felipeelorrieta/IAR_Model felipeelorrieta/IAR_Model

  • Stars
    star
    4
  • Rank 3,304,323 (Top 66 %)
  • Language
    Python
  • Created over 6 years ago
  • Updated over 5 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
felipeelorrieta/IAR_Model
github

felipeelorrieta

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

This folder contains R and Python functions to fit unequally spaced time series from the Irregular Autoregressive (IAR). From the functions of this folder we can generate observations for each process, compute the negative of the log likelihood of these process, fit each model to irregularly sampled data, and test the significance of the estimated parameters.

More Repositories

1

iAR

Python
3
star
2

iAR-package

Data sets, functions and scripts with examples to implement autoregressive models for irregularly observed time series. The models available in this package are the irregular autoregressive model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>), the complex irregular autoregressive model (Elorrieta et al.(2019) <doi:10.1051/0004-6361/201935560>) and the bivariate irregular autoregressive model.
2
star
3

CIAR_Model

This folder contains Python functions to fit unequally spaced time series from the Complex Irregular Autoregressive Model (CIAR model). From the functions of this folder we can generate observations for each process, compute the negative of the log likelihood of these process, fit each model to irregularly sampled data, and test the significance of the estimated parameters.
Jupyter Notebook
2
star
4

AITSPackage-R

This package contains a set of R functions and datasets to perform both the Irregular Autoregressive Model (IAR model) and the Complex Irregular Autoregressive Model (CIAR model) which are useful for unequally spaced time series.
1
star