estimatep: Estimate the probability that the read is 0 in a...

In zhangli1109/ENTC: Category encoding method for selecting feature genes for the classification of single-cell RNA-seq

Description

Estimate the probability that the read is 0 in a Zero-inflated Poisson model.

Usage

estimatep(x,y,xte=NULL,beta=1,
type=c("mle","deseq","quantile"), prior=NULL)

Arguments

x	MUST be a n times p matrix - i.e. observations on the rows and features on the columns
y	A numeric vector of class labels of length n: 1, 2, ...., K if there are K classes.Each element of y corresponds to a row of x; i.e. these are the class labels for the observations in x.
xte	A m-by-p data matrix: m test observations and p features. The classifier fit on the training data set x will be tested on this data set. If NULL, then testing will be performed on the training set.
beta	A standardized parameter
type	the method of normality
prior	vector of length equal to the number of classes, representing prior probabilities for each class.If NULL then uniform priors are used (i.e. each class is equally likely)

Value

p the probability that the read is 0 in a Zero-inflated Poisson model

Examples

library(SummarizedExperiment)
dat <- newCountDataSet(n=40,p=500, K=4, param=10, sdsignal=0.1,drate=0.4)
x <- t(assay(dat$sim_train_data))
y <- as.numeric(colnames(dat$sim_train_data))
xte <- t(assay(dat$sim_test_data))
prob <- estimatep(x=x, y=y, xte=x, beta=1, type="mle", prior=NULL)

zhangli1109/ENTC documentation built on Nov. 10, 2020, 11:16 p.m.