summarise_nls_MC: Summarize Monte Carlo simulations of linear least squares...
In Jonas-Wilhelm/jwtools: Useful tools for biology related projects
summarise_nls_MC R Documentation
Summarize Monte Carlo simulations of linear least squares models
Description
Summarizes the output of the nls_MC() function. For each fitted parameter
mean, original estimate, standard deviation and confidence intervals are computed.
Usage
summarise_nls_MC(data, conf.level = 0.95)
Arguments
data
A tibble generated by nls_MC().
conf.level
Level for confidence interval calculation (defaults to 0.95).
Examples
n <- nls(mpg ~ k * e ^ wt, data = mtcars, start = list(k = 1, e = 2))
s <- nls_MC(n)
summarise_nls_MC(s, conf.level = 0.99)
Jonas-Wilhelm/jwtools documentation built on April 14, 2025, 4:10 a.m.
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| summarise_nls_MC | R Documentation |
Summarize Monte Carlo simulations of linear least squares models
Description
Summarizes the output of the nls_MC() function. For each fitted parameter mean, original estimate, standard deviation and confidence intervals are computed.
Usage
summarise_nls_MC(data, conf.level = 0.95)
Arguments
data |
A tibble generated by nls_MC(). |
conf.level |
Level for confidence interval calculation (defaults to 0.95). |
Examples
n <- nls(mpg ~ k * e ^ wt, data = mtcars, start = list(k = 1, e = 2))
s <- nls_MC(n)
summarise_nls_MC(s, conf.level = 0.99)
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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