It is shown that likelihood-based calculations may provide insight into the quality of the resulting parameter estimates, and are directly applicable to the validation of experimental designs.

A rather complex numerical issue for (restricted) maximum likelihood estimation in nonlinear mixed-effects models is the evaluation of the log-likelihood function of the data, because it involves the ...

Right now, I see the occasional example log-likelihood function scattered throughout a ton of different math stats books, and I have to think that somewhere out there these have been collected ...

Quality of Life Research Vol. 16, Aug., 2007 Evaluating Measurement Equivalence Using the Item Response Theory Log-Likelihood Ratio (IRTLR) Method to Assess Differential Item Functioning (DIF): ...

The log likelihood function can only be evaluated for , c > 0, and . In the estimation process, you must enforce these conditions using lower and upper boundary constraints. The three-parameter ...

The LIK module computes the average log likelihood function. First, the average log likelihood function is computed using the default initial values: Z0=0 and VZ0= 106 I. The second call of module LIK ...

A likelihood function for the frequency of the A1 allele when 2 A1 alleles are observed in a sample of 10 alleles. The vertical dashed line is drawn through the maximum value of the likelihood ...