GenEst v1.4.5

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Generalized Mortality Estimator

Command-line and 'shiny' GUI implementation of the GenEst models for estimating bird and bat mortality at wind and solar power facilities, following Dalthorp, et al. (2018) <doi:10.3133/tm7A2>.

Readme

GenEst

GenEst: Generalized Fatality Estimator

GenEst is a tool for estimating mortalities from efficiency, persistence, and carcass data.

DISCLAIMER

This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U.S. Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the software.

Installation

Setup and installation require several steps. Do not skip any steps.

Updated version of R (>= 3.5.0, released on 23 April 2018):

R is free and open source software for statistical computing. If R is not installed on your computer or if your version of R is <3.5.0, download and install the latest version from https://cran.r-project.org/, following the instructions provided at the site. In particular, "Download" and then "install R for the first time" (if working in Windows), or "Download" and then follow the further instructions on the subsequent web page (if working on Mac OS or Linux-like OS). If you already have an older copy of R installed on your computer, the new version will be installed alongside the old. Unless you know a reason why you want to keep both versions, it is usually a good idea to uninstall the old version to avoid confusion and clutter.

NOTE TO EXPERIENCED R USERS: When you install a new version of R, packages that you previously installed under an older version may not be immediately available to the new R. If not, the easiest way to make them available is to copy the package folders in your old "library" folder into the "library" folder in your new R installation. Then, enter update.packages() in R. If asked about a CRAN mirror, choose the nearest location. If you are working in Windows OS and are asked whether you want to install packages "from source", choose "No".

Third-party packages:

Several third-party pacakges are required; all are free and open source and available from CRAN. The easiest way to install them is to run the following commands in R (with guidance concerning potential dialog boxes given below the commands):


package_req <- c("corpus", "DT", "gsl", "gtools", "htmltools", "htmlwidgets", "lubridate", "MASS", "matrixStats", "mvtnorm", "Rcpp", "shiny", "shinyjs",  "survival")
package_new <- package_req[!(package_req %in% installed.packages()[,"Package"])] 
if(length(package_new) > 0) install.packages(package_new)
if (packageVersion("htmlwidgets") < "1.5") install.packages("htmltools")
if (packageVersion("shiny") < "1.4.0") install.packages("shiny")

-- If asked about a "CRAN mirror", choose the nearest location.

-- If asked whether you want to use a "personal library", choose "Yes"

-- If you are on Windows and are asked whether you want to install packages and their dependencies "from source", choose "No" (unless you are ready to go to lunch, in which case, you can select "Yes" and the installation may well be done by the time you get back).

GenEst:

Click on "Tags" under the "Repository" tab on the left sidebar at https://code.usgs.gov/ecosystems/GenEst and then click the link for the specific release you want.

-- For Windows, download the compressed folder GenEst_1.x.x.zip (do not unzip) and note where it is stored. You will install from the local .zip folder.

-- For Mac OS or Unix-like OS, download the compressed file GenEst_1.x.x.tar.gz and note where it is stored. You will install from the local .tar.gz file.

If you are working directly in R (not R Studio), run the following command:

install.packages(file.choose()) # and navigate to the package archive file you just downloaded: GenEst_1.x.x.xxx

If you are working in R Studio:

Click "Install" in the Packages pane.

Select "Package Archive File (.zip; .tar.gz)" as "Install from:" in the dialog box.

Browse to where you saved the zip file, and open it so it appears in the "Package archive" space.

Click the Install button on the dialog box.

Getting Started

Graphical user interface (GUI): easy-to-use buttons and menus

To start the GUI, open R and enter the command:

library(GenEst)
runGenEst()

Download the User Guide from a link near the bottom of the "Help" page in the app or from https://pubs.usgs.gov/tm/7c19/tm7c19.pdf

R command line: more functionality and flexibility

library(GenEst)
browseVignettes("GenEst")
?GenEst

Also, help files for GenEst functions are accessible in the standard R way, for example:

