% Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/CytoDx.pred.R
 \name{CytoDx.pred}
 \alias{CytoDx.pred}
 \title{Make prediction using the CytoDx model}
 \usage{
 CytoDx.pred(fit, xNew, xSampleNew)
 }
 \arguments{
 \item{fit}{The two stage statistical model. Must be the object returned by CytoDx.fit.}
 
 \item{xNew}{The marker profile of cells pooled from all new samples. Each row is a cell, each column is
 a marker.}
 
 \item{xSampleNew}{A vector specifying which sample each cell belongs to. Length
 must equal to nrow(xNew).}
 }
 \value{
 Returns a list. xNew.Pred1 contains the predicted y for the new data at the cell level.
   xNew.Pred2 contains the predicted y for the new data at the sample level.
 }
 \description{
 A function that makes prediction using the CytoDx model.
 }
 \examples{
 # Find the table containing fcs file names in CytoDx package

 path <- system.file("extdata",package="CytoDx")

 # read the table

 fcs_info <- read.csv(file.path(path,"fcs_info.csv"))

 # Specify the path to the cytometry files

 fn <- file.path(path,fcs_info$fcsName)
 train_data <- fcs2DF(fcsFiles=fn,

                     y=fcs_info$Label,
                     assay="FCM",
                     b=1/150,
                     excludeTransformParameters=
                       c("FSC-A","FSC-W","FSC-H","Time"))
 # build the model

 fit <- CytoDx.fit(x=as.matrix(train_data[,1:7]),

                 y=train_data$y,
                 xSample = train_data$xSample,
                 reg=FALSE,
                 family="binomial")
 # check accuracy for training data

 pred <- CytoDx.pred(fit,

                    xNew=as.matrix(train_data[,1:7]),
                    xSampleNew=train_data$xSample)
 
 boxplot(pred$xNew.Pred.sample$y.Pred.s0~
           fcs_info$Label)
 
 }