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- W4256146306 abstract "The nlr function fits the model using methods that depend on the choice of classical or robust options. nlr includes features to handle heteroscedasticity of errors, autocorrelated errors, and outlier detection. To detect outliers, the nlr package uses some statistical measures. The object system can define a nonlinear regression model, a robust loss rho function, and a heteroscedastic variance in an object called nl.form. If any error or warning occurs during an nlr procedure, the output includes the Fault object, which explains the error type and the function that produced the error. nlr.control means that the parameters will be estimated using ordinary least squares and nlr.control means the parameters will be estimated using least median squared residual estimates. Initial values for parameters can be calculated from a geometric interpretation of the model and then inserted in the selfStart function slot. By default, the nlr function estimates parameters using robust methods based on the MM-estimator." @default.
- W4256146306 created "2022-05-12" @default.
- W4256146306 date "2018-06-29" @default.
- W4256146306 modified "2023-09-27" @default.
- W4256146306 title "<tt>nlr</tt> Package" @default.
- W4256146306 doi "https://doi.org/10.1002/9781119010463.ch8" @default.
- W4256146306 hasPublicationYear "2018" @default.
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