Description Usage Arguments Details Value Author(s) References See Also Examples

Functions for generating a sequence of plots of
the density and cdf of the consecutive standardized and centered sums of iid
r.v. distributed according to a prescribed discrete or absolutely continuous
distribution compared to the standard normal — uses the generic function
`plotCLT`

.

1 2 | ```
illustrateCLT(Distr, len, sleep = 0)
illustrateCLT.tcl(Distr, k, Distrname)
``` |

`Distr` |
object of class |

`len` |
integer: up to which number of summands plots are generated |

`k` |
integer: number of summands for which a plot is to be generated |

`Distrname` |
character: name of the summand distribution to be used as title in the plot |

`sleep` |
numeric: pause in seconds between subsequent plots |

`illustrateCLT`

generates a sequence of plots, while
`illustrateCLT.tcl`

may be used with Tcl/Tk-widgets as in demo
`illustCLT_tcl.R`

.

void

Matthias Kohl [email protected]

Peter Ruckdeschel [email protected]

Kohl, M., Ruckdeschel, P., (2014):
General purpose convolution algorithm for distributions
in S4-Classes by means of FFT. *J. Statist. Softw.*
**59**(4): 1-25.

1 2 3 4 5 6 7 | ```
distroptions("DefaultNrFFTGridPointsExponent" = 13)
illustrateCLT(Distr = Unif(), len = 10)
distroptions("DefaultNrFFTGridPointsExponent" = 12)
illustrateCLT(Distr = Pois(lambda = 2), len = 10)
distroptions("DefaultNrFFTGridPointsExponent" = 13)
illustrateCLT(Distr = Pois(lambda = 2)+Unif(), len = 10)
illustrateCLT.tcl(Distr = Unif(), k = 4, "Unif()")
``` |

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