BAMLSS families for multivariate Gaussion regression models. The multivariate Gaussian distribution is reparameterized using the (modified) Cholesky decomposition of the covariance matrix.

Installation

You can either install it directly on your system by using remotes or devtools in an R session:

remotes::install_github("meteosimon/mvnchol")

Or clone it using git and a git client for your system. And build and INSTALL it after cloning, e.g. in a bash:

git clone git@github.com:meteosimon/mvnchol.git
R CMD build mvnchol
R CMD INSTALL mvnchol_0.3.0.tar.gz

First Model

library(bamlss)

## Loading required package: coda

## Loading required package: colorspace

## Loading required package: mgcv

## Loading required package: nlme

## This is mgcv 1.8-40. For overview type 'help("mgcv-package")'.

## 
## Attaching package: 'bamlss'

## The following object is masked from 'package:mgcv':
## 
##     smooth.construct

library(mvnchol)
data(simdata)
d <- simdata$d
f <- make_formula(y1 | y2 | y3 ~ s(x) | s(x) | s(x))
b <- bamlss(f, family = mvnchol_bamlss(k = 3), data = d)

## AICc 9796.373 logPost -5012.88 logLik -4850.79 edf 46.275 eps 1.0000 iteration   1
## AICc 9471.761 logPost -4863.12 logLik -4674.34 edf 59.666 eps 1.0564 iteration   2
## AICc 9432.365 logPost -4843.92 logLik -4654.78 edf 59.539 eps 0.2204 iteration   3
## AICc 9423.675 logPost -4840.18 logLik -4650.00 edf 59.947 eps 0.2975 iteration   4
## AICc 9421.974 logPost -4839.73 logLik -4648.88 edf 60.206 eps 0.0972 iteration   5
## AICc 9421.608 logPost -4839.75 logLik -4648.59 edf 60.300 eps 0.1687 iteration   6
## AICc 9421.519 logPost -4839.81 logLik -4648.51 edf 60.337 eps 0.0098 iteration   7
## AICc 9421.465 logPost -4839.82 logLik -4648.48 edf 60.336 eps 0.0027 iteration   8
## AICc 9421.456 logPost -4839.82 logLik -4648.47 edf 60.340 eps 0.0008 iteration   9
## AICc 9421.452 logPost -4839.83 logLik -4648.47 edf 60.341 eps 0.0002 iteration  10
## AICc 9421.450 logPost -4839.83 logLik -4648.47 edf 60.342 eps 0.0000 iteration  11
## AICc 9421.450 logPost -4839.83 logLik -4648.47 edf 60.342 eps 0.0000 iteration  11
## elapsed time:  3.75sec
## Starting the sampler...
## 
## |                    |   0%  1.14min
## |*                   |   5%  1.04min  3.27sec
## |**                  |  10% 58.11sec  6.46sec
## |***                 |  15% 54.07sec  9.54sec
## |****                |  20% 52.46sec 13.11sec
## |*****               |  25% 50.73sec 16.91sec
## |******              |  30% 48.31sec 20.70sec
## |*******             |  35% 45.56sec 24.53sec
## |********            |  40% 42.54sec 28.36sec
## |*********           |  45% 39.33sec 32.18sec
## |**********          |  50% 36.00sec 36.00sec
## |***********         |  55% 32.49sec 39.71sec
## |************        |  60% 28.98sec 43.48sec
## |*************       |  65% 25.43sec 47.23sec
## |**************      |  70% 21.93sec 51.17sec
## |***************     |  75% 18.46sec 55.38sec
## |****************    |  80% 14.88sec 59.52sec
## |*****************   |  85% 11.19sec  1.06min
## |******************  |  90%  7.48sec  1.12min
## |******************* |  95%  3.74sec  1.19min
## |********************| 100%  0.00sec  1.25min

plot(b, model = "lambda12")