⌘+K

Pulse Explore Communities Researchers Journals

Browser extensionInstagram

Home Communities Explore

August 6, 2025

Predicting the producer price index (PPI) in China using Gaussian process regression frameworks parameterized through Bayesian inference

Bingzi Jin Xiaojie Xu

View at Publisher

Ask AI

Bookmark

Share

Key Points

The prediction of the producer price index (PPI) offers valuable insights into market dynamics and economic stability.
The use of Gaussian process regression provides a robust framework for analysis, enhancing forecasting accuracy.
An economic model based on Bayesian inference allows for the incorporation of uncertainty, yielding more reliable predictions.
Understanding PPI trends supports effective decision-making for stakeholders in various industries and financial markets.

Ask about this paper

Answers are grounded in this paper and cite their sources.

Ask your own question…

Implication

Gaussian process regression predicts PPI in China, suggesting insights into economic models and market dynamics.

Abstract

No abstract yet. The journal hasn't published one we can show.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Jin et al. (2025) studied this question.

synapsesocial.com/papers/68a368780a429f797332d67f https://doi.org/10.1142/s3082844925500137

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context:

1A Bayesian-tuned Gaussian process approach to forecasting carbon market prices: A case study of China's emissions trading schemeOriginal Research · 2026 · 31 citations
2Bayesian Gaussian Process Predictions of Chongqing Carbon Market Prices2025 · 36 citations
3Gaussian process regression based machine learning forecasts of steel price indices for the southern market in ChinaOriginal Research · 2026
4A Bayesian-optimized Gaussian process framework for carbon market price forecasting: An application to Fujian's emissions trading scheme2025 · 14 citations
5Forecasting the Chinese energy security index price: A Gaussian process regression-based machine learning framework enhanced by Bayesian optimisation and cross-validation2025 · 7 citations
6Forecasts of share prices for China with machine learning2025
7Predictive Modeling of the New Energy Index Trading Volume in Mainland China: A Gaussian Process Regression Approach in Machine LearningOriginal Research · 2026 · 26 citations
8Forecasts of thermal coal prices through Gaussian process regressions2024 · 150 citations