Other packages > Find by keyword >

biosurvey  

Tools for Biological Survey Planning
View on CRAN: Click here


Download and install biosurvey package within the R console
Install from CRAN:
install.packages("biosurvey")

Install from Github:
library("remotes")
install_github("cran/biosurvey")

Install by package version:
library("remotes")
install_version("biosurvey", "0.1.1")



Attach the package and use:
library("biosurvey")
Maintained by
Claudia Nuez-Penichet
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-14
Latest Update:
Description:
A collection of tools that allows users to plan systems of sampling sites, increasing the efficiency of biodiversity monitoring by considering the relationship between environmental and geographic conditions in a region. The options for selecting sampling sites included here differ from other implementations in that they consider the environmental and geographic conditions of a region to suggest sampling sites that could increase the efficiency of efforts dedicated to monitoring biodiversity. The methods proposed here are new in the sense that they combine various criteria and points previously made in related literature; some of the theoretical and methodological bases considered are described in: Arita et al. (2011) , Sober
How to cite:
Claudia Nuez-Penichet (2021). biosurvey: Tools for Biological Survey Planning. R package version 0.1.1, https://cran.r-project.org/web/packages/biosurvey. Accessed 23 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:22), 0.1.0 (2021-09-14 09:10), 0.1.1 (2021-09-15 23:10)
Other packages that cited biosurvey R package
View biosurvey citation profile
Other R packages that biosurvey depends, imports, suggests or enhances
Functions, R codes and Examples using the biosurvey R package
Some associated functions: DI_dendrogram . EG_selection . PAM_CS . PAM_from_table . PAM_indices . PAM_subset . assign_blocks . b_pam . base_PAM . biosurvey . block_sample . closest_to_centroid . compare_SAC . dis_loop . dist_list . distance_filter . explore_data_EG . files_2data . find_clusters . find_modes . grid_from_region . legend_bar . m_matrix . m_matrix_pre . m_selection . make_blocks . master_matrix . master_selection . match_rformat . mx . plot_DI . plot_PAM_CS . plot_PAM_geo . plot_SAC . plot_blocks_EG . plot_sites_EG . point_sample . point_sample_cluster . point_thinning . prepare_PAM_CS . prepare_base_PAM . prepare_master_matrix . preselected . preselected_dist_mask . print . purplow . random_selection . refill_PAM_indices . rlist_2data . selected_sites_DI . selected_sites_PAM . selected_sites_SAC . sp_data . sp_layers . sp_occurrences . spdf_2data . species_data . stack_2data . subset_PAM . summary . uniformE_selection . uniformG_selection . unimodal_test . variables . wgs84_2aed_laea . 
Some associated R codes: Classes.R . DI_plot_helpers.R . EG_selection.R . Methods.R . PAM_indices.R . base_pam.R . biosurvey.R . block_sample.R . color_palettes.R . compare_SAC.R . data_documentation.R . explore_data_EG.R . globals.R . make_blocks.R . master_matrix.R . pam_helpers.R . plot_PAM_CS.R . plot_PAM_geo.R . plot_SAC.R . plot_blocks_EG.R . plot_sites_EG.R . prepare_PAM_CS.R . preselected_dist_mask.R . random_selection.R . reduce_pam.R . selected_sites_DI.R . selected_sites_SAC.R . selectionEG_helpers.R . selection_helpers.R . short_helpers.R . uniformE_selection.R . uniformG_selection.R .  Full biosurvey package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
fitscape  
Classes for Fitness Landscapes and Seascapes
Convenient classes to model fitness landscapes and fitness seascapes. A low-level package with whic ...
Download / Learn more Package Citations See dependency  
gfcanalysis  
Tools for Working with Hansen et al. Global Forest Change Dataset
Supports analyses using the Global Forest Change dataset released by Hansen et al. gfcanalysis was ...
Download / Learn more Package Citations See dependency  
MixSIAR  
Bayesian Mixing Models in R
Creates and runs Bayesian mixing models to analyze biological tracer data (i.e. stable isotopes, fa ...
Download / Learn more Package Citations See dependency  
ODS  
Statistical Methods for Outcome-Dependent Sampling Designs
Outcome-dependent sampling (ODS) schemes are cost-effective ways to enhance study efficiency. In OD ...
Download / Learn more Package Citations See dependency  

27,889

R Packages

239,283

Dependencies

74,019

Author Associations

27,890

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA