Function reference • adoptr

All functions

AverageN2() evaluate(<AverageN2>,<TwoStageDesign>): Regularization via L1 norm

Binomial() quantile(<Binomial>) simulate(<Binomial>,<numeric>): Binomial data distribution

ConditionalPower() Power() evaluate(<ConditionalPower>,<TwoStageDesign>): (Conditional) Power of a Design

ConditionalSampleSize() ExpectedSampleSize() evaluate(<ConditionalSampleSize>,<TwoStageDesign>): (Conditional) Sample Size of a Design

evaluate(<Constraint>,<TwoStageDesign>) `<=`(<ConditionalScore>,<numeric>) `>=`(<ConditionalScore>,<numeric>) `<=`(<numeric>,<ConditionalScore>) `>=`(<numeric>,<ConditionalScore>) `<=`(<ConditionalScore>,<ConditionalScore>) `>=`(<ConditionalScore>,<ConditionalScore>) `<=`(<UnconditionalScore>,<numeric>) `>=`(<UnconditionalScore>,<numeric>) `<=`(<numeric>,<UnconditionalScore>) `>=`(<numeric>,<UnconditionalScore>) `<=`(<UnconditionalScore>,<UnconditionalScore>) `>=`(<UnconditionalScore>,<UnconditionalScore>): Formulating Constraints

ContinuousPrior(): Continuous univariate prior distributions

DataDistribution-class DataDistribution: Data distributions

GroupSequentialDesign() TwoStageDesign(<GroupSequentialDesign>): Group-sequential two-stage designs

MaximumSampleSize() evaluate(<MaximumSampleSize>,<TwoStageDesign>): Maximum Sample Size of a Design

N1() evaluate(<N1>,<TwoStageDesign>): Regularize n1

Normal() quantile(<Normal>) simulate(<Normal>,<numeric>): Normal data distribution

OneStageDesign() TwoStageDesign(<OneStageDesign>) plot(<OneStageDesign>): One-stage designs

PointMassPrior(): Univariate discrete point mass priors

Prior-class Prior: Univariate prior on model parameter

expected() evaluate(): Scores

Student() quantile(<Student>) simulate(<Student>,<numeric>): Student's t data distribution

TwoStageDesign() summary(<TwoStageDesign>): Two-stage designs

adoptr-package adoptr: Adaptive Optimal Two-Stage Designs

get_lower_boundary_design() get_upper_boundary_design(): Boundary designs

bounds(): Get support of a prior or data distribution

composite() evaluate(<CompositeScore>,<TwoStageDesign>): Score Composition

condition(): Condition a prior on an interval

c2(): Query critical values of a design

cumulative_distribution_function(): Cumulative distribution function

expectation(): Expected value of a function

get_initial_design(): Initial design

make_tunable() make_fixed(): Fix parameters during optimization

minimize(): Find optimal two-stage design by constraint minimization

n1() n2() n(): Query sample size of a design

plot(<TwoStageDesign>): Plot TwoStageDesign with optional set of conditional scores

posterior(): Compute posterior distribution

predictive_cdf(): Predictive CDF

predictive_pdf(): Predictive PDF

print(): Printing an optimization result

probability_density_function(): Probability density function

simulate(<TwoStageDesign>,<numeric>): Draw samples from a two-stage design

subject_to() evaluate(<ConstraintsCollection>,<TwoStageDesign>): Create a collection of constraints

tunable_parameters() update(<TwoStageDesign>) update(<OneStageDesign>): Switch between numeric and S4 class representation of a design