| add | Add constraints to a model |
| add_rand_var | Declare a random variable |
| add_var | Declare decision variables |
| as_program | Lower a model to a program |
| BINARY | A variable declaration |
| bin_var | Declare decision variables |
| consets | Constraint sets |
| constraint | A constraint row |
| CONTINUOUS | A variable declaration |
| cvar | The conditional value at risk at level 'alpha' |
| DEFAULT_BASE_URL | The public Quicopt endpoint |
| distribution | Distributions for random variables |
| empirical | A random variable given as a fixed scenario column |
| encode | Encode a program to the bytes the service reads |
| encode_params | Encode parameter tables alone, for rebinding data |
| expectation | The expected value over the scenarios |
| expressions | quicopt expressions — model arithmetic in plain R |
| index_set | A named index set with concrete elements |
| indicator | Constraint sets |
| INTEGER | A variable declaration |
| int_var | Declare decision variables |
| ir | quicopt IR — a model as plain data |
| ir_apply | quicopt IR — a model as plain data |
| ir_const | quicopt IR — a model as plain data |
| ir_param | quicopt IR — a model as plain data |
| ir_reduce | quicopt IR — a model as plain data |
| ir_set_ref | quicopt IR — a model as plain data |
| ir_source_ref | quicopt IR — a model as plain data |
| ir_var | quicopt IR — a model as plain data |
| job_delete | Poll a submitted job |
| job_log | Poll a submitted job |
| job_result | Poll a submitted job |
| job_status | Poll a submitted job |
| maximize | State what the model optimizes |
| minimize | State what the model optimizes |
| model | Create an empty optimization model |
| nonneg | Constraint sets |
| normal | Distributions for random variables |
| num_var | Declare decision variables |
| parametric | A random variable drawn from a distribution |
| prob | The probability that a comparison holds |
| program | A complete optimization model as plain data |
| rand_var | Declare a random variable |
| set_distribution | Give a random variable its distribution |
| set_empirical | Turn observed history into a model's uncertainty |
| set_scenarios | Set how many scenarios are drawn, and from which seed |
| solve.quicopt_model | Solve a model with the Quicopt service |
| solve_model | Solve a model with the Quicopt service |
| stochastic | Optimization under uncertainty |
| submit | Submit a model for asynchronous solving |
| var_decl | A variable declaration |
| wire | quicopt wire — a program's bytes |
| zero | Constraint sets |