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Bayesian Model to Estimate Population Trends from Counts Series
Infers the trends of one or several animal populations over time from series of counts. It does so by accounting for count precision (provided or inferred based on expert knowledge, e.g. guesstimates), smoothing the population rate of increase over time, and accounting for the maximum demographic potential of species. Inference is carried out in a Bayesian framework. This work is part of the FRB-CESAB working group AfroBioDrivers < https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/afrobiodrivers/>.
Fast Network Modularity and Roles Computation by Simulated Annealing (Rgraph C Library Wrapper for R)
Provides functions to compute the modularity and modularity-related roles in networks. It is a wrapper around the rgraph library (Guimera & Amaral, 2005,
Spatial Data Download and Utility Functions
A suite of conversion functions to create internally standardized spatial polygons data frames. Utility functions use these data sets to return values such as country, state, time zone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.)
Google Analytics API into R
Interact with the Google Analytics APIs < https://developers.google.com/analytics/>, including the Core Reporting API (v3 and v4), Management API, User Activity API GA4's Data API and Admin API and Multi-Channel Funnel API.
Improved Methods for Constructing Prediction Intervals for Network Meta-Analysis
Improved methods to construct prediction intervals for network meta-analysis. The parametric bootstrap and Kenward-Roger-type adjustment by Noma et al. (2022)
Dose Rate Modelling of Carbonate-Rich Samples
Translation of the 'MATLAB' program 'Carb' (Nathan and Mauz 2008
Highlight Conserved Edits Across Versions of a Document
Input multiple versions of a source document, and receive HTML code for a highlighted version of the source document indicating the frequency of occurrence of phrases in the different versions. This method is described in Chapter 3 of Rogers (2024) < https://digitalcommons.unl.edu/dissertations/AAI31240449/>.
Power and Sample Size for Health Researchers via Shiny
Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, regression coefficients (linear, logistic, gamma, and Cox), linear mixed model, Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease. You can also use the online version at < https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/>.
Koeppen-Geiger Climatic Zones
Aids in identifying the Koeppen-Geiger (KG) climatic zone for
a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system
to classify regions of the earth by their relative heat and humidity through the year, for
the benefit of human health, plant and agriculture and other human activity [1]. This climate
zone classification system, applicable to all of the earths surface, has continued to be
developed by scientists up to the present day. Recently one of use (FZ) has published updated,
higher accuracy KG climate zone definitions [2]. In this package we use these updated
high-resolution maps as the data source [3]. We provide functions that return the KG climate zone
for a given longitude and lattitude, or for a given United States zip code. In addition
the CZUncertainty() function will check climate zones nearby to check if the given location
is near a climate zone boundary. In addition an interactive shiny app is provided to define
the KG climate zone for a given longitude and lattitude, or United States zip code.
Digital data, as well as animated maps, showing the shift of the climate zones are provided
on the following website < http://koeppen-geiger.vu-wien.ac.at>.
This work was supported by the DOE-EERE SunShot award DE-EE-0007140.
[1] W. Koeppen, (2011)
Large Amplitude Oscillatory Shear (LAOS)
The Sequence of Physical Processes (SPP) framework is a way of interpreting the transient data derived from oscillatory rheological tests. It is designed to allow both the linear and non-linear deformation regimes to be understood within a single unified framework. This code provides a convenient way to determine the SPP framework metrics for a given sample of oscillatory data. It will produce a text file containing the SPP metrics, which the user can then plot using their software of choice. It can also produce a second text file with additional derived data (components of tangent, normal, and binormal vectors), as well as pre-plotted figures if so desired. It is the R version of the Package SPP by Simon Rogers Group for Soft Matter (Simon A. Rogers, Brian M. Erwin, Dimitris Vlassopoulos, Michel Cloitre (2011)