summary.jmdem.sim: Summarising JMDEM Simulations
In jmdem: Fitting Joint Mean and Dispersion Effects Models

Description Usage Arguments Details Value Author(s) See Also Examples

These functions are all methods for class jmdem.sim or summary.jmdem.sim objects.

## S3 method for class 'jmdem.sim'
summary(object, digits = max(3L, getOption("digits") - 3L), 
        scientific = FALSE, pvalue = 0.05, 
        minv.method = c("solve", "chol2inv", "ginv"), 
        other.call = FALSE, details = FALSE, ...)
              
## S3 method for class 'summary.jmdem.sim'
print(x, digits = max(3L, getOption("digits") - 3L), scientific = FALSE, 
      pvalue = 0.05, signif.stars = getOption("show.signif.stars"), 
      other.call = FALSE, details = FALSE, ...)

`object`	an object of class "`jmdem.sim`", usually, a result of a call to `jmdem.sim`.
`x`	an object of class "`summary.jmdem.sim`", usually, a result of a call to `summary.jmdem.sim`.
`digits`	the number of significant digits to use when printing.
`scientific`	logical; if `TRUE`, scientific notation is used when printing.
`pvalue`	a value between 0 and 1. It is used to compute the coverage proportion of the true parameter values by the simulated fits.
`minv.method`	the method used to invert matrices during the estimation process. "`solve`" gives the solutions of a system of equations, "`chol2inv`" gives the inverse from Choleski or QR decomposition and "`ginv`" gives the generalised inverse of a matrix. If none of the methods is specified or if they are specified in a vector such as `c("solve", "chol2inv", "ginv")`, the matrices will be inverted by the methods in the sequence as given in the vector until it is found.
`signif.stars`	logical. If `TRUE`, 'significance stars' are printed for each coefficient.
`other.call`	logical. If `true`, the rest of simulation call (i.e. without the mean and dispersion submodel formulas, families, true values) will be shown.
`details`	logical. If `true`, coefficients, standard errors, true parameter coverage (TRUE/FALSE) and asymptotic test statistics of each simulation will be listed.
`...`	further arguments passed to or from other methods.

The arithmetric mean of the coefficients, standard errors and coverage by the confidence intervals estimated in all simulations will be listed in a table. A detail listing of each simulation's results can be provided if required by details = TRUE. The summary also includes the averages of the Rao's score and Wald test statistics of all simulation fits.

print.summary.jmdem.sim tries to be smart about formatting the coefficients, standard errors, etc according the number of significant digits (default of user-specified) or the usage of scientific notation or not.

`digits`	the number of significant digits to use when printing.
`scientific`	logical value of using scientific notation when printing.
`details`	logical value of printing details of each simulation.
`other.call`	logical value of printing other parameters of the simulation call.
`pvalue`	numeric value between 0 and 1 used for the computation of the true parameter coverage.
`beta.true`	user-defined vector containing the true parameter values of the mean submodel.
`lambda.true`	user-defined vector containing the true parameter values of the dispersion submodel.
`simcall`	the component from `object`.
`mformula`	the component from `object`.
`dformula`	the component from `object`.
`mfamily`	the component from `object`.
`dfamily`	the component from `object`.
`coefficients`	mean and dispersion submodel parameter coefficients fitted in each simulation saved in a `data.frame`.
`stderr`	standard erros of all mean and dispersion submodel parameter coefficients estimated in each simulation saved in a `data.frame`.
`iterations`	a vectror containing the running numbers of each simulation.
`confint`	confidence intervals of all mean and dispersion submodel parameter coefficients estimated in each simulation saved in a `data.frame`.
`coverage`	the coverage of all true submodel parameters by the confidence intervals estimated in each simulation saved in a `data.frame`.
`asymp.test`	Rao's score and Wald test statistics of each simulation saved in a `data.frame`.
`average.summary`	Arithmetric means of the coefficients, standard errors, confidence interval converage estimated in all simulations saved in a `data.frame`.
`average.asymp.test`	(Arithmetric means of the Rao's score and Wald test statistics estimated in all simulations saved in a `data.frame`.

Karl Wu Ka Yui (karlwuky@suss.edu.sg)

jmdem.sim, jmdem, summary

## Example in jmdem.sim(...)
sim <- jmdem.sim(mformula = y ~ x, dformula = ~ z, beta.first = TRUE, 
                 mfamily = gaussian, dfamily = Gamma(link = "log"), 
                 x.str = list(type = "numeric", random.func = "rnorm", 
                              param = list(mean = 0, sd = 2)),
                 z.str = list(type = "factor", random.func = "runif", 
                              param = list(min = 0, max = 2)),
                 beta.true = c(1.5, 4), lambda.true = c(2.5, 3, -0.2), 
                 grad.func = TRUE, method = "BFGS", n = 50,
                 simnum = 10)
                  
## Summarise simulation
summary(sim, details = FALSE, other.call = TRUE)