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synthetic nonlinear data base on the graph. The data generation mechanism is y=scale(a1b1x^2+a2b2x^3+a3b3x^4+a4b4sin(x)+a5b5sin(x^2)).
synthetic_data_nonlinear(G, sample_num, ratio = 1, return_noise = FALSE)
An adjacency matrix.
The number of samples
The noise ratio. It will grow or shrink the value of the noise.
Whether return the noise of each nodes for further analysis.
Return a synthetic data
# NOT RUN {
G<-matrix(c(0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0),nrow = 4,ncol = 4)
data=synthetic_data_nonlinear(G,100)
# }
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