q.sample {asymmetry.measures} | R Documentation |

Returns the quantiles of selected distributions at user specified locations.

q.sample(s,dist, p1=0,p2=1)

`s` |
A scalar or vector: the probabilities where the quantile function will be evaluated. |

`dist` |
Character string, used as a switch to the user selected distribution function (see details below). |

`p1` |
A scalar. Parameter 1 (vector or object) of the selected distribution. |

`p2` |
A scalar. Parameter 2 (vector or object) of the selected distribution. |

Based on user-specified argument `dist`

, the function returns the value of the quantile function at `s`

.

Supported distributions (along with the corresponding `dist`

values) are:

weib: The quantile function for the weibull distribution is implemented as

*Q(s) = p_1 (-\log(1-s))^{1/{p_2}}*where

*p_1*is the shape parameter and*p_2*the scale parameter.lognorm: The lognormal distribution has quantile function implemented as

*Q(s)= \exp≤ft \{ p_1 +√{2p_2^2} \mathrm{erf}^{-1} (2s-1) \right \}*where

*p_1*is the mean,*p_2*is the standard deviation and*\mathrm{erf}*is the Gauss error function.norm: The normal distribution has quantile function implemented as

*Q(p)=Φ^{-1}(s; p_1, p_2)*where

*p_1*is the mean and the*p_2*is the standard deviation.uni: The uniform distribution has quantile function implemented as

*Q(s; p_1, p_2)=s(p_2-p_1)+p_1*for

*p_1 < s < p_2*.cauchy: The cauchy distribution has quantile function implemented as

*Q(s)=p_1 + p_2 \tan ≤ft \{ π ≤ft (s- \frac{1}{2} \right ) \right \}*where

*p_1*is the location parameter and*p_2*the scale parameter.fnorm: The half normal distribution has quantile function implemented as

*Q(s)= p_1√{2} \mathrm{erf}^{-1}(s)*where and

*p_1*is the standard deviation of the distribution.normmix: The quantile function normal mixture distribution is estimated numericaly, based on the built in quantile function.

skewnorm: There is no closed form expression for the quantile function of the skew normal distribution. For this reason, the quantiles are calculated through the

`qsn`

function of the sn package.fas:There is no closed form expression for the quantile function of the Fernandez and Steel distribution. For this reason, the quantiles are calculated through the

`qskt`

function of the skewt package.shash:There is no closed form expression for the quantile function of the Sinh-Arcsinh distribution. For this reason, the quantiles are calculated through the

`qSHASHo`

function of the gamlss package.

A vector containing the quantile values at the user specified points `s`

.

Dimitrios Bagkavos and Lucia Gamez Gallardo

R implementation and documentation: Dimitrios Bagkavos <dimitrios.bagkavos@gmail.com> , Lucia Gamez Gallardo <gamezgallardolucia@gmail.com>

selected.q <- "norm" #select Normal as the distribution shape <- 2 # specify shape parameter scale <- 2 # specify scale parameter xout <- seq(0.1,1,length=50) #design point where the quantile function is evaluated q.sample(xout,selected.q,shape,scale) # calculate quantiles at xout

[Package *asymmetry.measures* version 0.2 Index]