calcLikeSegments | R Documentation |
Rather than trying to estimate a single MLE of b
across an entire data
set, it may make more sense fitting the PLB distribution independently
across segments (distinct ranges) of the data. For example, if the full
range of body sizes are not collected using the same sampling protocols,
such as when combining phytoplankton and zooplankton data. Data are input as
EITHER vectors w
and d
of bin breaks and bin counts, OR as a tibble with
one row for each bin and columns as described below.
calcLikeSegments(
p = -1.5,
w = NULL,
d = NULL,
bin_tibble = NULL,
segmentIndices,
...
)
p |
initial value of |
w |
vector of length |
d |
vector of length |
bin_tibble |
data as a tibble, with each row representing a bin and columns:
|
segmentIndices |
the indices of |
... |
further inputs to negLL.PLB.binned *** TODO maybe? |
list containing:
bins_in_segs: tibble with a row for each bin and columns (this is
bin_tibble
with the extra column segment
):
wmin
: minimum body mass of that bin
wmax
: maximum body mass of that bin
binCount
: count in that bin
segment
: which segment the bin falls in, an integer from 1 to S
b_segs: tibble of results with a row for each segment and columns:
segment
: integer indicating the segment being fitted
segMin
: mininum body mass of that segment
segMax
: maximum body mass of that segment
confMin
: minimum of 95\
b
: MLE for b
for that segment
confMax
: maximum of 95\
Andrew Edwards
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