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The R package "bayesdtm" implements Bayesian decision-theoretic models to compute expected losses under an intervention (in causal inference senses) and those under no intervention (i.e., the status quo), across different ratios of the cost of the intervention to the cost of an undesirable outcome. For details on how to install and use the package, please see the vignette.
This function produces the plot of a complementary cumulative distribution function for the posterior samples of a causal effect. For details on how to install and use the package, please see the vignette.
This package includes a function to aggregate grid data to a different cell size. It works both for cross-sectional data and for cross-sectional time-series data. For details on how to install and use the package, please see the vignette.