summary.MLEtf function

Function to produce result summaries of the estimates of parameters from probability distributions using the mle_tf function or parameters from regression models using the mlereg_tf function.

# S3 method for MLEtf
summary(object, ...)

Arguments

object	an object of class MLEtf for which a summary is desired.
...	additional arguments affecting the summary produced.

Details

summary.MLEtf function displays estimates and standard errors of parameters from statistical distributions and regression models. Also, this function computes and displays the Z-score and p-values of significance tests for these parameters. If limits were defined for the parameters, the standard error and other statistics are not reported due to the transformation applied to the parameters.

Author

Sara Garcés Céspedes sgarcesc@unal.edu.co

Examples

#---------------------------------------------------------------
# Estimation of both normal distrubution parameters

# Generate a sample from the normal distribution
x <- rnorm(n = 1000, mean = 10, sd = 3)

# Use the summary function
summary(mle_tf(x,
               xdist = "Normal",
               optimizer = "AdamOptimizer",
               initparam = list(mean = 1.0, sd = 1.0),
               hyperparameters = list(learning_rate = 0.1)))
#> Distribution: Normal 
#> Number of observations: 1000 
#> TensorFlow optimizer: AdamOptimizer 
#> Negative log-likelihood: 680.8125 
#> Loss function convergence, 1164 iterations needed. 
#> ---------------------------------------------------
#>      Estimate  Std. Error Z value Pr(>|z|)    
#> mean  10.01339    0.09531  105.06   <2e-16 ***
#> sd     3.01389    0.06775   44.49   <2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1