There are three SAS procedures that enable you to do maximum likelihood estimation of parameters in an arbitrary model with a likelihood function that you define: PROC MODEL, PROC NLP, and PROC IML.

and is the normal probability function. This is the likelihood function for a binary probit model. This likelihood is strictly positive so that you can take a square root of and use this as your ...

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 ...

The current implementation of the phylim app only accepts a model_result object. This does not work if the model result has come from a split_codon=True model. In the latter case, there is no single ...

The maximum likelihoood estimator approach is used here for calculating the Regression parameter that is slope(b1),intercept(b0) and standard deviation of error/residuals. Then Result or the output ...

For some of my current projects, I'm probably going to need to eventually estimate some models using Metropolis-Hastings sampling. I understand the basic concepts, and the software I use (R) has ...