org.ojalgo.random

## Class Normal

• ### Constructor Detail

• #### Normal

public Normal()
• #### Normal

public Normal(double location,
double scale)
• ### Method Detail

• #### getDensity

public double getDensity(double value)
Description copied from interface: ContinuousDistribution
In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. The probability for the random variable to fall within a particular region is given by the integral of this variable's density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one. WikipediA
Parameters:
value - x
Returns:
P(x)
• #### getDistribution

public double getDistribution(double value)
Description copied from interface: ContinuousDistribution
In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable X with a given probability distribution will be found at a value less than or equal to x. Intuitively, it is the "area so far" function of the probability distribution. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. WikipediA
Parameters:
value - x
Returns:
P(≤x)
• #### getExpected

public double getExpected()
• #### getQuantile

public double getQuantile(double probability)
Description copied from interface: ContinuousDistribution
The quantile function, for any distribution, is defined for real variables between zero and one and is mathematically the inverse of the cumulative distribution function. WikipediA The input probability absolutely has to be [0.0, 1.0], but values close to 0.0 and 1.0 may be problematic
Parameters:
probability - P(<=x)
Returns:
x
• #### generate

protected double generate()
• #### getLowerConfidenceQuantile

public final double getLowerConfidenceQuantile(double confidence)
• #### getUpperConfidenceQuantile

public final double getUpperConfidenceQuantile(double confidence)