Our core expertise includes the following areas of statistics and the broader data science.
Time series analysis in one and multiple dimensions, including forecasting, trend estimation and quantifying forecast uncertainty.
Time series modelling under change (non-stationarity).
Change-point, change and anomaly detection (offline and online).
Predictive analytics, linear and non-linear regression modelling, high-dimensional regressions, time series regressions, regressions with time-varying parameters.
Multivariate analysis.
Dimensionality reduction and variable selection.
Exploratory data analysis and data mining.
Feature engineering, predictive signal construction and testing.
Scenario simulation.
Statistical inference and uncertainty quantification.
Statistical computing in R.
In addition, our broader expertise includes the following areas of data science.
Neural networks and deep learning with Keras.
Tree-based decision making, CART, random forests and associated techniques.
Other methods of supervised learning.
Reinforcement learning.
Causality (causal inference).
We offer consulting services and tailor-made short courses in all of the above areas. See also our past projects page.
These lists are non-exhaustive: please contact us if you require any statistical/data science services even if they are outside these domains, or if you are unsure whether your problem falls within these categories.
We mostly work in R, but are also able to work in Python, Matlab, C/C++ and other languages/environments, if needed.