Software

twdlstm

Python (PyTorch) code for a non-auto-regressive long short-term memory (LSTM) neural network model adapted to predict tree water deficit at arbitrary locations and time points from time series with sparse observations in space-time. Includes training, test, predictions, and cross-validation scripts.

routmod

R code for setting up and fitting the spatio-temporal routing module to improve river discharge predictions along a river network, supplementary material to Aeberhard et al. (2025)

manateessm

R code for fitting the manatee counts state space model, supplementary material to Scolardi, Wilkinson, and Aeberhard (2025)

EagleRayGrowth

R code for estimating the von Bertalanffy growth parameters from mark-recapture data, as well as comparing two populations (e.g. wild and aquarium) in terms of their growth parameters, supplementary material to Boggio-Pasqua, Bassos-Hull, Aeberhard, Hoopes, Swider, Wilkinson, and Dureuil (2022)

GrowthEstimation

R code for various estimation methods of von Bertalanffy growth parameters, supplementary material to Dureuil, Aeberhard, Dowd, Pardo, Whoriskey, and Worm (2022)

RobSSM

R code for robust estimation for state space models, supplementary material to Aeberhard, Cantoni, Field, Kuensch, Mills Flemming and Xu (2021)

spglmetm

R package for fitting of semi-parametric generalized linear models based on exponentially tilted mixtures

SSM-SeaScallops

R code for simulating and fitting the alternative state space model of Yin, Aeberhard, Smith and Mills Flemming (2019)

trNB

Fully-documented R package for truncated negative binomial and truncated Poisson family objects

robNB

Fully-documented R package for robust estimation and accurate inference for the negative binomial model, implementing the methods presented in Aeberhard, Cantoni and Heritier (2017)

glmrob.nb

R code for fitting a robust negative binomial generalized linear model, supplementary material to Aeberhard, Cantoni and Heritier (2014)