deviances: Deviance
In PUlasso: High-Dimensional Variable Selection with Presence-Only Data

Calculate deviances at provided coefficients

1	deviances(X, z, py1, coefMat, weights = NULL)

`X`	Input matrix
`z`	Response vector
`py1`	True prevalence Pr(Y=1)
`coefMat`	A coefficient matrix whose column corresponds to a set of coefficients
`weights`	observation weights. Default is 1 for each observation.

deviances

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data("simulPU")
coef0<-replicate(2,runif(ncol(simulPU$X)+1))
deviances(simulPU$X,simulPU$z,py1=simulPU$truePY1,coefMat = coef0)

PUlasso documentation built on May 2, 2019, 11:40 a.m.

PUlasso index

feature: Local Inferential Feature Significance for Multivariate Kernel Density Estimation

NCutYX: Clustering of Omics Data of Multiple Types with a Multilayer Network Representation

MIPHENO: Mutant Identification through Probabilistic High throughput Enabled NOrmalization

ridigbio: Interface to the iDigBio Data API

logconcens: Maximum Likelihood Estimation of a log-Concave Density Based on Censored Data

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