gaussianffLocal: Models expression data using generalized linear model with...
In phemd: Phenotypic EMD for comparison of single-cell samples
Description
Usage
Arguments
Details
Value
View source: R/functions-core.R
Description
Useful for modeling pre-normalized single-cell expression data.
Usage
1
gaussianffLocal(dispersion = 0, parallel = FALSE, zero = NULL)
Arguments
dispersion
Dispersion parameter. If 0, then estimate as described in VGAM 1.0-5 documentation.
parallel
A logical or formula. If a formula, the response of the formula should be a logical and the terms of the formula indicates whether or not those terms are parallel.
zero
An integer-valued vector specifying which linear/additive predictors are modelled as intercepts only. The values must be from the set 1...M where Mis the number of columns of the matrix response.
Details
Private method (not to be called by user directly). Requires VGAM package. Obtained from VGAM v1.0-5 (https://www.rdocumentation.org/packages/VGAM/versions/1.0-5/topics/gaussianff)
Value
Generalized linear model with Gaussian error
phemd documentation built on Nov. 8, 2020, 8:15 p.m.
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Description Usage Arguments Details Value
View source: R/functions-core.R
Description
Useful for modeling pre-normalized single-cell expression data.
Usage
1 | gaussianffLocal(dispersion = 0, parallel = FALSE, zero = NULL)
|
Arguments
dispersion |
Dispersion parameter. If 0, then estimate as described in VGAM 1.0-5 documentation. |
parallel |
A logical or formula. If a formula, the response of the formula should be a logical and the terms of the formula indicates whether or not those terms are parallel. |
zero |
An integer-valued vector specifying which linear/additive predictors are modelled as intercepts only. The values must be from the set 1...M where Mis the number of columns of the matrix response. |
Details
Private method (not to be called by user directly). Requires VGAM package. Obtained from VGAM v1.0-5 (https://www.rdocumentation.org/packages/VGAM/versions/1.0-5/topics/gaussianff)
Value
Generalized linear model with Gaussian error
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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