Description Usage Arguments Details Value Examples

Generate multinomial samples from a common probability vector and calculate the Chi-square and Likelihood Ratio test statistics.

1 |

`N1` |
Size of sample 1. |

`N2` |
Size of sample 2. |

`p0` |
Common probability vector from which to draw the multinomial samples. Can also be a matrix, in which case each simulation randomly draws with replacement from the rows of p0. |

`nreps` |
Number of replications of the simulation. |

`verbose` |
Logical. If |

The chi-squared and likelihood ratio test statistics are calculated from multinomial samples *(Y_11, Y_21),…,(Y_1M, Y_2M)*, where

*
Y_km ~ind Multinomial(N_k, p_m),
*

where *p_m* is the *m*th row of `p0`

.

An `nreps x 2`

matrix with the simulated chi-squared and LR values.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
# bootstrapped p-value calculation against equal genotype proportions
# in lakes Michipicoten and Simcoe
# contingency table
popId <- c("Michipicoten", "Simcoe")
ctab <- UM.suff(fish215[fish215$Lake %in% popId,])$tab
ctab
# MLE of probability vector
p.MLE <- colSums(ctab)/sum(ctab)
# sample sizes
N1 <- sum(ctab[1,]) # Michipicoten
N2 <- sum(ctab[2,]) # Simcoe
# bootstrapped test statistics (chi^2 and LRT)
T.boot <- UM.eqtest(N1 = N1, N2 = N2, p0 = p.MLE, nreps = 1e3)
# observed test statistics
T.obs <- c(chi2 = chi2.stat(ctab), LRT = LRT.stat(ctab))
# p-values
rowMeans(t(T.boot) > T.obs)
``` |

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