Man pages for phuchonguyen/mpower
Power Analysis via Monte Carlo Simulation for Correlated Data

bkmr_wrapperFits a BKMR model with significance criteria: PIP and...
bma_wrapperFits a linear model with Bayesian model selection with...
bws_wrapperFits a Bayesian weighted sums
cor2partialConvert a correlation matrix into a partial correlation...
cvineCitation: Daniel Lewandowski, Dorota Kurowicka, Harry Joe,...
estimate_snrMonte Carlo approximation of the SNR
fin_wrapperFits a Bayesian factor model with interactions
fitFits the model to given data and gets a list of significance...
genxGenerates a matrix of n observations of p predictors
genyGenerates a vector of outcomes
glm_wrapperFits a generalized linear model
InferenceModelStatistical model that returns significance criterion
MixtureModelCorrelated predictors generator
mplotVisualize marginals and Gaussian copula correlations of...
mpowermpower: Power analysis using Monte Carlo for correlated...
nhanes1518NHANES data from 2015-2016 and 2017-2018 cycles
OutcomeModelOutcome generator
partialPartial correlations between elements in x and elements in y
plot_summaryPlot summaries of power simulation
qgcomp_lin_wrapperFits a linear Quantile G-Computation model with no...
qmultinomQuantile function for the multinomial distribution, size = 1
rsq2snrConvert R-squared value to the SNR
scale_fRescale the mean function of an OutcomeModel to meet a given...
scale_sigmaRescale the noise variance of a Gaussian OutcomeModel to meet...
set_valueThis function updates values in an OutcomeModel object
sim_curvePower curve using Monte Carlo simulation
sim_powerPower analysis using Monte Carlo simulation
summaryTabular summaries of power simulation
phuchonguyen/mpower documentation built on Oct. 2, 2022, 7:57 p.m.