nlsB: Determine the nonlinear (weighted) MCMC estimates of the...

In jgodet/utilitR: Lots of useful functions

Determine the nonlinear (weighted) MCMC estimates of the parameters of a nonlinear model.

Description

Determine the nonlinear (weighted) MCMC estimates of the parameters of a nonlinear model.

Usage

nlsB(formula, data, graphOutput = TRUE, nIter = 10000, thin = 1)

Arguments

formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
data	an optional data frame containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which blm is called.
graphOutput	regression parameters graphical output (MCMC Trace and posterior density)
nIter	number of iterations
thin	thinning interval for monitors

Details

Models for lm are specified symbolically. A typical model has the form response ~ terms where response is the (numeric) response vector and terms is a series of terms which specifies a linear predictor for response.

Value

non-linear regression parameters

Author(s)

JuG

Examples

data(mtcars)
summary(lm(mpg~ cyl + vs+gear+carb,data=mtcars))
lmB(mpg~ cyl + vs+gear+carb,data=mtcars,nIter=50000)
lmB(mpg~ .,data=mtcars,nIter=50000,graphOutput=FALSE)

jgodet/utilitR documentation built on May 16, 2024, 12:01 p.m.