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Wiley Interdisciplinary Reviews:
WIREs Computational Statistics
Volume 13 Issue 3 (May 2021)
Page 0 - 0


An introduction to persistent homology for time series
Published Online: Feb 04 2021
DOI: 10.1002/wics.1548
Simulated time series, point clouds, and persistence diagrams. Constructed using the R package TDA.
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Advanced Reviews

Data analysis on nonstandard spaces
Published Online: Sep 08 2020
DOI: 10.1002/wics.1526
Surveying many non‐Euclidean statistical problems with ingenious solutions, we uncover new ones, keeping mathematicians, statisticians, computer and data scientists busy for a while.
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A review study of functional autoregressive models with application to energy forecasting
Published Online: Jul 28 2020
DOI: 10.1002/wics.1525
In this data‐rich era, it is essential to develop advanced techniques to analyze and understand large amounts of data and extract the underlying information in a flexible way. We provide a review study on the state‐of‐the‐art statistical time series models for univariate and multivariate functional data with serial dependence. In particular, we review functional autoregressive (FAR) models and their variations dealing with different scenarios including multivariate functional series, high‐dimensionality, seasonal variations, nonstationarity and causal relation to exogenous variables. We discuss the models' applicability and conduct out‐of‐sample forecasts using real‐world data of high‐resolution natural gas flows in the high‐pressure gas pipeline network of Germany.
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Advance of the sufficient dimension reduction
Published Online: Jun 03 2020
DOI: 10.1002/wics.1516
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Focus Article

Sampling James R. Thompson's inspired nonparametric portfolio approaches
Published Online: Dec 22 2020
DOI: 10.1002/wics.1542
Jim Thompson was a pioneer in nonparametric quantitative finance. This paper samples his contributions in this area. We review his ground breaking exploration of the veracity of the CAPM, and several nonparametric approaches to portfolio formulation including the SimugramTM, variants of his Max‐Median rule, and Tukey weightings.
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