fit_var: sigma^2 estimation
In reedssorenson/RNAdecay: Maximum Likelihood Decay Modeling of RNA Degradation Data
fit_var R Documentation
sigma^2 estimation
Description
Calculates the variance (sigma^2) estimate from the sum of the squared errors from the fit model.
Usage
fit_var(sse, n)
Arguments
sse
is the minimum SSE (sum of the squared errors) from the slsqp() fitting
n
is the total number of observations of a single gene (e.g., 8 time points X 4 replicates X 4 treatments/genotypes = 128)
Value
returns the sigma squared estimate
Examples
fit_var(1,128)
reedssorenson/RNAdecay documentation built on Oct. 28, 2023, 11:31 a.m.
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| fit_var | R Documentation |
sigma^2 estimation
Description
Calculates the variance (sigma^2) estimate from the sum of the squared errors from the fit model.
Usage
fit_var(sse, n)
Arguments
sse |
is the minimum SSE (sum of the squared errors) from the slsqp() fitting |
n |
is the total number of observations of a single gene (e.g., 8 time points X 4 replicates X 4 treatments/genotypes = 128) |
Value
returns the sigma squared estimate
Examples
fit_var(1,128)
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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