Description Usage Arguments Value Examples
Plot data, design matrix or co-clustering probabilities
1 | plot_rewind(x, simu, type = "data", title_val = type)
|
x |
data, design matrix or coclustering probabilities |
simu |
simulated objects; see |
type |
default to "data"; could be "design" or "cocluster" |
title_val |
the title of the plot; default is just |
a plot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # simulate data:
L0 <- 100 # dimension of measurements.
M0 <- 3 # true dimension of latent states.
K0 <- 8 # true number of clusters.
options_sim0 <- list(N = 100, # sample size.
M = M0, # true number of machines.
L = L0, # number of antibody landmarks.
K = K0, # number of true components.
theta = rep(0.8,L0), # true positive rates.
psi = rep(0.15,L0), # false positive rates.
#alpha1 = 1, # half of the people have the first machine.
frac = 0.2, # fraction of positive dimensions (L-2M) in Q.
#pop_frac = rep(1/K0,K0) # population prevalences.
#pop_frac = (1:K0)/sum(1:K0) # population prevalences.
pop_frac = c(rep(2,4),rep(1,4)) # population prevalences.
#pop_frac = c(rep(0.75/4,4),rep(0.25/4,4))
)
simu <- simulate_data(options_sim0, SETSEED=TRUE)
plot_rewind(simu$datmat,simu,"data","Simulated Data")
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