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 1.0.0 Index]