Adaptive Optimal Two-Stage Designs in R


[Up] [Top]

Documentation for package ‘adoptr’ version 0.1.1

Help Pages

A B C D E G I M N O P Q S T U misc

adoptr-package Adaptive Optimal Two-Stage Designs

-- A --

adoptr Adaptive Optimal Two-Stage Designs
AffineConditionalScore Affine functions of scores
AffineConditionalScore-class Affine functions of scores
AffineScore Affine functions of scores
AffineScore-class Affine functions of scores
AffineUnconditionalScore Affine functions of scores
AffineUnconditionalScore-class Affine functions of scores
AverageN2 Regularization via L1 norm
AverageN2-class Regularization via L1 norm

-- B --

bounds Get support of a prior or data distribution
bounds-method Get support of a prior or data distribution

-- C --

c2 Query critical values of a design
c2-method Query critical values of a design
condition Condition a prior on an interval
condition-method Condition a prior on an interval
ConditionalConstraint-class Formulating constraints
ConditionalPower Conditional power of a design given stage-one outcome
ConditionalPower-class Conditional power of a design given stage-one outcome
ConditionalSampleSize Conditional sample size of a design given stage-one outcome
ConditionalSampleSize-class Conditional sample size of a design given stage-one outcome
ConditionalScore Class for conditional scoring function
ConditionalScore-class Class for conditional scoring function
Constraint Formulating constraints
Constraint-class Formulating constraints
ConstraintsCollection Collection of constraints
ConstraintsCollection-class Collection of constraints
ContinuousPrior Continuous univariate prior distributions
ContinuousPrior-class Continuous univariate prior distributions
cumulative_distribution_function Cumulative distribution function
cumulative_distribution_function-method Cumulative distribution function

-- D --

DataDistribution Data distributions
DataDistribution-class Data distributions

-- E --

evaluate Evaluation of a score
evaluate-method Evaluation of a score
expectation Expected value of a function
expectation-method Expected value of a function
expected Compute the expectation of a conditional score
expected-method Compute the expectation of a conditional score

-- G --

get_lower_boundary_design Boundary designs
get_lower_boundary_design-method Boundary designs
get_upper_boundary_design Boundary designs
get_upper_boundary_design-method Boundary designs
GroupSequentialDesign Group-sequential two-stage designs
GroupSequentialDesign-class Group-sequential two-stage designs

-- I --

IntegralScore Unconditional score class obtained by integration of a 'ConditionalScore'
IntegralScore-class Unconditional score class obtained by integration of a 'ConditionalScore'

-- M --

make_fixed Fix parameters during optimization
make_fixed-method Fix parameters during optimization
make_tunable Fix parameters during optimization
make_tunable-method Fix parameters during optimization
minimize Find optimal two-stage design by constraint minimization

-- N --

n Query sample size of a design
n-method Query sample size of a design
N1 Regularize n1
n1 Query sample size of a design
N1-class Regularize n1
n1-method Query sample size of a design
n2 Query sample size of a design
n2-method Query sample size of a design
Normal Normal data distribution
Normal-class Normal data distribution

-- O --

OneStageDesign One-stage designs
OneStageDesign-class One-stage designs

-- P --

plot-method One-stage designs
plot-method Plot 'TwoStageDesign' with optional set of conditional scores
PointMassPrior Univariate discrete point mass priors
PointMassPrior-class Univariate discrete point mass priors
posterior Compute posterior distribution
posterior-method Compute posterior distribution
predictive_cdf Predictive CDF
predictive_cdf-method Predictive CDF
predictive_pdf Predictive PDF
predictive_pdf-method Predictive PDF
print.TwoStageDesignSummary Two-stage designs
Prior Univariate prior on model parameter
Prior-class Univariate prior on model parameter
probability_density_function Probability density function
probability_density_function-method Probability density function

-- Q --

quantile-method Normal data distribution

-- S --

score-arithmetic Score arithmetic
show-method Affine functions of scores
show-method Class for conditional scoring function
show-method Formulating constraints
show-method Continuous univariate prior distributions
show-method Unconditional score class obtained by integration of a 'ConditionalScore'
show-method Normal data distribution
show-method Univariate discrete point mass priors
show-method Two-stage designs
simulate-method Normal data distribution
simulate-method Draw samples from a two-stage design
subject_to Create a collection of constraints
summary-method Two-stage designs

-- T --

tunable_parameters Switch between numeric and S4 class representation of a design
tunable_parameters-method Switch between numeric and S4 class representation of a design
TwoStageDesign Two-stage designs
TwoStageDesign-class Two-stage designs
TwoStageDesign-method Group-sequential two-stage designs
TwoStageDesign-method One-stage designs
TwoStageDesign-method Two-stage designs

-- U --

UnconditionalConstraint-class Formulating constraints
UnconditionalScore Class for unconditional scoring function
UnconditionalScore-class Class for unconditional scoring function
update-method Switch between numeric and S4 class representation of a design

-- misc --

*-method Score arithmetic
+-method Score arithmetic
<=-method Formulating constraints
>=-method Formulating constraints