get.overall.covariance.matrix: Return the (average) model-estimated covariance matrix
In tfojo13/RMP: Fits Bayesian models on repeated measures of multiple symptoms
Usage
1
get.overall.covariance.matrix(rmp, times)
Arguments
rmp
An rmp object as returned by create.measurement.predictor
times
A vector of times for which to generate a covariance matrix
Value
A T*D x T*D covariance matrix, where T=length(times) and D is the number of tests (dimensions).
The return value is indexed such that element [D*(t1-1)+d1, D*(t2-1)+d2] represents the covariance between a measurment on test d1 at time times[t1] with a measurement on test d2 at time times[t2]
tfojo13/RMP documentation built on May 29, 2019, 12:42 p.m.
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Usage
1 | get.overall.covariance.matrix(rmp, times)
|
Arguments
rmp |
An rmp object as returned by create.measurement.predictor |
times |
A vector of times for which to generate a covariance matrix |
Value
A T*D x T*D covariance matrix, where T=length(times) and D is the number of tests (dimensions). The return value is indexed such that element [D*(t1-1)+d1, D*(t2-1)+d2] represents the covariance between a measurment on test d1 at time times[t1] with a measurement on test d2 at time times[t2]
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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