?pkm

Further Reading

GenEst User Guide: https://doi.org/10.3133/tm7C19

GenEst Statistical Models: https://doi.org/10.3133/tm7A2

Functions in GenEst

Name Description
aicc.cpmSet Create the AICc tables for a set of carcass persistence models
averageSS Tabulate an average search schedule from a multi-unit SS data table
dateCols Select the date columns from a data table
aicc.pkmSet Create the AICc tables for a set of searcher efficiency models
app_widgets Create and manage widgets for data input, function execution, data output
aicc.cpm Extract AIC and AICc for a carcass persistence model
cpmSetFail Check if cpm models fail
dateToDay Calculate day of study from calendar date
cpmFail Check if a CP model is well-fit
aicc.cpmSetSize Create the AICc tables for a list of sets of searcher efficiency models
SEsi_left Calculate conditional probability of observation at a search
app_ui_utilities HTML parameters
app_utilities app utilities
SEsi0 Calculate decayed searcher efficiency for a single pk
aicc.pkmSetSize Create the AICc tables for a list of sets of searcher efficiency models
app_download_functions GenEst app download funtions
app_msg_functions GenEst App Messages
checkSpecificModelCP Error check a specific model selection for a CP plot
calcRate Estimate the number of fatalities in each search interval throughout the monitoring period.
aicc.pkm extract AICc value from pkm object
app_server The GenEst server definition function
calcSplits Estimate the number of fatalities by up to two splitting covariates
app_content GenEst Information
cpLogLik Calculate the negative log-likelihood of a carcass persistence model
model_utility_functions model utility functions (not exported)
aicc.pkmSize Create the AICc tables for a list of sets of searcher efficiency models
estM Estimate mortality
estg Estimate all carcass-level detection rates and arrival intervals
countCarcs Count the minimum number of carcasses in the cells
checkComponents Check for model components
app_ui Create the GenEst User Interface HTML
checkSpecificModelSE Error check a specific model selection for an SE plot
combinePreds Combine predictors
SEsi_right Calculate conditional probability of observation after a series of searches
app_output_utilities app utilities for formatting text, tables, figs, etc. for display
calcTsplit Estimate the number of fatalities by time interval
aicc Generic S3 function for summarizing AICc
calcg Calculate detection probability for given SE and CP parameters and search schedule.
app_panels app panel utility functions
SEboxes Produce boxplots p and/or k for all cells for reference model and specific model
cpmSetFailRemove Remove failed cpm models from a cpmSet object
cpmSetSizeFail Check if all of the cpm models fail
expandModelSetCP Expand a CP model set for plotting
combinePredsAcrossModels Combine predictors across models
pkmSetFail Check if pkm models fail
estgGeneric Estimate generic g
estgGenericSize Estimate generic detection probability for multiple carcass classes
cpm Fit cp carcass persistence models
defineUnitCol Auto-parsing to find the name of the unit column (unitCol) If a unit column is not explicitly defined by user in the arg list to estM or estg, then defineUnitCol parses the CO, DWP, and SS files to extract the unit column if possible. Criteria that a column must meet to be a unit column are that it is found in both data_CO and data_DWP, all units in data_CO must also be included among units in data_DWP, all units in both data_CO and data_DWP must be included among the column names in data_SS. If data_DWP = NULL, then the unit column must be included in data_CO and all its units must be included among the column names of data_SS.
pkmSetFailRemove Remove failed pkm models from a pkmSet object
cpmCPCellPlot Plot cell-specific decay curve for carcass persistence
desc Descriptive statistics for a fitted CP model
checkDate Checks whether a vector of data can be interpreted as dates
obsCols_SE Select the columns from a data table that could be SE observations
cpmSetSizeFailRemove Remove failed cpm models from a cpmSetSize object
cpmSetSpecCPCellPlot Plot cell-specific decay curve for carcass persistence
dlModTabSE Create the download version of the Searcher Efficiency model table
obsCols_ltp Select the columns from a data table that could be CP Last Time Present observations
obsCols_fta Select the columns from a data table that could be CP First Time Absent observations
plot.gGeneric Plot results of a single generic ghat estimation
logit Compute the logit or anti-logit
pkmFail Check if a pk model is well-fit
ltranspose Transpose a list of arrays
plot.cpmSet Plot results of a set of CP models
