Class: distribution.continuous.normal.class — distribution.continuous.normal.class • mastiff

Derived class for a normally-distributed random variable.

Super classes

R6.class.class -> distribution.abstract.class -> distribution.continuous.class -> distribution.continuous.normal.class

interfaces: The list of available class interfaces
mean: The mean of a normal distribution with rate $params$rate.
sd: The standard deviation of a normal distribution with rate $params$rate.
var: The variance of a normal distribution with rate $params$rate.

Create a new object of class distribution.continuous.normal.class

distribution.continuous.normal.class$new(mean, sd)

Density function for a normal random variable with mean $params$mean and standard deviation $params$sd.

distribution.continuous.normal.class$d(x, log = FALSE)

Cumulative density function for a normal random variable with mean $params$mean and standard deviation $params$sd.

distribution.continuous.normal.class$p(q, lower.tail = TRUE, log.p = FALSE)

q: vector of quantiles.
lower.tail: logical; if TRUE (default), probabilities are $P[ X \leq x ]$, otherwise, $P[X>x]$.
log.p: logical; if TRUE, probabilities p are given as log(p).

Quantile function for a normal random variable with mean $params$mean and standard deviation $params$sd.

distribution.continuous.normal.class$q(p, lower.tail = TRUE, log.p = FALSE)

p: vector of probabilities.
lower.tail: logical; if TRUE (default), probabilities are $P[ X \leq x ]$, otherwise, $P[X>x]$.
log.p: logical; if TRUE, probabilities p are given as log(p).

Generates random deviates for a normal random variable with mean $params$mean and standard deviation $params$sd.

distribution.continuous.normal.class$r(n)

n: number of observations. If length( n ) > 1, the length is taken to be the number required.

The objects of this class are cloneable with this method.

distribution.continuous.normal.class$clone(deep = FALSE)