lukestrickland Goto Github PK

ari

Data analysis and cognitive modelling of an Anticipatory Response Inhibition task.

atc_xml_generator

Creates XML scripts for ATC-LAB advanced

auto_failures_analysis

Applying the linear ballistic accumulator model to understand how automated decision aids affect air traffic control conflict detection

automation_lba

An experiment applying the LBA model to understand human adaptation to automation

bandit_simple

Modifications to Akhil's feature bandit xxxxxx to make a simpler 'standard' multi-armed bandit

dmc

My personal (modified) copy of the dynamic models of choice software (DMC). DMC available at https://osf.io/pbwx8/

fips

The Fatigue Impairment Prediction Suite (for R)

flex

A responsive, flexible, Jekyll theme based on The Development's first design.

ggdmc

Dynamic Models of Choice with Better Graphic Tools

ggpmdc

testing software for bayesian parameter estimation of the 'PMDC' model (Strickland et al., 2018) using the 'ggDMC' software (https://github.com/yxlin/ggdmc). PMDC is very computationally demanding, and ggDMC is relatively efficient Bayesian sampling software, so the two are a perfect fit.

lba_recovery

Testing recovery of the LBA model

lukestrickland.github.io

mcmseer

multi_target_pm

neuromllite

Work towards creating a common JSON based format for compact network specification

pm_ongoingtask_bias

Data analysis for an experiment examining how ongoing task threshold biases affect prospective memory performance.

pmcost_inddiffs

Work with Brett Hunter Ball and Gene Brewer on understanding the latent variables underlying individual differences in PM cost. Original paper with ex-Gaussian analyses available at https://www.researchgate.net/publication/320216101_Proactive_Control_Processes_in_Event-Based_Prospective_Memory_Evidence_From_Intraindividual_Variability_and_Ex-Gaussian_Analyses

pmdc

reliability_analysis

target_learning

A study examining target learning in event-based prospective memory

workload_modelling

Exploring extensions of sleep modelling that incorporate workload