inflPlot | R Documentation |
A ggplot line plot showing the influences
inflPlot(
modelObj,
plotType = ifelse(length(modelObj$data) <= 2, "pointplot", "boxplot"),
pointFun = "sum",
lineSize = 0.07,
Dim = 1,
samples = seq_len(nrow(if (is.null(modelObj$covariates)) modelObj$latentVars else
modelObj$alphas)),
...
)
modelObj |
The fitted data integration |
plotType |
The type of plot requested, see details |
pointFun |
The function to calculate the summary measure to be plotted |
lineSize |
The line size |
Dim |
The dimension required |
samples |
index vector of which samples to be plotted |
... |
additional arguments passed on to the influence() function |
The options for plotType are: "pointPlot": Dot plot of total influence per view and sample, "boxplot": plot boxplot of influence of all observations per view and sample, "boxplotSingle": boxplot of log absolute total influence per view, "lineplot": line plot of total influence per view and sample. In the pointplot, dots crosses represent parameter estimates
A ggplot object
data(Zhang)
#Unconstrained
microMetaboInt = combi(
list("microbiome" = zhangMicrobio, "metabolomics" = zhangMetabo),
distributions = c("quasi", "gaussian"), compositional = c(TRUE, FALSE),
logTransformGaussian = FALSE, verbose = TRUE)
#Constrained
microMetaboIntConstr = combi(
list("microbiome" = zhangMicrobio, "metabolomics" = zhangMetabo),
distributions = c("quasi", "gaussian"), compositional = c(TRUE, FALSE),
logTransformGaussian = FALSE, covariates = zhangMetavars, verbose = TRUE)
load(system.file("extdata", "zhangFits.RData", package = "combi"))
inflPlot(microMetaboInt)
#Constrained
inflPlot(microMetaboIntConstr)
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