421 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University College LondonGB63 papers
- Systemic Risk CentreGB48 papers
- University of OxfordGB20 papers
- University of WarwickGB18 papers
- King's College LondonGB16 papers
- London Mathematical LaboratoryGB12 papers
- University of Illinois Urbana-ChampaignUS12 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- Queen Mary University of LondonGB11 papers
- The Open UniversityGB11 papers
- City, University of LondonGB10 papers
- ETH ZurichCH10 papers
52 papers · 1 filter
Maximum softly penalised likelihood in factor analysis
Philipp Sterzinger, Ioannis Kosmids, Irini Moustaki
Estimation in exploratory factor analysis often yields estimates on the boundary of the parameter space. Such occurrences, known as Heywood cases, are characterised by non-positive…
On a fast consistent selection of nested models with possibly unnormalized probability densities
Rong Bian, Kung-Sik Chan, Bing Cheng +1
Models with unnormalized probability density functions are ubiquitous in statistics, artificial intelligence and many other fields. However, they face significant challenges in mod…
Multiscale Autoregression on Adaptively Detected Timescales
Rafal Baranowski, Yining Chen, Piotr Fryzlewicz
We propose a multiscale approach to time series autoregression, in which linear regressors for the process in question include features of its own path that live on multiple timesc…
Exact Exploratory Bi-factor Analysis: A Constraint-based Optimisation Approach
Jiawei Qiao, Yunxiao Chen, Zhiliang Ying
Bi-factor analysis is a form of confirmatory factor analysis widely used in psychological and educational measurement. The use of a bi-factor model requires the specification of an…
Pairwise likelihood estimation and limited information goodness-of-fit test statistics for binary factor analysis models under complex survey sampling
Haziq Jamil, Irini Moustaki, Chris Skinner
This paper discusses estimation and limited information goodness-of-fit test statistics in factor models for binary data using pairwise likelihood estimation and sampling weights.…
When Composite Likelihood Meets Stochastic Approximation
Giuseppe Alfonzetti, Ruggero Bellio, Yunxiao Chen +1
A composite likelihood is an inference function derived by multiplying a set of likelihood components. This approach provides a flexible framework for drawing inference when the li…
A Note on Ising Network Analysis with Missing Data
Siliang Zhang, Yunxiao Chen
The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelih…
DIF Analysis with Unknown Groups and Anchor Items
Gabriel Wallin, Yunxiao Chen, Irini Moustaki
Ensuring fairness in instruments like survey questionnaires or educational tests is crucial. One way to address this is by a Differential Item Functioning (DIF) analysis, which exa…
A two-step estimator for multilevel latent class analysis with covariates
Roberto Di Mari, Zsuzsa Bakk, Jennifer Oser +1
We propose a two-step estimator for multilevel latent class analysis (LCA) with covariates. The measurement model for observed items is estimated in its first step, and in the seco…
Optimal Parallel Sequential Change Detection under Generalized Performance Measures
Zexian Lu, Yunxiao Chen, Xiaoou Li
This paper considers the detection of change points in parallel data streams, a problem widely encountered when analyzing large-scale real-time streaming data. Each stream may have…
Modelling matrix time series via a tensor CP-decomposition
Jinyuan Chang, Jing He, Lin Yang +1
We consider to model matrix time series based on a tensor CP-decomposition. Instead of using an iterative algorithm which is the standard practice for estimating CP-decompositions,…
An Online Sequential Test for Qualitative Treatment Effects
Chengchun Shi, Shikai Luo, Hongtu Zhu +1
Tech companies (e.g., Google or Facebook) often use randomized online experiments and/or A/B testing primarily based on the average treatment effects to compare their new product w…
Jump Interval-Learning for Individualized Decision Making
Hengrui Cai, Chengchun Shi, Rui Song +1
An individualized decision rule (IDR) is a decision function that assigns each individual a given treatment based on his/her observed characteristics. Most of the existing works in…
DIF Statistical Inference without Knowing Anchoring Items
Yunxiao Chen, Chengcheng Li, Jing Ouyang +1
Establishing the invariance property of an instrument is a key step for establishing its measurement validity. Measurement invariance is typically assessed by differential item fun…
Nonparametric, tuning-free estimation of S-shaped functions
Oliver Y. Feng, Yining Chen, Qiyang Han +2
We consider the nonparametric estimation of an S-shaped regression function. The least squares estimator provides a very natural, tuning-free approach, but results in a non-convex…
Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces
Xueqin Wang, Jin Zhu, Wenliang Pan +2
Distribution function is essential in statistical inference, and connected with samples to form a directed closed loop by the correspondence theorem in measure theory and the Glive…
Latent variable models for multivariate dyadic data with zero inflation: Analysis of intergenerational exchanges of family support
Jouni Kuha, Siliang Zhang, Fiona Steele
Understanding the help and support that is exchanged between family members of different generations is of increasing importance, with research questions in sociology and social po…
An Automatic Finite-Sample Robustness Metric: When Can Dropping a Little Data Make a Big Difference?
Tamara Broderick, Ryan Giordano, Rachael Meager
Study samples often differ from the target populations of inference and policy decisions in non-random ways. Researchers typically believe that such departures from random sampling…
Unfolding-Model-Based Visualization: Theory, Method and Applications
Yunxiao Chen, Zhiliang Ying, Haoran Zhang
Multidimensional unfolding methods are widely used for visualizing item response data. Such methods project respondents and items simultaneously onto a low-dimensional Euclidian sp…
Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
Xiuqin Xu, Ying Chen, Yannig Goude +1
Probabilistic forecasting of electricity load curves is of fundamental importance for effective scheduling and decision making in the increasingly volatile and competitive energy m…
Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework
Siliang Zhang, Yunxiao Chen
Latent variable models have been playing a central role in psychometrics and related fields. In many modern applications, the inference based on latent variable models involves one…
Testing for unit roots based on sample autocovariances
Jinyuan Chang, Guanghui Cheng, Qiwei Yao
We propose a new unit-root test for a stationary null hypothesis against a unit-root alternative . Our approach is nonparametric as only assumes that the process c…
A Note on Exploratory Item Factor Analysis by Singular Value Decomposition
Haoran Zhang, Yunxiao Chen, Xiaoou Li
We revisit a singular value decomposition (SVD) algorithm given in Chen et al. (2019b) for exploratory Item Factor Analysis (IFA). This algorithm estimates a multidimensional IFA m…
Detecting linear trend changes in data sequences
Hyeyoung Maeng, Piotr Fryzlewicz
We propose TrendSegment, a methodology for detecting multiple change-points corresponding to linear trend changes in one dimensional data. A core ingredient of TrendSegment is a ne…