Individual based models using R (and netlogo) (IBMS01)
1 April 2019 - 5 April 2019£275.00 - £510
This workshop will provide attendees with the opportunity to learn how (1) to understand; (2) run simulations of readily available Individual Based Models (IBMs); (3) analyze the outputs of IBMs; (4) parameterize IBMs, and (5) code relatively basic IBMs in R and NetLogo.
Examples and applications will include cases from diverse domains and scientific disciplines such as social sciences, biology, and environmental sciences.
This workshop is ideal for any scientists seeking an introduction as well as functional use in terms of parameterizing, simulating, and analyzing outputs of IBMs; some moderate skills of programming and own coding will also be acquired.
This course will suite attendees from a diverse range of scientific disciplines such as biology, ecology, psychology, economics, or education. No prior knowledge of programming in R or Netlogo are required. However basic to moderate prior R knowledge is required (loading data, loading R packages, basic R environment and basic R commands).
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday evening, farewell dinner Thursday evening, refreshments and accommodation. Self-catering facilities are available in the accommodation. Accommodation is approximately a 6-minute walk from the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 31st March (after 5pm) and departure Friday 5th April (accommodation must be vacated by 9:15am).
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PRstatistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PRstatistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Dr Aristides (Aris) Moustakas
There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge
A basic understanding of statistical concepts. Specifically, generalised linear regression models, statistical significance, hypothesis testing.
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links.
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) internet access may not always be available.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at 43 Cook Street, Glasgow, G5 8JN at approx. 17:00 onwards
Monday `1st – Classes from 09:30 to 17:30
Differences between statistical modelling and process-based predictive models
Introduction to cellular automata
Introduction to Individual & Agent Based Models
Running simulations with readily coded IBMs in Netlogo
Application of cellular automata: coding the game of life in R
Tuesday 2nd – Classes from 09:30 to 17:30
Introduction to scientific programming
Introduction to Netlogo
Go through a coded IBM in NetLogo and understand the code
Code IBMs in R (full code provided and explained)
Run simulations of the IBM
Wednesday 3rd – Classes from 09:30 to 17:30
Complex vs. simple models
How many processes & details to include
Combining IBMs with statistical analysis
Running simple vs more complex coded IBMs
Exporting outputs from IBMs
Statistical analysis of IBM outputs
Thursday 4th – Classes from 09:00 to 17:00
Sensitivity of input parameters
Coding IBMs in R
Analyzing IBM outputs of varying parameter inputs
Friday 5th – Classes from 09:30 to 16:00
Examples of IBMs across disciplines
IBMs providing new insights & groundbreaking results
Understanding the description, replicating and coding a journal-published IBM
Discussions with the tutor and the group of own IBMs and coding
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)