Computes relative bias between variables estimated from field data and their TLS counterparts derived from TLS data. Field estimates and TLS metrics for a common set of plots are required in order to compute relative bias. These data must come from any of the three different plot designs currently available (circular fixed area, k-tree and angle-count) and correspond to plots with incremental values for the plot design parameter (radius, k and BAF, respectively). In addition to computing relative bias, interactive line charts graphically representing the values obtained between each field estimate and its related TLS metrics are also generated.
relative.bias(simulations,
variables = c("N", "G", "d", "dg", "d.0", "h", "h.0"),
save.result = TRUE, dir.result = NULL)
If no “fixed.area.plot” element exists in simulations
argument, missing; otherwise, the matrix will include estimates of the the relative bias
under circular fixed area plot design between each field estimation specified in
variables argument and its TLS counterpart(s) existing in the
“fixed.area.plot” element in the simulations argument. Each
row will correspond to a radius value, and the following columns will be included:
radius: radius (m) of the simulated plots used for computing
the estimated relative bias.
Column(s) ‘<x>.<y>’: numeric column(s) containing
estimated relative bias between ‘<x>’, a field estimation,
and ‘<y>’, a TLS counterpart.
If no “k.tree.plot” element exists in the simulations
argument, missing; otherwise, the matrix will include the relative bias estimated
in the k-tree plot design between each field estimation specified in
variables argument and its TLS counterpart(s) existing in
“k.tree.plot” element in simulations argument. Each row will correspond to a k value, and the following columns will be included:
k: number of trees (trees) of the simulated plots used for
computing the estimated relative bias.
Column(s) ‘<x>.<y>’: numeric column(s) containing
estimated relative bias between ‘<x>’, a field estimation,
and ‘<y>’, a TLS counterpart.
If no “angle.count” element exists in simulations
argument, missing; otherwise, the matrix will contain estimated relative bias under
angle-count plot design between each field estimation specified in the
variables argument and its TLS counterpart(s) existing in the
“angle.count.plot” element in the simulations argument. Each
row will correspond to a BAF value, and the following
columns will be included:
BAF: BAF (\({m}^{2}/ha\)) of the simulated plots used for computing
the estimated relative bias.
Column(s) ‘<x>.<y>’: numeric column(s) containing
estimated relative bias between ‘<x>’, a field estimation,
and ‘<y>’, a TLS counterpart.
List containing variables estimated from field data and metrics
derived from TLS data. The structure and format must be analogous to output
returned by the simulations function. In particular, teh list must include
at least one of the following named elements:
fixed.area.plot: same description and format as indicated
for same named element in simulations argument of
correlations function. The only difference is the
columns required when it is included in the argument: in adittion to id,
radius and at least one of the field estimate columns, it must
include at least one TLS counterpart for each field estimate condidered.
k.tree.plot: same description and format as indicated for
same named element in simulations argument of
correlations function. The only difference is the columns required when it is included in the argument: in adittion to id, k
and at least one of the field estimate columns, it must include at
least one TLS counterpart for each field estimate considered.
angle.count.plot: same description and format as indicated
for the same named element in the simulations argument of
correlations function. The only difference is the columns that are required when this element is included in the argument: in adittion to id,
BAF and at least one of the field estimate columns, it must
contain at least one TLS counterpart for each field estimate considered.
Optional character vector naming field estimates for which the relative bias
between them and all their available TLS counterparts will be computed. If
this argument is specified by the user, it must contain at least one of the
following character strings: “N”, “G”,
“V”, “d”, “dg”,
“dgeom”, “dharm”, “d.0”,
“dg.0”, “dgeom.0”, “dharm.0”,
“h”, “hg”, “hgeom”,
“hharm”, “h.0”, “hg.0”,
“hgeom.0”, or “hharm.0”. If this argument is not
specified by the user, it will be set to
c("N", "G", "V", "d", "dg", "d.0", "h", "h.0") by default. In both
cases, all the elements in simulations argument
must include at least the columns corresponding to the field estimations specified in the
variables argument.
Optional logical which indicates whether or not the output files described in
‘Output Files’ section must be saved in dir.result. If
this argument is not specified by the user, it will be set to TRUE by
default and, as a consequence, the output files will be saved.
Optional character string naming the absolute path of an existing directory
where files described in ‘Output Files’ section will be saved.
.Platform$file.sep must be used as the path separator in
dir.result. If this argument is not specified by the user, and
save.result is TRUE, it will be set to NULL by default and,
as a consequence, the current working directory of the R process will be
assigned to dir.result during the execution.
During the execution, if the save.result argument is TRUE, the
function will print the matrices described in the ‘Value’ section to files. These
are written without row names in dir.result directory using
write.csv function from the utils package. The pattern used
for naming these files is RB.<plot design>.csv, where
<plot design> is equal to “fixed.area.plot”,
“k.tree.plot” or “angle.count.plot” is according to the
plot design.
Furthermore, if the save.result argument is TRUE, interactive line
charts graphically representing relative bias values will also be created and saved
in the dir.result directory by means of the saveWidget function
in the htmlwidgets package. Generated widgets allow users to
consult relative bias data directly on the plots, select/deselect different
sets of traces, to zoom and scroll, and so on. The pattern used for naming
these files is RB.<x>.<plot design>.html, where <plot design> is
indicated for the previously described files, and <x> equals N,
G, V, d and/or h according to the variables
argument. All relative biases related to diameters are
plotted in the same chart (files named as RB.d.<plot design>.html), and
the same applies to those related to heights (files named as
RB.h.<plot design>.html).
Juan Alberto Molina-Valero and Adela Martínez-Calvo.
For each radius, k or BAF value (according to the currently available plot
designs: circular fixed area, k-tree and angle-count), this function computes the relative
bias between each variable estimated from field data, and specified in the
variables argument, and their counterparts derived from TLS data, and
existing in the data frames included in the simulations argument. TLS
metrics considered counterparts for each field estimate are
detailed below (see simulations ‘Value’ function
for details about used notation):
TLS counterparts for N are N.tls, N.hn,
N.hr, N.hn.cov, N.hr.cov and N.sh in the fixed
area and k-tree plot designs; and N.tls and N.pam in the
angle-count plot design.
TLS counterparts for G are G.tls, G.hn,
G.hr, G.hn.cov, G.hr.cov and G.sh in the fixed
area and k-tree plot designs; and G.tls and G.pam in the
angle-count plot design.
TLS counterparts for V are V.tls, V.hn,
V.hr, V.hn.cov, V.hr.cov and V.sh in the fixed
area and k-tree plot designs; and V.tls and V.pam in the
angle-count plot design.
TLS counterparts for d, dg, dgeom, dharm,
d.0, dg.0, dgeom.0, and dharm.0 are,
respectively: d.tls, dg.tls, dgeom.tls,
dharm.tls, d.0.tls, dg.0.tls, dgeom.0.tls,
and dharm.0.tls in any of the three available plot designs.
TLS counterparts for h, hg, hgeom, hharm,
h.0, hg.0, hgeom.0, and hharm.0 are,
respectively h.tls, hg.tls, hgeom.tls,
hharm.tls, h.0.tls, hg.0.tls, hgeom.0.tls, and
hharm.0.tls in any of the three available plot designs. In adittion, P99 is also taken into account as a counterpart for all
these field estimates.
The relative bias between a field estimation and any of its TLS counterparts is estimated as follows $$\frac{\frac{1}{n}\sum_{i = 1}^{n}{y_{i}} - \frac{1}{n}\sum_{i = 1}^{n}{x_{i}}}{\frac{1}{n}\sum_{i = 1}^{n}{x_{i}}} * 100$$ where \(x_{i}\) and \(y_{i}\) are the values of the field estimate and its TLS counterpart, respectively, corresponding to plot \(i\) for \(i = 1, \ldots, n\).
simulations, correlations.
# \donttest{
# Load variables estimated from field data, and TLS metrics
# corresponding to Rioja data set
data("Rioja.simulations")
# Establish directory where relative bias results corresponding to Rioja example
# will be saved. For instance, current working directory
dir.result <- getwd()
# Compute relative bias between field-based estimates of TLS metrics
# corresponding to Rioja example
# Relative bias for variables by default
rb <- relative.bias(simulations = Rioja.simulations, dir.result = dir.result)
# Relative bias for variable 'N'
rb <- relative.bias(simulations = Rioja.simulations, variables = "N",
dir.result = dir.result)
# Relative bias corresponding to angle-count design for all available variables
rb <- relative.bias(simulations = Rioja.simulations["angle.count"],
variables <- c("N", "G", "V", "d", "dg", "dgeom", "dharm",
"d.0", "dg.0", "dgeom.0", "dharm.0", "h",
"hg", "hgeom", "hharm", "h.0", "hg.0",
"hgeom.0", "hharm.0"),
dir.result = dir.result)
# }
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