summary.UPG.MNL {UPG} | R Documentation |
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. In addition, LaTeX, HTML and pandoc tables can be quickly generated via knitr
.
## S3 method for class 'UPG.MNL' summary( object = NULL, ..., q = c(0.025, 0.975), groups = NULL, names = NULL, digits = 2, include = NULL, table = NULL, cap = NULL )
object |
an object of class |
... |
other summary parameters. |
q |
a numerical vector of length two holding 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 |
include |
can be used to summarize and tabulate only a subset of variables. Specificy 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 ( |
cap |
character vector that can be used to specify the table caption is returned. |
Returns a knitr_kable
object containing the summary table.
Gregor Zens
plot.UPG.MNL
to plot the results of a discrete choice model from an UPG.MNL
object.
predict.UPG.MNL
to predict probabilities from a discrete choice model from an UPG.MNL
object.
coef.UPG.MNL
to extract coefficients from an UPG.MNL
object.
# 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, type = "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")