ezsim (version 0.5.5)

summary.ezsim: Summarize an ezsim Object

Description

A quick summary to the simulation. Summary statistics included mean, true value (tv), bias, bias percentage (mean/tv-1), sd, rmse (root mean square error), min, q25 (first quarter), median, q75 (third quarter), max, p value of jb-test. See ezsim and plot.summary.ezsim for details and examples.

Usage

"summary"(object,stat=c('mean','tv','bias',
'biaspercentage','sd','rmse','min','q25','median',
'q75','max','jb_test'),simple=TRUE,subset,...)

Arguments

object

An ezsim object

stat

Some preset summary statistics. Included, c('mean','tv','bias','biaspercentage','sd','rmse','min','q25','median','q75','max','jb_test')

simple

If True, shows only mean, true value, bias, sd and rmse of the estimator. If False, shows all statistics in stat.

subset

subset of estimators or parameters. See subset.ezsim for details.

...

Furhter summary statistics. Given in the form stat_name=stat. For example, Mean=mean

Value

A summary.ezsim object

See Also

ezsim, plot.summary.ezsim, getSelectionName.summary.ezsim

Examples

## Not run: 
# ezsim_basic<-ezsim(
#     m             = 100,
#     run           = TRUE,
#     display_name  = c(mean_hat="hat(mu)",sd_mean_hat="hat(sigma[hat(mu)])"),
#     parameter_def = createParDef(list(n=seq(20,80,20),mu=c(0,2),sigma=c(1,3,5))),
#     dgp           = function() rnorm(n,mu,sigma),
#     estimator     = function(x) c(mean_hat = mean(x),
#                                  sd_mean_hat=sd(x)/sqrt(length(x)-1)),
#     true_value    = function() c(mu, sigma / sqrt(n-1))
# )
# 
# 
# 
# ## Summary of an ezsim object
# summary(ezsim_basic)
# 
# ## Summary of a subset of ezsim object
# summary(ezsim_basic,subset=list(estimator='mean_hat',n=c(20,40),sigma=c(1,3)))
# 
# ## More Summary Statistics
# summary(ezsim_basic,simple=FALSE,subset=list(estimator='mean_hat',n=c(20,40),sigma=c(1,3)))
# 
# ## Customize the Summary Statistics
# summary(ezsim_basic,stat=c("q25","median","q75"),Q025=quantile(value_of_estimator,0.025),
#   Q975=quantile(value_of_estimator,0.975),subset=list(estimator='mean_hat',n=c(20,40),sigma=c(1,3)))
# ## End(Not run)