summary
is a generic function for summarizing
results produced from Zero-truncated Poisson and Negative
Binomial models with maximum likelihood estimation. Using
the estimates of fitted object obj
, the size of
unknown population N
and its 100*(1-alpha)
confidence interval are calculated.
1 2 3 |
object |
a fitted model object, |
alpha |
a confidence level required
( |
k |
an integer, the penalty per parameter to be
used; the |
j |
an integer, for Lagrange multiplier test |
... |
other arguments |
LM.test |
Lagrange multiplier test |
HT.est |
Horvitz-Thompson estimator |
An object of class summary.ztpr
with components
including
tab |
Formatted object to be printed including coefficients, standard errors, etc. Significance star is also printed with stars, |
aic |
Akaike Information Criteria, |
N |
Estimate of unknown population size, |
VarN |
Variance of |
ciu |
Upper bound of confidence interval, |
cil |
Lower bound of confidence interval. |
print.summary.ztpr
is a generic function that
displays all summaries of object generated from
summary.ztpr
.
Chel Hee Lee <gnustats@gmail.com>
AIC
, extractAIC
,
printCoefmat
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.