Description Usage Arguments Details Value Author(s) References See Also Examples
Generate sample data from the target model based on predictor trajectories.
1 2 | generate.data.targetmodel(env = rep(1, 10), noise.sd = 0.01, L = 15,
d = 7, seed = NA)
|
env |
integer vector of length n encoding to which experiment each repetition belongs. |
noise.sd |
numerical value specifying the standard deviation of the noise. |
L |
number of time points for evaluation. |
d |
number of total variables (d-1 preditor variables). |
seed |
random seed. Does not work if a "Detected blow-up" warning shows up. |
For further details see the references.
list consisting of the following elements
simulated.data |
D-matrix of noisy data. |
time |
vector containing time points |
env |
vector specifying the experimental environment. |
true.model |
vector specifying the target equation model. |
target |
target variable. |
Niklas Pfister, Stefan Bauer and Jonas Peters
Pfister, N., S. Bauer, J. Peters (2018). Identifying Causal Structure in Large-Scale Kinetic Systems ArXiv e-prints (arXiv:1810.11776).
The functions generate.data.maillard
and
generate.data.hidden
allow to simulate ODE data
from two additional models.
1 2 3 4 5 6 7 8 9 10 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.