Search Java Classes and Packages
#Com.numericalmethod.suanshu.analysis.function.special.gaussian Classes and Interfaces - 8 results found.
| Name | Description | Type | Package | Framework |
| CumulativeNormalHastings | Hastings algorithm is faster but less accurate way to compute the cumulative standard Normal. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| CumulativeNormalInverse | The inverse of the cumulative standard Normal distribution function is defined as: This implementation uses the Beasley-Springer-Moro algorithm. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| CumulativeNormalMarsaglia | Marsaglia is about 3 times slower but is more accurate to compute the cumulative standard Normal. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Erf | The Error function is defined as: operatorname{erf}(x) = frac{2}{sqrt{pi}}int_{0}^x e^{-t^2} dt | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Erfc | This complementary Error function is defined as: operatorname{erfc}(x) | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| ErfInverse | The inverse of the Error function is defined as: operatorname{erf}^{-1}(x) | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Gaussian | The Gaussian function is defined as: f(x) = a e^{- { frac{(x-b)^2 }{ 2 c^2} } } | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| StandardCumulativeNormal | The cumulative Normal distribution function describes the probability of a Normal random variable falling in the interval ((-infty, x]). | Interface | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |