dendro.varcov {DendroSync} | R Documentation |
Fit variance-covariance mixed models on tree-ring chronologies
Description
The function calculates variance-covariance (VCOV) mixed models from a data.frame
with tree-ring width index and years for each chronology following the methodology described in Shestakova et al. (2014).
The mixed models relate tree-ring width (Y
) against specific names of tree-ring width chronologies (A
), using years and grouping variable as random factors to characterize the strength of the common signal across the grouping variable.
First, a linear mixed-effect model with null positive-definite matrix structure or broad evaluation is fitted and the subsequent models are consequently derived from it using the function update
.
When a data.frame
with tree-ring width index has NAs the models are fitted with na.action
= na.omit
. Simultaneously, complete.cases
is applied to guarantee that rows have no missing values across the entire data.frame
.
Usage
dendro.varcov(formula, varTime = "", varGroup = "", data,
homoscedastic = TRUE, null.mod = FALSE, all.mod = FALSE)
Arguments
formula |
a model |
varTime |
a |
varGroup |
a |
data |
a |
homoscedastic |
|
null.mod |
|
all.mod |
|
Details
The function fits a set of variance-covariance mixed models following Shestakova et al. (2014). A total of 7 different variance-covariance mixed models can be fitted: a null positive-definite matrix structure (mBE), and the homoscedastic and heteroscedastic versions of a diagonal positive-definite matrix structure (mNE, mHeNE), a positive-definite matrix with compound symmetry structure (mCS, mHeCS) and a general positive-definite matrix structure (mUN, mHeUN). Note that if null.mod is TRUE
the function only fits broad evaluation model (mBE), this is set to FALSE
by default. If all.mod is TRUE
the function fits heteroscedastic and homoscesdastic versions of all models. This is set to FALSE
by default, because for large-datasets it may take a long time to converge.
Value
The function returns a list
containing the following components:
for
null.mod = TRUE
:
mBE |
an object of class "lme" representing the linear mixed-effects model fit of null positive-definite matrix structure or broad evaluation. See |
for
homoscedastic = TRUE
:
mNE |
an object of class "lme" representing the linear mixed-effects model fit of a diagonal positive-definite matrix structure or narrow evaluation. See |
mCS |
an object of class "lme" representing the linear mixed-effects model fit of a positive-definite matrix with compound symmetry structure. See |
mUN |
an object of class "lme" representing the linear mixed-effects model fit of a general positive-definite matrix structure or unstructured. See |
for
homoscedastic = FALSE
:
mHeNE |
an object of class "lme" representing the linear mixed-effects model fit of the heteroscedastic variant of a diagonal positive-definite matrix structure or narrow evaluation. See |
mHeCS |
an object of class "lme" representing the linear mixed-effects model fit of the heteroscedastic variant of a positive-definite matrix with compound symmetry structure. See |
mHeUN |
an object of class "lme" representing the linear mixed-effects model fit of the heteroscedastic variant of a general positive-definite matrix structure or unstructured. See |
for
all.mod = TRUE
:
all.mod |
The function returns the homoscedastic and heteroscedastic versions of all fitted models. |
Author(s)
Josu G. Alday, Tatiana A. Shestakova, Victor Resco de Dios, Jordi Voltas
References
Shestakova, T.A., Aguilera, M., Ferrio, J.P., Gutierrez, E. & Voltas, J. (2014). Unravelling spatiotemporal tree-ring signals in Mediterranean oaks: a variance-covariance modelling approach of carbon and oxygen isotope ratios. Tree Physiology 34: 819-838.
Shestakova, T.A., Gutierrez, E., Kirdyanov, A.V., Camarero, J.J., Genova, M., Knorre, A.A., Linares, J.C., Resco de Dios, V., Sanchez-Salguero, R. & Voltas, J. (2016). Forests synchronize their growth in contrasting Eurasian regions in response to climate warming. Proceedings of the National Academy of Sciences of the United States of America 113: 662-667.
See Also
lmeObject
, na.action
, complete.cases
Examples
## Calculate variance-covariance models on Iberian Peninsula conifers
# chronologies using two different grouping strategies.
# Tree-ring width chronologies are grouped according to taxonomic (i.e. Species)
# or geographic (i.e. Region) criteria.
#User-defined homoscedastic or heteroscedastic variances can be fitted.
data(conifersIP)
#Chop the data from 1960 to 1989.
conif.30 <- conifersIP[conifersIP$Year>1959 & conifersIP$Year<1990,]
summary(conif.30$Year)
##Fit the homoscedastic set of varcov models (mBE, mNE, mCS, mUN)
# using taxonomic grouping criteria (ie. Species)
ModHm <- dendro.varcov(TRW ~ Code, varTime = "Year", varGroup = "Species",
data = conif.30, homoscedastic = TRUE)
summary(ModHm)# Class and length of list elements
ModHm
ModHm[2]#mNE fitted model results
##Fit the heteroscedastic set of varcov models (mBE, mHeNE, mHeCS, mHeUN)
# using geographic grouping criteria (ie. Region)
ModHt <- dendro.varcov(TRW ~ Code, varTime = "Year", varGroup = "Region",
data = conif.30, homoscedastic = FALSE)
summary(ModHt)# Class and length of list elements
ModHt
ModHt[3]#mHeCS fitted model results