Man pages for mst1g15/biasedcoin

atkinsAssuming a linear model for the response, allocate treatment...
calc.AGiven a design matrix, calculate the A optimality for a...
calc.biasGiven a design, the current estimate of beta (or true value...
calc.DGiven a design matrix, calculate the D optimality for a...
calc.DAGiven a design matrix, calculate the D-A optimality for a...
calc.GGiven a design matrix, calculate the G optimality for a...
calc.logit.wDACalculate DA-optimal criterion assuming a logistic model...
calc.logit.wLCalculate L-optimal criterion assuming a logistic model (with...
calc.lossGiven a design matrix, calculate the loss for a linear model
calc.mseGiven a design, the current estimate of beta (or true value...
calc.tzGiven a design matrix, calculate the covariate balance for a...
calc.vcovGiven a design, the current estimate of beta (or true value...
calc.wDACalculate DA-optimal criterion assuming a linear model (with...
calc.wLCalculate L-optimal criterion assuming a linear model (with...
calc.y.DCompute the D-optimality criterion of the information matrix...
calc.y.DACompute the DA-optimality criterion of the information matrix...
calc.y.GCompute the G-optimality criterion of the information matrix...
coord.crAllocate treatment using a coordinate exchange algorithm with...
coordexAllocate treatment using coordinate exchange algorithm,...
cr.bayes.desAssuming a Bayesian linear model for the response with a...
cr.desAssuming a linear model for the response, allocate treatment...
cr.des.pseudoAllocate treatments according to a (weighted) L-optimal...
cr.exp.lossBreak down expected future optimality into two components: 1)...
cr.futureCalculate (weighted) L-optimal expected optimality for a...
cr.future.lossAssuming the currrent response, future covariate value and...
cr.future.yAssuming a current response, break down the expected future...
cr.logit.contAssuming a logistic model for the response, allocate...
cr.logit.desAssuming a logistic model for the response, allocate...
cr.randAssuming a logistic model for the response, allocate...
cr.simfuture.logisAllocate treatments according to an information matrix based...
cr.simfuture.logis.contAllocate treatments according to weighted L-optimal objective...
discretediscretize a vector of continuous values into binary (0 and...
Dopt.y.tCompute the D-optimality criterion of the information matrix...
Dopt.y.t.initCompute the D-optimality criterion of of an initial design...
efronAllocate treatment basead on Efron's biased coin
exp.lossBreak down expected future optimality into two components: 1)...
exp.loss.kBreak down the expected future optimality by cases for every...
futureCalculate expected optimality for a given trajectory using...
future.coordexCalculates expected optimality for a given trajectory after...
future.coordex.logisCalculate expected optimality for a given trajectory using...
future.logisCalculate expected optimality for a given trajectory using...
future.logis.contCalculate expected optimality for a given trajectory using...
future.lossAssuming the currrent response, future covariate value and...
future.loss.kAssuming the currrent response, future covariate value and...
future.yAssuming a current response, break down the expected future...
gencovCreate a set of binary covariates with a specific covariate...
Imat.betaCompute the information matrix, given beta, for logistic...
learn.zprobsFind the empirical distribution of the covariates
linear.nonmyopAllocate treatments according to an information matrix based...
linear.nonmyop.dynAllocate treatments according to an information matrix based...
linear.randAssuming a linear model for the response, allocate treatment...
logit.contAssuming a logistic model for the response, allocate a...
logit.coordAssuming a logistic model for the response, allocate...
logit.desAssuming a logistic model for the response, allocate...
logit.LbnonAllocate treatments according to a weighted L-optimal...
logit.mseAllocate treatments according to the MSE matrix when a...
logit.nonmyAllocate treatments according to an information matrix based...
logit.randAssuming a logistic model for the response, allocate...
max.imbAllocate treatment based on Hu and Hu (2012)'s version of...
min.classicClassic version of Minimization, appropriate for binary...
min.contAllocate treatment using a version of minimization,...
min.genAllocate treatment based on an imbalance criterion - most...
min.senAllocate treatment using Senn's version of Minimization,...
probiCompute P(y=1) for logistic regression
randRandomly allocate treatment
shadeplotPlot distribution
simfutureAllocate treatments according to an information matrix based...
simfuture.logisAllocate treatments according to an information matrix based...
simfuture.logis.contAllocate continuous treatments according to an information...
wLopt.pseudo.tCalculate average L-optimal criterion assuming a logistic...
wLopt.tCalculate L-optimal criterion assuming a logistic model (with...
wLopt.t.initCalculate L-optimal criterion assuming a logistic model (with...
mst1g15/biasedcoin documentation built on March 23, 2019, 12:10 a.m.