A statistical model of random numbers
A list object named '
qsd' of class
QLmodel with additional elements
simfn simulation function
sim simulation results at design points, class '
OPT result from call to estimation function
QS quasi-scoring iteration results after initial approximation
This is a pedagogic example of a simulated data set for quasi-likelihood estimation using
normally distributed random numbers. The model outcome is a vector of summary statistics, that is,
simply the median and mean average deviation of
n=10 random numbers, which is evaluated at the
model parameter θ=(μ,σ) with mean μ and standard deviation σ as
the parameters of the normal distribution. We estimate the model parameter given a specific
"observation" of those summary statistics. Clearly, maximum likelihood estimation would be the
method of first choice if we had a real sample of observations. However, this example is used to demonstrate
the basic workflow of estimating the model parameter. We use this model as a standard example in the package
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