mph.summary

mph.out

Logical variable indicating whether cell specific
 statistics are to be output. Default:
 <code>cell.stats = FALSE</code>.

cell.stats

Logical variable indicating whether model
 information is to be output. Default:
 <code>model.info = FALSE</code>.

model.info

Integer giving output precision; used in the
 <code>round()</code> function.

digits

Computes and prints a collection of summary statistics of the
fitted MPH model.
This function is used in conjunction with the ML fitting function
<code>mph.fit</code>.

htest

Contingency table analysis is performed based on maximum likelihood (ML) fitting of
multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models.
See Lang (2004) <doi:10.1214/aos/1079120140> and Lang (2005) <doi:10.1198/016214504000001042>
for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood-
based (cell- and link-specific) residuals; and cell probability and expected count estimates along
with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood,
score, power-divergence--confidence intervals for contingency table estimands, when table
probabilities are potentially subject to equality constraints. For test-inversion intervals, see
Lang (2008) <doi:10.1002/sim.3391> and Zhu (2020) <doi:10.17077/etd.005331>.

mph.summary: Summary Statistics of the Fitted MPH Model

Description

Usage

Arguments

Value

References

See Also