Description Usage Arguments Details Value Author(s) References Examples

Test whether copy number has an effect on mRNA expression.

1 | ```
plrs.test(object, alpha=0.05)
``` |

`object` |
An object of class |

`alpha` |
Significance level |

Two cases present themselves:

1. The model is unconstrained. Thus, the model under the null hypothesis is the intercept
and an F-test is performed.

2. The model is constrained and the following hypothesis are tested:

H0: All constraints are actives (=)

H1: At least one constraint is strict (>)

Under H0, we always have the intercept model. Indeed, if `constr.slopes = 1`

(or 2) and
`constr.intercepts = T`

, then the only parameter free of inequality constraint is the
overall intercept. If `constr.intercepts = F`

, the local intercepts are additionnaly
constrained to be 0 in order to obtain the intercept model under the null.
The likelihood ratio statistic (unknown variance) is asymptotically distributed as a
weighted mixture of Beta distribution (cf Gromping (2010)). Calculation of p-values is based on
functions `ic.weights`

and `pbetabar`

of package ic.infer. The package
mvtnorm is also involved.

In both cases the input model is taken as the model under the alternative.

A `list`

object with the following components:

`stat` |
Test statistic |

`pvalue` |
Calculated pvalue |

`wt.bar` |
Weights (if the model is constrained) |

`df.bar` |
Degrees of freedom. |

`unconstr` |
Unconstrained model of class |

`qbetabar` |
(1- |

`alpha` |
Significance level |

Gwenael G.R. Leday g.g.r.leday@vu.nl

Gromping, U. (2010). Inference with linear equality and inequality constraints using
R: The package ic.infer. *J Stat Softw*, 33(i10).

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