Parametric bootstrap confidence interval of parameters of BBBVPA distribution.
param.boot(
data,
s1.int,
s2.int,
a0.int,
a1.int,
a2.int,
conf.lev = 0.95,
intv.m1 = c(0, 2),
intv.m2 = c(0, 2),
no.paboot = 100,
tol = 1e-04,
...
)A matrix of lower and upper confidence interval limits (in the first and second column respectively). The matrix rows are labeled by the parameter names (if any) and columns by the corresponding distribution quantiles.
bivariate observations.
initial choice of \(\sigma_1\).
initial choice of \(\sigma_2\).
initial choice of \(\alpha_0\).
initial choice of \(\alpha_1\).
initial choice of \(\alpha_2\).
confidence level, defult \(0.95\).
interval related to confidence interval of \(\mu_1\), c(0,2) (default).
interval related to confidence interval of \(\mu_1\), c(0,2) (default).
number of bootstrap samples, 100 (default).
convergence tolerance for confidence interval of \(\mu_1\).
and \(\mu_2\), 0.0001 (default).
further arguments to pass to estimates.
Biplab Paul <paul.biplab497@gmail.com> and Arabin Kumar Dey <arabin@iitg.ac.in>
# see the example of estimation
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