Pdata_given_rangerow_dp: Calculate probability of detection data given a true...
In BioGeoBEARS: BioGeography with Bayesian (and Likelihood) Evolutionary Analysis in R Scripts

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/BioGeoBEARS_detection_v1.R

This function calculates P(data|range,dp), i.e. the probability of some detection and taphonomic control counts, given the true geographic range/state, and dp, a detection probability (and, optionally, a false detection probability, fdp).

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  Pdata_given_rangerow_dp(truerange_areas, numareas,
    detects_df, controls_df, mean_frequency = 0.1, dp = 1,
    fdp = 0)

`truerange_areas`	The list of areas (as 0-based numbers) in this geographic range/state.
`numareas`	The function needs to know the total number of areas in the analysis.
`detects_df`	A column/vector of detection counts, as produced from a column of the output from `read_detections`.
`controls_df`	A column/vector of detection counts, as produced from a column of the output from `read_controls`.
`dp`	The detection probability. This is the per-sample probability that you will detect the OTU in question. In other words, the model assumes that each specimen from the taphonomic control group has a chance of being a representative of the OTU you are looking for. The default is 1, which assumes perfect detection, i.e. the assumption being made in all historical biogeography analyses that do not take into account detection probability. A value of 1 will only work when the taphonomic control count equals the detection count; any other data would have likelihood=0.
`fdp`	The false detection probability. This is probability of falsely concluding a detection occurred, when in fact the specimen was of something else. The default is 0, which assumes zero error rate, i.e. the assumption being made in all historical biogeography analyses that do not take into account detection probability. This option is being included for completeness, but it may not be wise to try to infer both `dp` and `fdp` at once due to identifiability issues (and estimation of fdp may take a very large amount of data).
`mean_frequency`	This is the proportion of samples from the taphonomic control group that will truly be from this OTU, GIVEN that the OTU is present. This could be estimated, but a decent first guess is (total # samples of OTU of interest / total # of samples in the taphonomic control group where the OTU is known to be present). All that is really needed is some reasonable value, such that more sampling without detection lowers the likelihood of the data on the hypothesis of true presence, and vice versa. This value can only be 1 when the number of detections = the number of taphonomic control detections, for every OTU and area. This is the implicit assumption in e.g. standard historical biogeography analyses in LAGRANGE or BioGeoBEARS.

The idea of taphonomic controls dates back at least to work of Bottjer & Jablonski (1988). The basic idea is that if you have taxa of roughly similar detectability, then detections of other taxa give some idea of overall detection effort. Obviously this is a very simple model that can be criticized in any number of ways (different alpha diversity in each region, different detectability of individual taxa, etc.), but it is a useful starting point as there has been no implementation of any detection model in historical/phylogenetic biogeography to date.

One could imagine (a) every OTU and area has a different count of detections and taphonomic control detections, or (b) the taphonomic control detections are specified by area, and shared across all OTUs. Situation (b) is likely more common, but this function assumes (a) as this is the more thorough case. Behavior (b) could be reproduced by summing each column, and/or copying this sum to all cells for a particular area.

dtf

Go BEARS!

Nicholas J. Matzke matzke@berkeley.edu

http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster

Matzke_2012_IBS

Bottjer_Jablonski_1988

rcpp_calc_anclikes_sp_COOweights_faster

testval=1

Loading required package: rexpokit
Loading required package: cladoRcpp
Loading required package: ape
Loading required package: phylobase

Attaching package: 'phylobase'

The following object is masked from 'package:ape':

    edges