Posts by categories

Code (14) Etc (11) Talks (8)

Code

August 30, 2018 — Fitting removal models with the detect R package
March 08, 2018 — Shiny slider examples with the intrval R package
February 09, 2018 — Phylogeny and species traits predict bird detectability
January 23, 2018 — The progress bar just got a lot cheaper
January 26, 2017 — What is new in the intrval R package?
December 02, 2016 — Relational operators for intervals with the intrval R package
November 26, 2016 — How to write and document %special% functions in R
October 15, 2016 — Progress bar overhead comparisons
September 16, 2016 — How to add pbapply to R packages
September 11, 2016 — What is the cost of a progress bar in R?
August 23, 2016 — Trends in daily R package downloads
March 14, 2016 — wac2wav converter
March 04, 2016 — Timer progress bar added to pbapply package
March 02, 2016 — mefa4 R package update

Etc

June 22, 2020 — How many birds are out there?
February 06, 2018 — PVA: Publication Viability Analysis, round 3
November 05, 2016 — Effects of industrial sectors on species abundance in Alberta
August 30, 2016 — My first blog post was a guest post
June 14, 2016 — Data set with all the conceivable errors
February 27, 2016 — Personal website revamped
February 25, 2016 — Hierarchical models for conservation biologists made easy
October 20, 2015 — Version 3 of the ABMI Species Website released
August 28, 2015 — Hierarchical modeling workshop in Monpellier
May 05, 2015 — Cumulative effects of Oil Sands development on songbirds
December 20, 2014 — ABMI Species Website launched

Talks

April 19, 2026 — Analyzing Ecological Data with Detection Error
April 11, 2023 — CalgaryR & YEGRUG Meetup: Data Cloning - Hierarchical Models Made Easy
July 18, 2016 — NACCB 2016 talk on cumulative effects monitoring
August 04, 2015 — What can we do with a single survey?
February 17, 2015 — Human footprint change during the last decade
July 16, 2014 — Budapest Use R!
July 01, 2014 — ISEC 2014 in Montpellier
May 05, 2014 — Bird modeling in the Oil Sands

Closing the gap between data and decision making

Analyzing Ecological Data with Detection Error

This course is for researchers who analyze field observations. These data are often inconsistent because sampling protocols can change across projects, over time, or when older data are combined with new recordings.

ABMI (7) ARU (1) Alberta (1) BAM (1) C (1) CRAN (1) Hungary (2) JOSM (2) MCMC (2) PVA (2) PVAClone (1) QPAD (3) R (21) R packages (1) abundance (1) bioacoustics (1) biodiversity (1) birds (2) course (2) data (1) data cloning (4) datacloning (1) dclone (3) density (1) dependencies (1) detect (3) detectability (4) footprint (3) forecasting (1) functions (3) intrval (4) lhreg (1) mefa4 (1) monitoring (2) pbapply (5) phylogeny (1) plyr (1) poster (2) processing time (2) progress bar (4) publications (2) report (1) sector effects (1) shiny (1) single visit (1) site (1) slider (1) slides (2) special (3) species (1) trend (1) tutorials (2) video (4) workshop (2)