Plot a PoisMixClus object.
1 2 3 4 5 6  ## S3 method for class 'PoisMixClus'
plot(x, y_profiles = NULL, K = NULL,
threshold = 0.8, conds = NULL, average_over_conds = FALSE,
graphs = c("logLike", "ICL", "profiles", "boxplots", "probapost_boxplots",
"probapost_barplots", "probapost_histogram", "lambda_barplots"),
order = FALSE, profiles_order = NULL, ...)

x 
An object of class 
y_profiles 
y (n x q) matrix of observed profiles for n
observations and q variables to be used for graphing results (optional for

K 
If desired, the specific model to use for plotting. If 
threshold 
Threshold used for maximum conditional probability; only observations with maximum conditional probability greater than this threshold are visualized 
conds 
Condition labels 
average_over_conds 
If 
graphs 
Graphs to be produced, one (or more) of the following:

order 
If 
profiles_order 
If 
... 
Additional optional plotting arguments 
Andrea Rau
1 2 3 4 5 6 7 8 9 10  ## Simulate toy data, n = 300 observations
set.seed(12345)
countmat < matrix(round(runif(300*4, min=0, max=500)), nrow=300, ncol=4)
countmat < countmat[which(rowSums(countmat) > 0),]
conds < rep(c("A","B","C","D"), each=2)
## Run the Poisson mixture model for K = 2,3
run < coseq(y=countmat, K=2:3, iter=5, model="Poisson")
plot(run)
summary(run)

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