bsyule {degreenet} | R Documentation |
Uses the parametric bootstrap to estimate the bias and confidence interval of the MLE of the Yule Distribution.
bsyule(x, cutoff=1, m=200, np=1, alpha=0.95, v=NULL, hellinger=FALSE, cutabove=1000) bootstrapyule(x,cutoff=1,cutabove=1000, m=200,alpha=0.95,guess=3.31,hellinger=FALSE, mle.meth="ayulemle")
x |
A vector of counts (one per observation). |
cutoff |
Calculate estimates conditional on exceeding this value. |
m |
Number of bootstrap samples to draw. |
np |
Number of parameters in the model (1 by default). |
alpha |
Type I error for the confidence interval. |
v |
Parameter value to use for the bootstrap distribution. By default it is the MLE of the data. |
hellinger |
Minimize Hellinger distance of the parametric model from the data instead of maximizing the likelihood. |
cutabove |
Calculate estimates conditional on not exceeding this value. |
guess |
Initial estimate at the MLE. |
mle.meth |
Method to use to compute the MLE. |
dist |
matrix of sample CDFs, one per row. |
obsmle |
The Yule MLE of the PDF exponent. |
bsmles |
Vector of bootstrap MLE. |
quantiles |
Quantiles of the bootstrap MLEs. |
pvalue |
p-value of the Anderson-Darling statistics relative to the bootstrap MLEs. |
obsmands |
Observed Anderson-Darling Statistic. |
meanmles |
Mean of the bootstrap MLEs. |
See the working papers on http://www.csss.washington.edu/Papers for details
Jones, J. H. and Handcock, M. S. "An assessment of preferential attachment as a mechanism for human sexual network formation," Proceedings of the Royal Society, B, 2003, 270, 1123-1128.
ayulemle, simyule, llyule
# Now, simulate a Yule distribution over 100 # observations with rho=4.0 set.seed(1) s4 <- simyule(n=100, rho=4) table(s4) # # Calculate the MLE and an asymptotic confidence # interval for rho # s4est <- ayulemle(s4) s4est # # Use the bootstrap to compute a confidence interval rather than using the # asymptotic confidence interval for rho. # bsyule(s4, m=20)