sim.tdlnm: Creates simulated data for TDLNM
In dlmtree: Bayesian Treed Distributed Lag Models
sim.tdlnm R Documentation
Creates simulated data for TDLNM
Description
Method for creating simulated data for TDLNM
Usage
sim.tdlnm(sim = "A", error.to.signal = 1)
Arguments
sim
character (A - D) specifying simulation scenario
error.to.signal
scalar value setting error: sigma^2/var(f)
Details
sim.tdlnm
Simulation scenarios:
Scenario A: Piecewise constant effect
Scenario B: Linear effect
Scenario C: Logistic effect, piecewise in time
Scenario D: Logistic effect, smooth in time
Value
Simulated data and true parameters
Examples
sim.tdlnm(sim = "A", error.to.signal = 1)
dlmtree documentation built on June 22, 2024, 10:05 a.m.
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| sim.tdlnm | R Documentation |
Creates simulated data for TDLNM
Description
Method for creating simulated data for TDLNM
Usage
sim.tdlnm(sim = "A", error.to.signal = 1)
Arguments
sim |
character (A - D) specifying simulation scenario |
error.to.signal |
scalar value setting error: sigma^2/var(f) |
Details
sim.tdlnm
Simulation scenarios:
Scenario A: Piecewise constant effect
Scenario B: Linear effect
Scenario C: Logistic effect, piecewise in time
Scenario D: Logistic effect, smooth in time
Value
Simulated data and true parameters
Examples
sim.tdlnm(sim = "A", error.to.signal = 1)
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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