Search Results - subject:"PCA"

Classification of Latin American and Caribbean countries based on multidimensional development indicators : a multivariate empirical analysis

Mendoza-Mendoza, Adel; Visbal-Cadavid, Delimiro; … - In: Economies : open access journal 13 (2025) 6, pp. 1-21

component analysis (PCA), the objective was to reduce the complexity of the data set and reveal the main structural dimensions …

Persistent link: https://www.econbiz.de/10015439162

Portfolio margining using PCA latent factors

Du, Shengwu; Nesmith, Travis D. - 2025

Persistent link: https://www.econbiz.de/10015406665

PCA-ICA-LSTM : a hybrid deep learning model based on dimension reduction methods to predict S&P 500 index price

Sarıkoç, Mehmet; Celik, Mete - In: Computational economics 65 (2025) 4, pp. 2249-2315

Persistent link: https://www.econbiz.de/10015590240

Robust functional principal component analysis for detecting anomalous behaviors in electricity markets

Bernardi, Mara Sabina; Cerasa, Andrea; Grossi, Luigi; … - In: Energy economics 154 (2026), pp. 1-15

Persistent link: https://www.econbiz.de/10015627091

Multidimensional measures of quality of life : a comparison of methods using U.S. county-level data

Cheng, Yang; Conroy, Tessa; Deller, Steven C. - In: Papers in regional science : the journal of the … 105 (2026) 1, pp. 1-21

There are numerous measures of place-based quality of life, accompanied by ongoing debate over which factors should be included. Past studies have predominately relied on aspatial, subjectively weighted combinations of different place-based characteristics. Little attention has been given to the...

Persistent link: https://www.econbiz.de/10015638967

Hierarchical house price model incorporating geographical and macroeconomic factors : evidence from Australia

Lyu, Lingfeng; Shen, Yang; Sherris, Michael; Zivey, Jonathan - 2025

Persistent link: https://www.econbiz.de/10015651855

Making sense of labor-market indicators amid data imperfections

Brave, Scott A.; Crust, Erin; Eusepi, Stefano; Hobijn, Bart - 2026

Interpreting real-time labor market conditions is challenging because commonly used indicators are noisy, revised over time, and often send conflicting signals. In practice, policymakers and market participants describe labor market developments using a shared narrative language centered on...

Persistent link: https://www.econbiz.de/10015647170

Optimizing data aggregation and clustering in Internet of things networks using principal component analysis and Q-learning

Bajpai, Abhishek; Verma, Harshita; Yadav, Anita - In: Data science and management : DSM 7 (2024) 3, pp. 189-196

analysis (PCA) and a reinforcement learning algorithm to achieve efficient clustering and data reduction. The primary …

Persistent link: https://www.econbiz.de/10015078068

Dimensionality reduction analysis of the renewable energy sector in Azerbaijan : nonparametric analyses of large datasets

Niftiyev, Ibrahim - In: Statistics in transition : an international journal of … 25 (2024) 2, pp. 81-102

on nonparametric dimensionality reduction are rather sparse. Principal component analysis (PCA) and multiple … energy sector and selected key macroeconomic indicators was evaluated. The PCA procedure yielded four distinct principle … resource revenues. The PCA method offers the possibility to examine the precise correlations and the underlying patterns …

Persistent link: https://www.econbiz.de/10015125542

New rank-based tests and estimators for common primitive shocks

Carlini, Federico; Rubin, Mirco; Vallarino, Pierluigi - 2025 - This version: February 28, 2025

We propose a new rank-based test for the number of common primitive shocks, q, in large panel data. After estimating a VAR(1) model on r static factors extracted by principal component analysis, we estimate the number of common primitive shocks by testing the rank of the VAR residuals'...

Persistent link: https://www.econbiz.de/10015329825