Man pages for JGCRI/ambrosia
An R package for calculating and analyzing food demand that is responsive to changing incomes and prices
| apply.bias.corrections | Apply bias corrections to model outputs |
| assign.sigma.Q | Assign observational errors to observed demand quantities |
| calc1eps | Calculate the exponents in the demand equation. |
| calc1q | Calculate demand quantities for a single set of inputs |
| calc.elas.actual | Calculate actual elasticities using numerical derivatives. |
| calc.hicks.actual | Calculate the actual Hicks elasticities using the Slutsky... |
| calc.pop.weight | Calculate a weight factor based on the population. |
| calculate_ambrosia_params | Calculates the 11 parameters for ambrosia using data... |
| compute_bias_corrections | Compute regional bias corrections. |
| create_dataset_for_parameter_fit | Create dataset with observational error for log likelihood... |
| data_used_for_original_param | Dataset used for original parameter estimation |
| eta.constant | Generate an income elasticity function with constant income... |
| food.dmnd | Calculate food demand using the Edmonds, et al. model. |
| food.dmnd.byincome | Tabulate food demand by per-capita-income |
| food.dmnd.byyear | Tabulate food demand by year for a model. |
| guiconst | Constants used in the GUI |
| guiwidgets | Input widgets for food demand GUI app |
| lamks2nu1y0 | Convert the lambda and ks parameters to nu1 and y0 |
| make.byincome.plot | Plot model results by per-capita income |
| make.byyear.plot | Plot model results by year |
| make.demand.plot | Plot staple, nonstaple, and total demand output from the... |
| mc_data_example | Sample dataset of mc data |
| mc.food.dmnd.byyear | Compute food demand by year |
| mc.make.byyear.plot | Make the by-year plot for a set of monte carlo results by... |
| mcparam.clip.tails | Filter a Monte Carlo distribution by quantiles |
| mcparam.density | Create a density plot for all of the MC variables |
| mcparam.itercount | Get the iteration count for a monte carlo dataset. |
| mcparam.ML | Get the maximum a-posteriori (MAP) parameters |
| mcparam.sample | Sample the MC results using bootstrap sampling. |
| mc.setup | Create a posterior log-pdf function for monte carlo sampling... |
| merge_trn_tst | Create a merged dataset with training and test data, each... |
| namemc | Return the list of names for the parameters in the model. |
| plohi | Recommended parameter limits for the model. |
| prepare.obs | Prepare observations for use in the model. |
| processed_data_example | Sample dataset of processed data |
| read.mc.data | Read the Monte Carlo results file |
| recursive.partition | Partition input data into clusters with a minimum number of... |
| runapp | Launch the interactive GCAM food demand model |
| testdata | Sample values for the demand model. |
| training_data | Sample dataset of training data for ambrosia |
| vec2param | Convert a vector of parameters into a params structure. |
