Description Usage Arguments Value Author(s) References Examples

Create positive definite matrices without nuisance parameters. Tabulate distribution. Calculate goodness of fit

1 2 | ```
testunknown(x, pvector, k, diagnose.s = FALSE, diagnose = FALSE,
verbose = TRUE)
``` |

`x ` |
Name of matrix or array. |

`pvector` |
Dimensionality of random vectors |

`k ` |
Number of cuts per unit for diagonal elements of matrix. Program uses 2k cuts per unit for off-diagonal elements |

`diagnose.s ` |
Logical T causes printing of diagnostic terms in internal called function(s) |

`diagnose ` |
Logical. T causes printing of diagnostic content |

`verbose ` |
Logical. T causes printing of function ID before and after running |

a list including elements

`Distribution` |
List. Count of pd matrices within individual subcubes of pd space, 1 for each layer of list |

`Goodness of fit` |
List. Chi square test of goodness of fit to uniform distribution, 1 for each layer of list |

`Call` |
Call to testunknown function |

William R. Fairweather

Csorgo, M and Seshadri, V (1970). On the problem of replacing composite hypotheses by equivalent simple ones, Rev. Int. Statist. Instit., 38, 351-368 Csorgo,M and Seshadri,V (1971). Characterizing the Gaussian and exponential laws by mappings onto the unit interval, Z. Wahrscheinlickhkeitstheorie verw. Geb., 18, 333-339. Fairweather, WR (1973). A test for multivariate normality based on a characterization. Dissertation submitted in partial fulfillment of the requirements for the Doctor of Philosophy, University of Washington, Seattle WA.

1 2 3 | ```
data(unknown.Np2)
testunknown(x=unknown.Np2, pvector=2, k=20,
diagnose.s = FALSE, diagnose = FALSE, verbose = TRUE)
``` |

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