deviances: A function to extract deviances for all dimension, including...
In RCM: Fit row-column association models with the negative binomial distribution for the microbiome
Description
Usage
Arguments
Value
Description
A function to extract deviances for all dimension,
including after filtering on confounders
Usage
1
Arguments
rcm
an object of the RCM class
squaredSum
a boolean, should total deviance be returned?
Total deviances can be deceptive and not correspond to the differences in
log-likelihood. As the dispersion is different for each model.
To compare models it is better to compare likelihoods.
Value
If Sum is FALSE, a named array of deviance residuals of the
independence model and all models with dimension 1 to k, including after
filtering on confounders. Otherwise a table with total deviances (the sum of
squared deviance residuals), deviance explained and cumulative deviance
explained.
RCM documentation built on Nov. 8, 2020, 5:22 p.m.
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Description Usage Arguments Value
Description
A function to extract deviances for all dimension, including after filtering on confounders
Usage
1 |
Arguments
rcm |
an object of the RCM class |
squaredSum |
a boolean, should total deviance be returned? Total deviances can be deceptive and not correspond to the differences in log-likelihood. As the dispersion is different for each model. To compare models it is better to compare likelihoods. |
Value
If Sum is FALSE, a named array of deviance residuals of the independence model and all models with dimension 1 to k, including after filtering on confounders. Otherwise a table with total deviances (the sum of squared deviance residuals), deviance explained and cumulative deviance explained.
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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