summary.UPG.MNL: Estimation results and tables for UPG.MNL objects

Description

summary generates a summary of estimation results for UPG.MNL objects. Point estimates, estimated standard deviation as well as credible intervals for each variable are tabulated. In addition, an indicator quickly shows whether the credible interval includes zero or not. Moreover, LaTeX, HTML and pandoc tables can be quickly generated via knitr.

Usage

# S3 method for UPG.MNL
summary(
  object = NULL,
  ...,
  q = c(0.025, 0.975),
  groups = NULL,
  names = NULL,
  digits = 2,
  include = NULL,
  table = NULL,
  cap = NULL
)

Value

Returns a knitr_kable object containing the summary table.

Arguments

object: an object of class UPG.MNL.
...: other summary parameters.
q: a numerical vector of length two providing the posterior quantiles to be extracted. Default are 0.025 and 0.975 quantiles.
groups: a character vector indicating names for the groups, excluding the baseline. The group names must correspond to the ordering in the dependent variable used for estimation.
names: a character vector indicating names for the variables used in the output.
digits: number of digits to be included in output. Last digit will be rounded using round.
include: can be used to summarize and tabulate only a subset of variables. Specify the columns of X that should be kept in the plot. See examples for further information.
table: can be used to return a LaTeX table ('latex'), a Word table ('pandoc') and HTML tables ('html') via knitr. Include package "booktabs" in LaTeX preamble for LaTeX tables.
cap: character vector that can be used to specify the table caption.

Author

Gregor Zens

Examples

Run this code

# \donttest{
# estimate a multinomial logit model using example data
library(UPG)
data(program)
y = program[,1]
X = program[,-1]
results.mnl = UPG(y = y, X = X, model = "mnl")

# basic summary of regression results
summary(results.mnl)

# generate a LaTeX table with subset of variables and custom names
summary(results.mnl,
        include=c(1,3),
        groups=c("Alpha","Beta"),
        names=c("V. kept 1", "V. kept 3"),
        table="latex")
# }