Description Usage Arguments Details Value References See Also Examples

Function for calculating the negative log-likelihood for ordinal quantile model with more than 3 outcomes.

1 | ```
qrnegLogLikensum_or1(deltaIn, y, x, beta, p)
``` |

`deltaIn` |
initialization of cut-points. |

`y` |
observed ordinal outcomes, column vector of dimension |

`x` |
covariate matrix of dimension |

`beta` |
column vector of coefficients of dimension |

`p` |
quantile level or skewness parameter, p in (0,1). |

Computes the negative of the log-likelihood function for ordinal quantile regression model with more than 3 outcomes.

Returns a list with components

`nlogl`

: vector with likelihood values.`negsumlogl`

: scalar with value of negative log-likelihood.

Rahman, M. A. (2016). “Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24. DOI: 10.1214/15-BA939

likelihood maximization

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
set.seed(101)
deltaIn <- c(-0.002570995, 1.044481071)
data("data25j4")
x <- data25j4$x
y <- data25j4$y
p <- 0.25
beta <- c(0.3990094, 0.8168991, 2.8034963)
output <- qrnegLogLikensum_or1(deltaIn, y, x, beta, p)
# nlogl
# 0.7424858
# 1.1649645
# 2.1344390
# 0.9881085
# 2.7677386
# 0.8229129
# 0.8854911
# 0.3534490
# 1.8582422
# 0.9508680 .. soon
# negsumlogl
# 663.5475
``` |

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