A B C D E G I M N O P Q S T U misc
adoptr-package | Adaptive Optimal Two-Stage Designs |
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 |
bounds | Get support of a prior or data distribution |
bounds-method | Get support of a prior or data distribution |
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 |
DataDistribution | Data distributions |
DataDistribution-class | Data distributions |
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 |
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 |
IntegralScore | Unconditional score class obtained by integration of a 'ConditionalScore' |
IntegralScore-class | Unconditional score class obtained by integration of a 'ConditionalScore' |
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 | 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 |
OneStageDesign | One-stage designs |
OneStageDesign-class | One-stage designs |
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 |
quantile-method | Normal data distribution |
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 |
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 |
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 |
*-method | Score arithmetic |
+-method | Score arithmetic |
<=-method | Formulating constraints |
>=-method | Formulating constraints |