Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

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Abstract: Hidden Markov models (HMMs) for time-series data analysis are attracting wide interests in industries due to their ability to model the extensively existing dynamics and non-Gaussianities.

Abstract: Long-term Time Series Forecasting (LTSF) plays a crucial role in various fields, including energy consumption and weather prediction. Recent advancements in deep learning, particularly ...

Introduction: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Solargis’ Evaluate 2.0 platform uses more granular time series data. Image: Solargis. For years, the solar industry has relied on Typical Meteorological Year (TMY) data as the standard for PV ...

Linear pluggable optics (LPO) is garnering more attention as a way to quickly and efficiently move data in and out of server racks, but a lack of standards for connecting the optical modules is ...

ABSTRACT: The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on ...