print.summary.ecoML: Print the Summary of the Results for the Maximum Likelihood...

In eco: Ecological Inference in 2x2 Tables

Print the Summary of the Results for the Maximum Likelihood Parametric Model for Ecological Inference in 2x2 Tables

Description

summary method for class eco.

Usage

## S3 method for class 'summary.ecoML'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x	An object of class summary.ecoML.
digits	the number of significant digits to use when printing.
...	further arguments passed to or from other methods.

Value

summary.eco yields an object of class summary.eco containing the following elements:

call	The call from eco.
sem	Whether the SEM algorithm was executed, as specified by the user upon calling ecoML.
fix.rho	Whether the correlation parameter was fixed or allowed to vary, as specified by the user upon calling ecoML.
epsilon	The convergence threshold specified by the user upon calling ecoML.
n.obs	The number of units.
iters.em	The number iterations the EM algorithm cycled through before convergence or reaching the maximum number of iterations allowed.
iters.sem	The number iterations the SEM algorithm cycled through before convergence or reaching the maximum number of iterations allowed.
loglik	The final observed log-likelihood.
rho	A matrix of iters.em rows specifying the correlation parameters at each iteration of the EM algorithm. The number of columns depends on how many correlation parameters exist in the model. Column order is the same as the order of the parameters in param.table.
param.table	Final estimates of the parameter values for the model. Excludes parameters fixed by the user upon calling ecoML. See ecoML documentation for order of parameters.
agg.table	Aggregate estimates of the marginal means of W_1 and W_2
agg.wtable	Aggregate estimates of the marginal means of W_1 and W_2 using X and N as weights.

If units = TRUE, the following elements are also included:

W.table

Unit-level estimates for W_1 and W_2.

This object can be printed by print.summary.eco

See Also

ecoML

eco documentation built on Nov. 4, 2022, 1:07 a.m.