estimatep {CAEN}R Documentation

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

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

would be a SummarizedExperiment Bioconductor object, then it would be transformed into a n times p matrix - i.e. observations on the rows and features on the columns in the function, or x would be a n times p matrix.

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

would be a SummarizedExperiment Bioconductor object, then would be transformed into a m-by-p data matrix: m test observations and p features, or xte would be a m-by-p data matrix. 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 <- dat$sim_train_data
y <- as.numeric(colnames(dat$sim_train_data))
xte <- dat$sim_test_data
prob <- estimatep(x=x, y=y, xte=x, beta=1, type="mle", prior=NULL)

[Package CAEN version 1.1.0 Index]