summary.ztpr: Object summaries for Zero-truncated Poisson and Negative...

In ipeglim: Imprecise Inferential Framework on Statistical Reasoning

Description

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.

Usage

  ## S3 method for class 'ztpreg'
 summary(object, alpha = 0.05, k = 2,
    j = 1, LM.test = FALSE, HT.est = FALSE, ...)

Arguments

object	a fitted model object,
alpha	a confidence level required (alpha=0.05 by default),
k	an integer, the penalty per parameter to be used; the k=2 is used for classical AIC (Akaike's information criteria),
j	an integer, for Lagrange multiplier test
...	other arguments
LM.test	Lagrange multiplier test
HT.est	Horvitz-Thompson estimator

Value

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 N,
ciu	Upper bound of confidence interval,
cil	Lower bound of confidence interval.

Note

print.summary.ztpr is a generic function that displays all summaries of object generated from summary.ztpr.

Author(s)

Chel Hee Lee <[e-mail]>

See Also

AIC, extractAIC, printCoefmat

ipeglim documentation built on May 2, 2019, 4:31 p.m.