# randomize

0th

Percentile

##### Transform Smooth Constructs to Random Effects

The transformer function takes a bamlss.frame object and transforms all smooth.constructs into a random effects representation. Note that this is only possible for smooth terms with a single smoothing variance. The function is based on function smooth2random.

Keywords
regression, smooth
##### Usage
randomize(x)
##### Arguments
x

Object returned from function bamlss.frame.

##### Details

The decomposition is achieved by a spectral decomposition of the penalty and design matrix by finding a basis of the null space of the penalty matrix. This feature is used, e.g., for the JAGS sampler function. For more details see also jagam.

A transformed bamlss.frame. To each smooth.construct model term an element named "Xf", the fixed effects design matrix, and an element "rand$Xr", the random effects design matrix, is added. In addition, for re-transforming parameters elements "trans.U" and "trans.D" are supplied. See also function smooth2random. ##### References Fahrmeir L, Kneib T, Lang S, Marx B (2013). Regression - Models, Methods and Applications. Springer-Verlag, Berlin. ISBN 978-3-642-34332-2. Wood S.N. (2006). Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC. ##### See Also bamlss.frame, bamlss, smooth2random. ##### Aliases • randomize ##### Examples # NOT RUN { ## Simulate data. d <- GAMart() ## Create a "bamlss.frame". bf <- bamlss.frame(num ~ s(x1) + s(x2) + s(x3) + s(lon,lat), data = d) ## Structure of the "s(x1)" smooth.construct. str(bf$x$mu$smooth.construct[["s(x1)"]])

## Transform.
bf <- randomize(bf)

## and random effect matrices.
str(bf$x$mu\$smooth.construct[["s(x1)"]])
# }

Documentation reproduced from package bamlss, version 1.1-2, License: GPL-2 | GPL-3

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