summary_sema: Interpreting sema output
In L-Ippel/SEMA: Streaming Expectation Maximization Approximation

Description Usage Arguments Details Value See Also Examples

Returns a list with the current model parameter estimates

1	summary_sema(x)

`x`	A sema model output.

The output of the sema_fit functions are usually large, and difficult to read, lists. In order to interpret the output of the sema_fit functions, summary_sema returns a general overview of the model parameters, the fixed effects coefficients, the random effects variances and covariances, and the residual variance. The summary_sema function is also incorpprated within the sema_fit_one function, such that with the argument print_every the user can see a summary of the updated model parameters every X data points.

A list with sample size, number of units, the coefficients of the fixed effects, the variance of the random effects and the residual variance.

store_fixed_coef, store_random_var, store_resid_var, ranef

## First we create a dataset, consisting of 2500 observations from 20 
## units. The fixed effects have the coefficients 1, 2, 3, 4, and 5. The 
## variance of the random effects equals 1, 4, and 9. Lastly the 
## residual variance equals 4:
  
test_data <- build_dataset(n = 2500, 
                           j = 20, 
                           fixed_coef = 1:5, 
                           random_coef_sd = 1:3, 
                           resid_sd = 2)
                           
## Next, we fit a simple model to these data                           
m1 <- sema_fit_df(formula = y ~ 1 + V3 + V4 + V5 + V6 + (1 + V4 + V5 | id), 
                    data_frame = test_data, 
                    intercept = TRUE)
summary_sema(m1)