randomparameters
Random parameters are model parameters treated as random variables rather than fixed constants. In statistical modeling, this approach allows the effect of a predictor to vary across entities such as individuals, groups, or time. This stands in contrast to fixed-parameter models, where all parameters are assumed identical across observations.
In practice, random parameters appear in several forms. In linear mixed models and generalized linear mixed
Interpretation centers on variance components. The estimated variance of a random parameter measures how much the
Applications are widespread in economics, marketing, psychology, and biostatistics. Examples include modeling varying price sensitivities in
Challenges include identifiability, the need for sufficient data to estimate variance components, and computational demands due