Linear quadratic family that assumes the following relation for the *variance*
of the normal distribution `Var = mu*(1+s*mu)`

.
regression on mu and on the sigma (log and identity links)

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
dLQNO(x, mu = 1, sigma = 1, log = FALSE)
pLQNO(q, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
qLQNO(p, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
rLQNO(n, mu = 1, sigma = 1)
LQNO(mu.link="log", sigma.link="log")
dLQNO(x, mu = 1, sigma = 1, log = FALSE)
pLQNO(q, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
qLQNO(p, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
rLQNO(n, mu = 1, sigma = 1)
``` |

`mu.link` |
type of transformation |

`sigma.link` |
type of transformation |

`x` |
vector of quantiles. |

`mu` |
vector of means. |

`sigma` |
vector of standard deviations. |

`log` |
logical; if TRUE, probabilities p are given as log(p). |

`q` |
vector of quantiles. |

`lower.tail` |
logical; if TRUE (default), probabilities are P(X < x) otherwise, P(X > x). |

`log.p` |
logical; if TRUE, probabilities p are given as log(p). |

`p` |
vector of probabilities. |

`n` |
number of observations. If length(n) > 1, the length is taken to be the number required. |

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