Biology Reference
In-Depth Information
If the
type
argument is set to
"PT.adjusted"
, the Portmanteau test is com-
puted; the Breusch-Godfrey test is computed if
type
is set to
"BG"
.
In addition, the univariate and multivariate ARCH-LM tests for heteroscedastic-
ity are implemented in
arch.test
.
> arch.test(var.2c)
ARCH (multivariate)
data: Residuals of VAR object var.2c
Chi-squared = 538.8897, df = 500, p-value = 0.1112
As was the case for
normality.test
, by default only the multivariate test is
computed. We can set
multivariate.only
to
FALSE
to compute the univariate
tests as well.
> arch.test(var.2c, multivariate.only = FALSE)
For a complete overview of the functionality implemented in
vars
, we refer the
reader to
Pfaff
(
2008a
,
b
).
3.5.2 LASSO Learning: lars and simone
Several implementations of LASSO are available in
R
; in the following, we will use
the
lars
package developed by
Hastie and Efron
(
2012
). Other possible choices are
glmnet
by
Friedman et al.
(
2010
)and
penalized
by
Goeman
(
2012
).
> library(lars)
Consider the
arth800
MTS data set from the
GeneNet
package.
arth800
de-
scribes the temporal expression of 800 genes of the
Arabidopsis thaliana
during the
diurnal cycle. In the following example, we will consider a subset
arth12
of 12
genes.
> library(GeneNet)
> data(arth800)
> subset = c(60, 141, 260, 333, 365, 424, 441, 512,
+ 521, 578, 789, 799)
> arth12 = arth800.expr[, subset]
Model estimation is performed using the
lars
function for a target variable
specified by a vector (
y
) and a set of possible parents specified by a matrix of pre-
dictors (
x
). The
arth800
data set is composed of 2 time series of 11 time points
each: there are two repeated measurements for each time point. Suppose we want to
estimate a VAR(1) process. Consequently, we removed the two repeated measure-
ments for the first time point from
y
and the two repeated measurements for the
last time point from
x
; they cannot be used for the LASSO due to the lack of the
corresponding time points in
x
and
y
, respectively.
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