cv: Compute model quality
In sjstats: Collection of Convenient Functions for Common Statistical Computations
cv R Documentation
Compute model quality
Description
Compute the coefficient of variation.
Usage
cv(x, ...)
Arguments
x
Fitted linear model of class lm, merMod (lme4)
or lme (nlme).
...
More fitted model objects, to compute multiple coefficients of
variation at once.
Details
The advantage of the cv is that it is unitless. This allows
coefficient of variation to be compared to each other in ways
that other measures, like standard deviations or root mean
squared residuals, cannot be.
Value
Numeric, the coefficient of variation.
Examples
data(efc)
fit <- lm(barthtot ~ c160age + c12hour, data = efc)
cv(fit)
sjstats documentation built on May 29, 2024, 12:09 p.m.
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| cv | R Documentation |
Compute model quality
Description
Compute the coefficient of variation.
Usage
cv(x, ...)
Arguments
x |
Fitted linear model of class |
... |
More fitted model objects, to compute multiple coefficients of variation at once. |
Details
The advantage of the cv is that it is unitless. This allows coefficient of variation to be compared to each other in ways that other measures, like standard deviations or root mean squared residuals, cannot be.
Value
Numeric, the coefficient of variation.
Examples
data(efc)
fit <- lm(barthtot ~ c160age + c12hour, data = efc)
cv(fit)
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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