The function performs PCA on matrix based on weighted relative likelihood function and provides a plot of first two PCs as well as summary of PCA.

1 | ```
pois.rel.pca(x, lambda.min, lambda.max, len = 10, plot = TRUE, seed = 132)
``` |

`x` |
Data can be entered as matrix or list. |

`lambda.min` |
Minimum value of lambda. |

`lambda.max` |
Maximum value of lambda. |

`len` |
Length of values to be evaluated at in between mu.min and mu.max. |

`plot` |
If set TRUE, provides plot of weighted relative likelihood functions colored by their cluster assignment. |

`seed` |
Seed to be set for reproducibility |

For mathematical details, please contact the authors.

`PCA.output` |
Summary of Principal Component Analysis |

None.

Milan Bimali.

None.

1 2 | ```
x <- sim.pois(c(4,10),15,10)
pois.rel.pca(x,1,20,len=20,plot=TRUE,seed=132)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

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