Concept

Statistiques non paramétriques

Cours associés (21)

CIVIL-226: Introduction to machine learning for engineers

Machine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinki

MATH-524: Nonparametric estimation and inference

Nonparametric models are used to identify nonlinear relationships within data. This course gives a graduate-level overview of nonparametric statistical estimation and inference theory.

MATH-449: Biostatistics

This course covers statistical methods that are widely used in medicine and biology. A key topic is the analysis of longitudinal data: that is, methods to evaluate exposures, effects and outcomes that

EE-209: Elements of statistics for data science

MATH-342: Time series

A first course in statistical time series analysis and applications.

MATH-665: Functional Data Analysis

A rigorous introduction to the statistical analysis of random functions and associated random operators. Viewing random functions either as random Hilbert vectors or as stochastic processes, we will s

EE-607: Advanced Methods for Model Identification

This course introduces the principles of model identification for non-linear dynamic systems, and provides a set of possible solution methods that are thoroughly characterized in terms of modelling as

MATH-516: Applied statistics

The course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use comput

FIN-619: Financial Econometrics and Machine Learning

This course consists of three parts: an introduction to financial time series data characteristics and analysis, a discussion on econometrics techniques (eg, GARCH models, cointegration, extreme value

FIN-525: Financial big data

The course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to fi

MATH-341: Linear models

Regression modelling is a fundamental tool of statistics, because it describes how the law of a random variable of interest may depend on other variables. This course aims to familiarize students with

COM-500: Statistical signal and data processing through applications

Building up on the basic concepts of sampling, filtering and Fourier transforms, we address stochastic modeling, spectral analysis, estimation and prediction, classification, and adaptive filtering, w

AR-219: Advanced CAO and Integrated Modeling DIM

1ère année: bases nécessaires à la représentation informatique 2D (3D). Passage d'un à plusieurs logiciels: compétence de choisir les outils adéquats en 2D et en 3D. Mise en relation des outils de CAO

EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees

CS-401: Applied data analysis

This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the dat

MATH-655: Advanced methods for causal inference

This course covers recent methodology for causal inference in settings with time-varying exposures (longitudinal data) and causally connected units (interference). We will consider theory for identifi

FIN-474: Advanced risk management topics

The students learn different financial risk measures and their risk theoretical properties. They learn how to design and implement risk engines, with model estimation, forecast, reporting and validati

MATH-441: Robust and nonparametric statistics

In the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a th

ENV-400: Air pollution and climate change

A survey course describing the origins of air pollution and climate change

MATH-685: Learning Theory of Nonparametric Regression

This course is intended to give a brief overview of how to prove consistency results in nonparametric regression. In particular, we will focus on least-square regression estimators. Some connections t