Description Usage Arguments Details Value Examples

Setting of inequality constraints on shape parameters.

`hin.SGB`

sets inequality constraints on the shape parameters in a SGB regression.

`hin.SGB.jac`

defines the corresponding Jacobian.

1 2 | ```
hin.SGB(x, d, u, bound, ...)
hin.SGB.jac(x, d, u, ...)
``` |

`x` |
vector of parameters ( |

`d` |
data matrix of explanatory variables (without constant vector) |

`u` |
data matrix of compositions (independent variables) |

`bound` |
the estimates of shapes are constrained by |

`...` |
not used. |

These functions are invoked internally by `regSGB`

with `bound`

specified by the user.

`shape1`

is constrained to be larger than 0.1, in order to avoid numerical problems and `shape2`

must be positive.

Moments of ratios of parts only exist up to `bound`

. Thus `bound = 2.1`

guarantees the existence of variances of ratios of parts.

`hin.SGB`

: vector of length *D+1* with the current value of `c(shape1-0.1,shape1*shape2-bound)`

. It should be non-negative at convergence of the regression algorithm.

`hin.SGB.jac`

: corresponding jacobian matrix of dimensions *(D+1) \times* `length(x)`

.

1 2 3 4 5 6 7 |

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