lmB | R Documentation |
Fitting Linear Models using bayesian inference
lmB(
formula,
data = NULL,
graphOutput = TRUE,
nIter = 10000,
thin = 1,
returnCodaSamples = FALSE
)
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 |
returnCodaSamples |
if TRUE, return the cosa samples output as a mcmc.list |
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.
regression parameters
JuG
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)
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