Description Usage Arguments Details Value Author(s) Examples

View source: R/denpro.R View source: R/sim.data.R

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.

1 2 3 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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ```
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)
``` |

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