Results 111 to 120 of about 60,493 (305)
MathematicsRegime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis.
Zhenni Tan, Yuehua Wu
doaj +1 more source
Detecting Turning Points with Many Predictors through Hidden Markov Models [PDF]
This paper explores the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series which offer reliable information to detect recessions in real time.
David Saint-Martin, Benoit Bellone
core
Spatio‐Temporal Dual‐Encoder Transformer for Short‐Term Regional Wind Power Forecasting
Energy Science &Engineering, EarlyView.ST‐DualFormer separates temporal and spatial encoding to model complex dependencies in regional wind power forecasting. The fused dual‐stream representation enables accurate short‐term regional forecasts from multi‐farm meteorological and historical power data. The method achieved 5.25% nMAE and 7.53% nRMSE for three‐day‐ahead forecasting on real‐world
Jianfeng Che +4 more
wiley +1 more source
Complexity of Comparing Hidden Markov Models
, 2001 The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960's, and has since then been applied to numerous problems, e.g. biological sequence analysis. In this paper we consider the problem of computing the most likely string generated by a given model, and its implications on the complexity of ...
Lyngsø, R.B., Pedersen, C.N.S.
openaire +2 more sources
Brain–Computer Interfaces: The Dawn of a New Era in Disease Treatment
Exploration, EarlyView.This study investigates the potential of brain–computer interface (BCI) technology in treating neuropsychiatric disorders, such as movement and communication barriers. Our review examines the history, signal paradigms, and diverse applications of BCI while also discussing ongoing research into novel materials and emerging technologies that offer ...
Yuqi Feng +11 more
wiley +1 more source
Hidden Markov models with spectral features for 2D shape recognition
, 2001 We present a technique using Markov models with spectral features for recognizing 2D shapes. We analyze the properties of Fourier spectral features derived from closed contours of 2D shapes and use these features for 2D pattern recognition.
Cai, Jinhai, Liu, Zhi-Qiang
core +1 more source
Journal of Forecasting, EarlyView.ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu +3 more
wiley +1 more source
Computation of the asymptotic null distribution of goodness-of-fit tests for multi-state models. [PDF]
, 2009 We develop an improved approximation to the asymptotic null distribution of the goodness-of-fit tests for panel observed multi-state Markov models (Aguirre-Hernandez and Farewell, Stat Med 21:1899-1911, 2002) and hidden Markov models (Titman and Sharples,
Titman, Andrew C.
core
International Journal of Finance &Economics, EarlyView.ABSTRACT This study aims to classify pivotal fintech innovations and explore the prospects and pitfalls associated with emerging fintech services extensively discussed in the literature. We conducted a multistage systematic review of research published on fintech over the past decade from a technological perspective. Using the Preferred Reporting Items
Muhammad Imran Qureshi, Nohman Khan
wiley +1 more source
Variational Bayesian Analysis for Hidden Markov Models
, 2009 The variational approach to Bayesian inference enables simultaneous estimation of model parameters and model complexity. An interesting feature of this approach is that it also leads to an automatic choice of model complexity.
McGrory, Clare A. +2 more
core +1 more source