nncg: Non-negative conjugate gradient algorithm
In SSPA: General Sample Size and Power Analysis for Microarray and Next-Generation Sequencing Data

Non-negative conjugate gradient algorithm

1	nncg(A, b, type = 1, trace = FALSE)

`A`	the A matrix of the system: Ax = b.
`b`	the b vector of the system: Ax = b.
`type`	for the conjugate-gradients method. Takes value '1' for the Fletcher-Reeves update, '2' for Polak-Ribiere and '3' for Beale-Sorenson.
`trace`	tracing information on the progress of the optimization is produced.

C-implementation, details follow.

list containg regression coefficients and some additional information.

Maarten van Iterson

SSPA documentation built on Nov. 8, 2020, 5:50 p.m.

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Power and sample size analysis, Microarray data, RNAseq data

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