Density Estimation with a Penalized Mixture Approach

Allianz | Daily final prices (DAX) of the German stock Allianz in the... |

bias.par | Calculating the bias of the parameter beta |

ck | Calculating the actual weights ck |

Derv1 | Calculating the first derivative of the pendensity likelihood... |

Derv2 | Calculating the second order derivative with and without... |

DeutscheBank | Daily final prices (DAX) of the German stock Deutsche Bank in... |

distr.func | These functions are used for calculating the empirical and... |

D.m | Calculating the penalty matrix |

f.hat | Calculating the actual fitted values 'f.hat' of the estimated... |

L.mat | Calculates the difference matrix of order m |

marg.likelihood | Calculating the marginal likelihood |

my.AIC | Calculating the AIC value |

my.bspline | my.bspline |

my.positive.definite.solve | my.positive.definite.solve |

new.beta.val | Calculating the new parameter beta |

new.lambda | Calculating new penalty parameter lambda |

pendenForm | Formula interpretation and data transfer |

pendensity | Calculating penalized density |

pendensity-package | The package 'pendensity' offers routines for estimating... |

pen.log.like | Calculating the log likelihood |

plot.pendensity | Plotting estimated penalized densities |

print.pendensity | Printing the main results of the (conditional) penalized... |

test.equal | Testing pairwise equality of densities |

variance.par | Calculating the variance of the parameters |

variance.val | Calculating variance and standard deviance of each... |

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