18918 hits since June 13, 2007

Random regression (RR) models have become a popular choice for the analysis of longitudinal data or 'repeated' records. Typically, analyses require numerous parameters, i.e. (co)variances between RR coefficients and measurement error variances, to be estimated, especially if the model of analysis includes additional random effects such as maternal effects. Programs for RR model analysis using restricted maximum likelihood (REML) are available. However, the high computational demands of REML analyses for RR models severely limit the feasibility of RR analyses for data sets sufficiently large to support estimation of the pertaining (co)variance components, in particular for models fitting many RR coefficients.

Bayesian analyses using Gibbs sampling provide an alternative which is markedly simpler to implement than REML. Whilst the range of models which can be accommodated via Gibbs sampling may be more restrictive and the total computing time required may be longer than for corresponding REML analyses, memory requirements are substantially less. Hence Bayesian methodology readily facilitates large scale analyses. Apart from these practical advantages, of course, it provides estimates of complete sampling distributions rather than just simple point estimates.

** RRGIBBS** performs a single task : the analysis of a simple class of
RR models using Bayesian methodology. Models may involve :

- multiple fixed effects, including cross-classified effects and 'standard' covariables, as well as fixed regression(s) on Legendre polynomials of the meta-meter;
- sets of random regression coefficients, regressing on orthogonal polynomials or user-defined functions of a single, continuous covariable, the so-called 'meta-meter';
- multiple random effects, distributed proportionally to an identity matrix or the numerator relationship matrix between animals,
- different orders of polynomial fit for each random effect,
- homogeneous or heterogeneous measurement error variances modelled as a step function of the covariable,
- a single trait only.

Model specification is via a parameter file. The run time behaviour
of **RRGIBBS** can be modified by a number of command line
options. **RRGIBBS** is a 'no-frills' program. It basically
offers little more than a reasonably efficient Gibbs sampler for a
range of random regression analyses. The main output are files with
the successive samples of (co)variance components drawn, ready for
your favourite post-Gibbs analysis. In addition, limited summary
information is produced, including estimates of covariance matrices
among RR coefficients and measurement error variances obtained as
means over samples (after 'burn-in'), and approximate 95% highest
posterior density regions.

- While every effort
has been made to ensure that
**RRGIBBS**does what it claims to do, there is absolutely**no**guarantee for its correctness. - You are using
**RRGIBBS**entirely at your own risk, and there is**no**user-support service.

- LINUX :
**RRGIBBS**for Linux has been compiled under Red Hat Fedora 2, using the Lahey/Fujitsu FORTRAN 95 compiler (version L6.20c). Download :RRGibbs.Linux.gz (391 KB, 1635 downloads since 19/6/2007).

Updated to accommodate sparse basis functions such as B-splines. - LINUX 64-bit version: compiled under Red Hat Fedora 5, using the Pathscale F95 compiler (version 2.4, 2006).
Download :
RRGibbs.Linux64bit.gz (879 KB, 0 downloads since 19/11/2007). -
COMPAQ Alpha station :
**RRGIBBS**has been compiled for a Compaq True64 work station, using the Compaq FORTRAN compiler (V5.5-2602; UNIX V5.1A) : Download :RRGibbs.Compaq64.gz (1.07 MB, 1168 downloads since 19/6/2007). - Updated to accommodate sparse basis functions such as B-splines. A corresponding file for a 32 bit machine, compiled using the Compaq FORTRAN compiler (V5.3-915) is available as :RRGibbs.Compaq32.gz (901 KB, 1501 downloads since 19/6/2007). -
SUN work station :
A Solaris version has been compiled using Sun Workshop 6 Fortran 95 6.0 on a SPARC
Ultra work station. Download :
RRGibbs.Solaris.gz (233 KB, 1654 downloads since 19/6/2007).

Download bsplines.f90.gz (2 KB, 3654 downloads since 19/6/2007). or a pre-compiled Linux executable bsplines_lnx.gz (191 KB, 1620 downloads since 19/6/2007).

Download bin2out.f90.gz (409 B, 3484 downloads since 19/6/2007). or a pre-compiled Linux executable bin2out_lnx.gz (5 KB, 3434 downloads since 19/6/2007).