pkmParamPlot Plot parameter box plots for each cell for either p or k
pkm Fit pk searcher efficiency models.
dwpm Fit density-weighted proportion (DWP) models.
pkLogLik Calculate the negative log-likelihood of a searcher efficiency model
plot.estM Plot total mortality estimation
pllogis The CDF of the loglogistic distribution
mock A mock example data set
pkmSECellPlot Plot cell-specific decay curve for searcher efficiency
plotSEBoxTemplate template box plot
pkmSetAllFail Check if all of the pkm models fail within a given set
plot.gGenericSize Plot results of a set of size-based generic ghat estimations
plot.cpm Plot results of a single CP model
plotCPHeader The CP plot header
pkmSetSizeFailRemove Remove failed pkm models from a pkmSetSize object
plotSEBoxPlots p and k box plots for an SE model set
pkmSetSizeFail Check if all of the pkm models fail
plotSECells Plot the cellwise results of a single model in a set of SE models
plot.pkmSet Plot results of a set of SE models
refMod Return the model with the greatest log-likelihood
prettySplitTab Create the pretty version of the split summary table
removeCols Remove selected columns from column names
print.corpus_frame Generic S3 function for printing corpus_frame
runGenEst Launch the GenEst Application
plot.splitFull Plot summary statistics for splits of mortality estimates
pkmSetSpecParamPlot p or k box plots for an SE model set
pkmSetSpecSECellPlot Plot cell-specific decay curve for searcher efficiency for a specific model with comparison to the cellwise model
plotCPFigure Plot results of a single CP model in a set
plot.splitSummary Plot summary statistics for splits of mortality estimates
summary.gGeneric Summarize the gGeneric list to a simple table
plot.pkm Plot results of a single pk model
plotCPCells Plot the cellwise results of a single model in a set of CP models
plotSEFigure Plot results of a single SE model in a set
rpk Simulate parameters from a fitted pk model
plotSEHeader The SE plot header
prepPredictors Prepare predictors based on inputs
summary.gGenericSize Summarize the gGenericSize list to a list of simple tables
prepSS Create search schedule data into an prepSS object for convenient splits analyses
ppersist Calculate the probability of persistence to detection
qpk Quantiles of marginal distributions of \(\hat{p}\) and \(\hat{k}\)
simpleMplot Plot a total mortality estimation for a simple situation
prettyModTabCP Create the pretty version of the Carcass Persistence model table
sizeCols Select the potential carcass class columns from a data table
prettyModTabSE Create the pretty versions of model and summary tables
print.cpm Print a cpm model object
predsCols Select the predictor-ok columns from a data table
rdwp Simulate parameters from a fitted dwp model
readCSV Read in csv files in either format
print.pkm Print a pkm model object
rcp Simulate parameters from a fitted cp model
summary.splitFull Summarize results of mortality estimate splits
tidyModelSetSE Tidy an SE model set
tidyModelSetCP Tidy a CP model set
wind_cleared Wind cleared plot (60m) Search Example
trimSetSize Trim a Model-Set-Size Complex to a Single Model Per Size
update_input Update the inputs when an event occurs
transposeSplits Transpose a splitFull array (preserving attributes)
solar_PV Photovoltaic Example Dataset
solar_trough Trough-based solar thermal power simulated example
summary.estM Summarize total mortality estimation
solar_powerTower Power Tower Example Dataset
update_output Update the outputs when an event occurs
update_rv Update the reactive value list when an event occurs
wind_RP Wind Road and Pad (120m) Example
wind_RPbat Wind Bat-Only Road and Pad (120m) Example
CO_DWP Associate CO carcasses with appropriate DWP values (by unit and carcass class)
SEpanel Produce a single panel in an SE summary/diagnostic plot
GenEst Generalized estimation of mortality
SEcols Produce a named vectory with standard SE plot colors
CPcols Produce a named vector of standard CP plot colors
CPdistOptions Produce the options for the distributions in the CP model
SEfig Plot results of a single SE model in a set
SEsi Calculate decayed searcher efficiency
DWPCols Select the DWP-ok columns from a data table
No Results!

Vignettes of GenEst

Name
GenEstGUI.Rmd
command-line-example.Rmd
solar-examples.Rmd
wind-examples.Rmd
No Results!

Last month downloads

Details

Date 2020-11-21
License CC0
Encoding UTF-8
LazyData true
RoxygenNote 6.1.1
VignetteBuilder knitr
LinkingTo Rcpp
NeedsCompilation yes
Packaged 2020-11-21 21:44:13 UTC; ddalthorp
Repository CRAN
Date/Publication 2020-11-22 00:00:06 UTC

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