Description Usage Arguments Value References Examples

The nonparametric likelihood ratio test to test for symmetry is discussed in Gijbels et al. (2019d).

1 2 |

`y` |
This is a vector of quantiles. |

`f` |
This is the reference density function |

`F` |
This is the cumulative distribution function |

`QF` |
This is the quantile function of the reference density |

`method` |
The method to be used for drawing bootstrap samples. The default method is a smooth bootstrap procedure. The density function |

`nboot` |
The number of bootstrap samples desired. The default number is 500. |

The nonparametric likelihood ratio test statistic with bootstrap *P*-value.

Gijbels, I., Karim, R. and Verhasselt, A. (2019d). Test of symmetry and a quantile-based asymmetric family of densities, *Manuscript*.

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# Example 1: Let F be a standard normal cumulative distribution function then
f_N<-function(s){dnorm(s, mean = 0,sd = 1)} # density function of N(0,1)
F_N<-function(s){pnorm(s, mean = 0,sd = 1)} # distribution function of N(0,1)
QF_N<-function(beta){qnorm(beta, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)}
# Example: STRength dataset
my.sample<-c(1.901,2.132,2.203,2.228,2.257,2.350,2.361,2.396,2.397,
2.445,2.454,2.474,2.518,2.522,2.525,2.532,2.575,2.614,2.616,
2.618,2.624,2.659,2.675,2.738,2.740,2.856,2.917,2.928,2.937,
2.937,2.977,2.996,3.030,3.125,3.139,3.145,3.220,3.223,3.235,
3.243,3.264,3.272,3.294,3.332,3.346,3.377,3.408,3.435,3.493,
3.501,3.537,3.554,3.562,3.628,3.852,3.871,3.886,3.971,4.024,
4.027,4.225,4.395,5.020)
NLRTest(my.sample,f=NULL,F=NULL,QF=NULL,method=c("smooth"),nboot=500)
NLRTest(my.sample,f=f_N,F=F_N,QF=QF_N,method=c("parametric"),nboot=500)
NLRTest(my.sample,f=f_N,F=F_N,QF=NULL,method=c("parametric"),nboot=500)
``` |

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