Filter Results
16 results
Julia Code to aid reproducibility for the paper: Malliavin-Mancino estimators implemented with the non-uniform fast Fourier transform. DOI for the Dataset: 10.25375/uct.11903442
Data Types:
  • Software/Code
The R code explores the calibration and simulation of the Farmer and Joshi (2002) agent-based model of financial markets using the method of moments along with a genetic algorithm and a Nelder-Mead with threshold accepting algorithm. The model is used for understanding daily trading decisions made from closing auction to closing auction in equity markets, as it attempts to model financial market behaviour without the inclusion of agent adaptation. However, our attempt at calibrating the model has limited success in replicating important stylized facts observed in financial markets, similar to what has been found in other calibration experiments of the model. This leads us to extend the Farmer-Joshi model to include agent adaptation using a Brock-Hommes (1998) approach to strategy fitness based on trading strategy profitability. The adaptive Farmer-Joshi model allows trading agents to switch between strategies, favouring strategies that have been more profitable over some period of time determined by a free-parameter determining the profit monitoring time-horizon.
Data Types:
  • Software/Code
Julia Code to aid reproducibility for the paper: Malliavin-Mancino estimators implemented with the non-uniform fast Fourier transform. DOI for the Dataset: 10.25375/uct.11903442
Data Types:
  • Software/Code
The R code explores the calibration and simulation of the Farmer and Joshi (2002) agent-based model of financial markets using the method of moments along with a genetic algorithm and a Nelder-Mead with threshold accepting algorithm. The model is used for understanding daily trading decisions made from closing auction to closing auction in equity markets, as it attempts to model financial market behaviour without the inclusion of agent adaptation. However, our attempt at calibrating the model has limited success in replicating important stylized facts observed in financial markets, similar to what has been found in other calibration experiments of the model. This leads us to extend the Farmer-Joshi model to include agent adaptation using a Brock-Hommes (1998) approach to strategy fitness based on trading strategy profitability. The adaptive Farmer-Joshi model allows trading agents to switch between strategies, favouring strategies that have been more profitable over some period of time determined by a free-parameter determining the profit monitoring time-horizon.
Data Types:
  • Software/Code
Code for paper for vaccine comparison study. This is linked to new releases from Github, unlike the other VaccComp item.
Data Types:
  • Software/Code
This fileset contains Data and R code for : Jansen et al. 2019. Survival synchronicity in two avian insectivore communities. published in the International Journal of Avian Science Ibis." This set of files contains the capture-mark-recapture data and R / WinBUGS code to run some of the analyses presented in the publication. Koeberg and Darvill are the two study sites from which the data as collected. The Koeberg data was collected by Penn Lloyd and the Darvill data is a SAFRING data set.
Data Types:
  • Software/Code
Code for paper for vaccine comparison study. This is linked to new releases from Github, unlike the other VaccComp item.
Data Types:
  • Software/Code
Bootstrapped confidence intervals in ggplot2. Still in development.
Data Types:
  • Software/Code
This code is an R package bundle that contains the functions to generate the figures in the paper 'A comparison of antigen-specific T cell responses induced by six novel tuberculosis vaccine candidates'.The functions automatically generate bootstrap-based univariate confidence intervals and bivariate confidence areas and plots them in ggplot2. Has much wider scope than this study’s application.An updated version (not necessarily compatible with the package VaccComp) is available on Github at MiguelRodo/ggboot.
Data Types:
  • Software/Code
Raw data and processing code for vaccine comparison study. This is linked to GIthub to update with new releases, should any be made available.
Data Types:
  • Software/Code