make.measurement.predictions: Make predictions of Repeated Measurements
In tfojo13/RMP: Fits Bayesian models on repeated measures of multiple symptoms
Usage
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2
make.measurement.predictions(dm, observations, observed.times, predict.times,
covariates = NULL, ci.coverage = 0.95, iq.coverage = 0.5, sum = F)
Arguments
observations
an array indexed [i,time,test] - where i denotes an individual
observed.times
a numeric vector such that observed.times[t] is the time at which observations[,t,] were taken
covariates
A row for each individual with the covariates used to fit the model
Value
A 4d array indexed[individual, time, test, statistic], where statistic is one of: mean, ci.lower, ci.upper, iq.lower, iq.upper
tfojo13/RMP documentation built on May 29, 2019, 12:42 p.m.
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Usage
1 2 | make.measurement.predictions(dm, observations, observed.times, predict.times,
covariates = NULL, ci.coverage = 0.95, iq.coverage = 0.5, sum = F)
|
Arguments
observations |
an array indexed [i,time,test] - where i denotes an individual |
observed.times |
a numeric vector such that observed.times[t] is the time at which observations[,t,] were taken |
covariates |
A row for each individual with the covariates used to fit the model |
Value
A 4d array indexed[individual, time, test, statistic], where statistic is one of: mean, ci.lower, ci.upper, iq.lower, iq.upper
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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