods
signature(e1 = "UnivariateDistribution"):
application of `-' to this univariate distribution
signature(e1 = "UnivariateDistribution", e2 =
"numeric"):
multiplication of this univariate distribution by an object of class `numeric'
signature(e1 = "UnivariateDistribution", e2 =
"numeric"):
division of this univariate distribution by an object of class `numeric'
signature(e1 = "UnivariateDistribution", e2 =
"numeric"):
addition of this univariate distribution to an object of class `numeric'
signature(e1 = "UnivariateDistribution", e2 =
"numeric"):
subtraction of an object of class `numeric' from this univariate distribution
signature(e1 = "numeric", e2 =
"UnivariateDistribution"):
multiplication of this univariate distribution by an object of class `numeric'
signature(e1 = "numeric", e2 =
"UnivariateDistribution"):
addition of this univariate distribution to an object of class `numeric'
signature(e1 = "numeric", e2 =
"UnivariateDistribution"):
subtraction of this univariate distribution from an object of class `numeric'
signature(e1 = "UnivariateDistribution", e2 =
"UnivariateDistribution"):
Convolution of two univariate distributions. The slots p, d and q are approximated by grids.
signature(e1 = "UnivariateDistribution", e2 =
"UnivariateDistribution"):
Convolution of two univariate distributions. The slots p, d and q are approximated by grids.
signature(e1 = "AbscontDistribution"):
application of `-' to this absolutely continuous distribution
signature(e1 = "AbscontDistribution", e2 = "numeric"):
multiplication of this absolutely continuous distribution by an object of class `numeric'
signature(e1 = "AbscontDistribution", e2 = "numeric"):
division of this absolutely continuous distribution by an object of class `numeric'
signature(e1 = "AbscontDistribution", e2 = "numeric"):
addition of this absolutely continuous distribution to an object of class `numeric'
signature(e1 = "AbscontDistribution", e2 = "numeric"):
subtraction of an object of class `numeric' from this absolutely continuous distribution
signature(e1 = "numeric", e2 = "AbscontDistribution"):
multiplication of this absolutely continuous distribution by an object of class `numeric'
signature(e1 = "numeric", e2 = "AbscontDistribution"):
addition of this absolutely continuous distribution to an object of class `numeric'
signature(e1 = "numeric", e2 = "AbscontDistribution"):
subtraction of this absolutely continuous distribution from an object of class `numeric'
signature(e1 = "AbscontDistribution", e2 =
"AbscontDistribution"):
Convolution of two absolutely continuous distributions. The slots p, d and q are approximated by grids.
signature(e1 = "AbscontDistribution", e2 =
"AbscontDistribution"):
Convolution of two absolutely continuous distributions. The slots p, d and q are approximated by grids.
signature(e1 = "DiscreteDistribution"):
application of `-' to this discrete distribution
signature(e1 = "DiscreteDistribution", e2 =
"numeric"):
multiplication of this discrete distribution by an object of class `numeric'
signature(e1 = "DiscreteDistribution", e2 =
"numeric"):
division of this discrete distribution by an object of class `numeric'
signature(e1 = "DiscreteDistribution", e2 =
"numeric"):
addition of this discrete distribution to an object of class `numeric'
signature(e1 = "DiscreteDistribution", e2 =
"numeric"):
subtraction of an object of class `numeric' from this discrete distribution
signature(e1 = "numeric", e2 =
"DiscreteDistribution"):
multiplication of this discrete distribution by an object of class `numeric'
signature(e1 = "numeric", e2 =
"DiscreteDistribution"):
addition of this discrete distribution to an object of class `numeric'
signature(e1 = "numeric", e2 =
"DiscreteDistribution"):
subtraction of this discrete distribution from an object of class `numeric'
signature(e1 = "DiscreteDistribution", e2 =
"DiscreteDistribution"):
Convolution of two discrete distributions. The slots p, d and q are approximated by grids.
signature(e1 = "DiscreteDistribution", e2 =
"DiscreteDistribution"):
Convolution of two discrete distributions. The slots p, d and q are approximated by grids.
signature(e1 = "numeric", e2 = "Norm"):
multiplication of this normal distribution by an object of class `numeric'
signature(e1 = "numeric", e2 = "Norm"):
addition of this normal distribution to an object of class `numeric'
signature(e1 = "numeric", e2 = "Norm"):
subtraction of this normal distribution from an object of class `numeric'
signature(e1 = "Norm", e2 = "numeric"):
multiplication of this normal distribution by an object of class `numeric'
signature(e1 = "Norm", e2 = "numeric"):
addition of this normal distribution to an object of class `numeric'
signature(e1 = "Norm", e2 = "numeric"):
subtraction of an object of class `numeric' from this normal distribution
signature(e1 = "Norm", e2 = "numeric"):
division of this normal distribution by an object of class `numeric'
signature(e1 = "Norm", e2 = "Norm")signature(e1 = "Norm", e2 = "Norm"):
For the normal distribution the exact convolution formulas are implemented thereby improving the general numerical approximation.
signature(e1 = "Unif", e2 = "numeric"):
multiplication of this uniform distribution by an object of class `numeric'
signature(e1 = "Unif", e2 = "numeric"):
addition of this uniform distribution to an object of class `numeric'
signature(e1 = "Binom", e2 = "Binom"):
For two binomial distributions with the same probabilities the exact convolution formula is implemented thereby improving the general numerical approximation.
signature(e1 = "Pois", e2 = "Pois"):
For the Poisson distribution the exact convolution formula is implemented thereby improving the general numerical approximation.
UnivariateDistribution-class
AbscontDistribution-class
DiscreteDistribution-class
Norm-class
Binom-class
Pois-class