Miscellaneous Models

Misc

behavior-i

Model for behavioral data with individual-level random effects only.

Dataset: behavior

behavior-iF

Model for behavioral data with individual-level random effects and fixed effects.

Dataset: behavior

behavior-ihm

Model for behavioral data with individual-level, household-level, and monthly random effects but no fixed effects.

Dataset: behavior

behavior-ihmF

Model for behavioral data with individual-level, household-level, and monthly random effects as well as fixed effects.

Dataset: behavior

detergents

Multinomial regression model for detergent purchases based on Burgette et al. (2021), although they consider multinomial probit regression.

Dataset: detergents

pres_vote_historical-2

Hierarchical Gaussian process model for election forecasting inspired by Rob Trangucci’s presentation at StanCon 2017. A country-level GP is added and the kernel is reduced from a superposition of two squared exponentials to one Matern 3/2.

Dataset: pres_vote_historical

pres_vote_historical-trangucci

Hierarchical Gaussian process model for election forecasting presented by Rob Trangucci at StanCon 2017. The model is largely copied as-is from p. 21–23 with minor modifications to variable names, changes to comply with recent Stan syntax, and performance improvements. Generated quantities for actual forecasting are omitted here–future work.

Dataset: pres_vote_historical