regionSegCost {biomvRCNS} | R Documentation

## Regional segmentation cost matrix

### Description

To calculate regional cost matrix for the initial stage and second merging stage of the segmentation model.

### Usage

    regionSegCost(x, maxk = NULL, segs = NULL, family = NULL, alpha = NULL, useSum = TRUE, useMC = FALSE, comVar = TRUE)

### Arguments

`x` | The input data matrix or vector
`maxk` | Maximum number of index to search forward
`segs` | Starting indices (excluding 1) for the candidate segments, for the second stage model, `maxk` will be overridden with `length(segs)+1`.
`family` | which exponential family the data belongs to, possible values are 'norm', 'pois' and 'nbinom'
`alpha` | alpha matrix for negative binomial cost calculation, estimated from `regionSegAlphaNB`
`useSum` | TRUE if using grand sum across sample / x columns, like in the `tilingArray` solution
`useMC` | TRUE if `mclapply` should be used to speed up
`comVar` | TRUE if assuming common variance across samples (x columns)

### Details

Preparing the cost matrix for the follow-up segmentation. Using residual sum of squares for 'norm' data, and negative log-likelihood for 'pois' and 'nbinom' data. Extension of the `costMatrix` function in `tilingArray`.

### Value

Matrix with `maxk` rows and `nrow(x)` columns, or a `length(segs)+1` square matrix for the second stage model.

### References

Piegorsch, W. W. (1990). Maximum likelihood estimation for the negative binomial dispersion parameter. Biometrics, 863-867.

Picard,F. et al. (2005) A statistical approach for array CGH data analysis. BMC Bioinformatics, 6, 27.

Huber,W. et al. (2006) Transcript mapping with high density oligonucleotide tiling arrays. Bioinformatics, 22, 1963-1970. .

Robinson MD and Smyth GK (2008). Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics, 9, 321-332

### See Also

`regionSegAlphaNB`

### Examples

    	x<-matrix(rnorm(120), ncol=3)
    	Ca<-regionSegCost(x, maxk=20, family='norm')
    	dim(Ca) # [1] 20 40
    	Cb<-regionSegCost(x, segs=as.integer(c(3, 6, 12, 30)), family='norm')
    	dim(Cb) # [1] 5 5

[Package biomvRCNS version 1.32.0 Index]