Results 191 to 200 of about 63,609 (288)

Identifying and Mapping Industrial Districts Through a Spatially Constrained Cluster‐Wise Regression Approach

open access: yesJournal of Regional Science, Volume 65, Issue 2, Page 403-428, March 2025.
ABSTRACT The aim of this article is to exploit an innovative spatial econometric approach to map and study the evolving patterns of industrial districts (IDs). The procedure can be classified as a k‐means cluster‐wise regression procedure and is designed to detect homogeneous areas of subcontracting activity.
Jacopo Canello   +3 more
wiley   +1 more source

Multiple Changepoint Detection for Non‐Gaussian Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios.
Robert Lund   +3 more
wiley   +1 more source

Testing for Unspecified Periodicities in Binary Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT Given random variables Y1,…,Yn$$ {Y}_1,\dots, {Y}_n $$ with Yi∈{0,1}$$ {Y}_i\in \left\{0,1\right\} $$ we test the hypothesis whether the underlying success probabilities pi$$ {p}_i $$ are constant or whether they are periodic with an unspecified period length of r≥2$$ r\ge 2 $$.
Finn Schmidtke, Mathias Vetter
wiley   +1 more source

Beyond just correlation: causal machine learning for the microbiome, from prediction to health policy with econometric tools. [PDF]

open access: yesFront Microbiol
Khelfaoui I   +9 more
europepmc   +1 more source

Adaptive Estimation for Weakly Dependent Functional Times Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro   +2 more
wiley   +1 more source

Online Jump and Kink Detection in Segmented Linear Regression: Statistical Optimality Meets Computational Efficiency

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We consider the problem of sequential (online) estimation of a single change point in a piecewise linear regression model under a Gaussian setup. We demonstrate that certain CUSUM‐type statistics attain the minimax optimal rates for localizing the change point.
Annika Hüselitz, Housen Li, Axel Munk
wiley   +1 more source

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