# Inference for Change-Point and Related Processes

Created: | 2014-01-02 10:05 |
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Institution: | Isaac Newton Institute for Mathematical Sciences |

Description: | In many applications data is collected over time or can be ordered with respect to some other criteria (e.g. position along a chromosome). Often the statistical properties, such as mean or variance, of the data will change along data. This feature of data is known as non-stationarity. An important and challenging problem is to be able to model and infer how these properties change. Examples occur in environmental applications (e.g. detecting changes in ecological systems due to climatic conditions crossing some critical thresholds), signal processing (e.g. structural analysis of EEG signals), epidemiology (e.g. early detection of hospital infections from changes in patient’s antibody levels), bioinformatics (e.g. detecting changes in copy number variation), and finance (e.g. changing volatility). As technology advances, and ever larger and complex data are collected, the need to model changes in the statistical properties of the data, and the difficulty of making inference for these models increases.
Read more at www.newton.ac.uk/programmes/ICP/ |

# Media items

This collection contains 49 media items.

### Media items

#### A primal dual method for inverse problems in MRI with non-linear forward operators

Valkonen, T (University of Cambridge)

Friday 07 February 2014, 14:30-15:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 14 Feb 2014

#### Adaptive Spectral Estimation for Nonstationary Time Series

Stoffer, D (University of Pittsburgh)

Friday 17 January 2014, 11:30-12:15

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 24 Jan 2014

#### An algorithm to segment count data using a binomial negative model

Rigaill, G (INRA-CNRS-Université d'Evry Val d'Essonne, URGV)

Thursday 16 January 2014, 10:00-10:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 24 Jan 2014

#### An Automated Statistician which learns Bayesian nonparametric models of time series data

Ghahramani, Z (University of Cambridge)

Thursday 16 January 2014, 14:15-15:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 24 Jan 2014

#### Analysis of time series observed on networks

Nunes, M (Lancaster University)

Wednesday 15 January 2014, 09:30-10:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 22 Jan 2014

#### Applications of Change-Points Methods in Brain Signal and Image Analysis

Ombao, H (University of California, Irvine)

Wednesday 05 February 2014, 11:30-12:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 12 Feb 2014

#### Bayesian inference in continuous time jump processes

Godsill, S (University of Cambridge)

Thursday 16 January 2014, 13:30-14:15

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 24 Jan 2014

#### Change-point detection and analysis

Siegmund, D (Stanford University)

Monday 13 January 2014, 14:00-15:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 15 Jan 2014

#### Change-point tests based on estimating functions

Kirch, C (Karlsruhe Institute of Technology)

Wednesday 15 January 2014, 13:30-14:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 22 Jan 2014

#### Characterizing, predicting and handling rapid and large changes of wind power production.

Girard, R (Mines Paris Tech)

Monday 27 January 2014, 15:10-16:10

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 28 Jan 2014

#### Computationally Efficient Algorithms for Detecting Changepoints

Fearnhead, P (Lancaster University)

Thursday 16 January 2014, 09:30-10:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 24 Jan 2014

#### Decentralized Quickest Change Detection in Hidden Markov Models for Sensor Networks

Fuh, C-D (National Central University, Taiwan)

Wednesday 15 January 2014, 10:00-10:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 22 Jan 2014

#### Detecting copy number variants for rare genetic disorders and non-invasive pre-natal diagnosis

Plagnol, V (University College London)

Tuesday 04 February 2014, 11:30-12:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 12 Feb 2014

#### Detecting smooth changes in locally stationary processes

Vogt, M (University of Konstanz)

Tuesday 14 January 2014, 09:30-10:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 22 Jan 2014

#### Detection and Exploitation of Nonstationarities in Time Series Data

Nason, G (University of Bristol)

Monday 13 January 2014, 15:30-16:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 15 Jan 2014

#### Detection of Genomic Signals by Resequencing

Siegmund, D (Stanford University)

Monday 03 February 2014, 11:30-12:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 11 Feb 2014

#### Detection of multiple structural breaks in multivariate time series

Dette, H (Ruhr-Universität Bochum)

Tuesday 14 January 2014, 14:50-15:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 22 Jan 2014

#### Exact Bayesian inference for change point models with application to genomics

Robin, S (INRA - Institut National de la Recherche Agronomique)

Monday 03 February 2014, 14:00-15:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 12 Feb 2014

#### Fourier based statistics for irregular spaced spatial data: with an application to testing for spatial stationarity.

Subba Rao , S (Texas A&M University )

Friday 24 January 2014, 14:00-15:00

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 3 Feb 2014

#### Graph-Based Change-Point Detection

Chen, H (University of California, Davis)

Tuesday 21 January 2014, 11:30-12:30

**Collection**:
Inference for Change-Point and Related Processes

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 3 Feb 2014