sim.data {denpro} | R Documentation |

Returns a random sample from some distributions, to illustrate some visulization tools. Returns also the density (as a piecewise constant function) for some examples, or the distribution function.

sim.data(n = NULL, seed = 1, N = NULL, type = "mulmod", M = NULL, sig = NULL, p = NULL, d = NULL, cova = NULL, marginal = NULL, t = NULL, df = NULL, distr = FALSE, noisedim = 1, sig1 = 0.5, sig2 = 1.5, diff = 0.1, dist = 4)

`n` |
positive integer; size of the sample to be generated |

`seed` |
real number; seed for the random number generator. |

`N` |
2*1 vector of positive integers; the size of the grid where the piecewise constant function is evaluated |

`type` |
"mixt", "mulmod", "fox", "tetra3d", "penta4d", "cross", "gauss", "student", "gumbel", "1d2modal", or "claw". |

`M` |
mixnum*d-matrix; rows of M are means of the Gaussians in the mixture. We have a mixture of "mixnum" Gaussians, whose dimension is d. |

`sig` |
mixnum*d-matrix; rows of sig are the diagonals of the covariance matrices of the mixtures. |

`p` |
mixnum-vector; weights for the members of the mixture. The sum of elements of "p" is 1. |

`d` |
positive integer; dimension of the vectors of the sample to be generated, need to be given only when type="mixt" and d=1 |

`cova` |
Covariance matrix for the Gauss or Student copulas |

`marginal` |
NULL, "gauss", or "student"; this parameter is used to give the marginal distribution for the Gauss or Student copulas; if marginal=NULL, then the uniform marginals are used |

`t` |
if marginal="student", gives the degrees of freedom |

`df` |
degrees of freedom for the Student copula |

`distr` |
internal (implemented for "1d2modal") TRUE, if one wants the distribution function instead of the density function |

`noisedim` |
the number of noise dimension in the projection pursuit example ("fssk") |

`sig1` |
standard deviation for "cross" and "diff1d" |

`sig2` |
second standard deviation for "cross" |

`diff` |
parameter for "diff1d"; the difference between the Gaussians in the 1D mixture |

`dist` |
a positive real number; gives the distance between the mixture centers in the 4D mixture of Gaussians "penta4d" |

When type="mixt", generates data from a mixture of Gaussians. When type="mulmod", the density is 3-modal. When type="fox", the density has multimodal level sets.

If "n" is not NULL, then the function returns a n*d-data matrix or a n*2-data matrix, if "N" is not NULL, then the function returns a piecewise constant function on the grid of size N[1]*N[2], if the both are NULL, then the function returns the mean, covariance, and the weights of the mixture components

Jussi Klemela

d<-2 mixnum<-3 M<-matrix(0,mixnum,d) M[1,]<-c(0,0) M[2,]<-c(4,0) M[3,]<-c(0,4) sig<-matrix(1,mixnum,d) p0<-1/mixnum p<-p0*rep(1,mixnum) n<-100 dendat<-sim.data(type="mixt",n=n,M=M,sig=sig,p=p,seed=1) plot(dendat) dendat<-sim.data(n=100) plot(dendat) N<-c(20,20) pcf<-sim.data(N=N) dp<-draw.pcf(pcf,pnum=c(30,30)) contour(dp$x,dp$y,dp$z,drawlabels=FALSE) sim.data() type="fox" dendat<-sim.data(n=100,type=type) plot(dendat) pcf<-sim.data(N=N,type=type) dp<-draw.pcf(pcf,pnum=c(30,30)) contour(dp$x,dp$y,dp$z,drawlabels=FALSE)

[Package *denpro* version 0.9.0 Index]