Tuberculosis is a major global public health problem, which also affects economic and social development. China has the second largest burden of tuberculosis in the world. The tuberculosis morbidity in Xinjiang is much higher than the national situation; therefore, there is an urgent need for monitoring and predicting tuberculosis morbidity so as to make the control of tuberculosis more effecti...

Abstract Existing integer-valued generalised autoregressive conditional heteroskedasticity (INGARCH) models for spatio-temporal counts do not allow negative parameter and autocorrelation values. Using approximately linear INGARCH models, the unified flexible (B)INGARCH framework modelling unbounded (bounded) is proposed. These combine dependencies with kinds of a long memory. They are easily ad...

In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any parametric specification of the volatility process and takes contemporaneous error correlation implicitly into account. Via a Monte Carlo investigation empiric...

The popularity of Bitcoin increased significantly in 2021. is considered to deliver high returns a relatively short period, indicating that bitcoin has volatility. Data with volatility usually violates the Autoregresstive IntegratedinMovinginAverage (ARIMA)in homoscedasticity assumption. Autoregressive Conditional Heteroscedasticity (ARCH) and General (GARCH) model often used overcome problem h...

This work investigates the effects of using independent Jeffreys prior for degrees freedom parameter a t-student model in asymmetric generalised autoregressive conditional heteroskedasticity (GARCH) model. To capture asymmetry reaction to past shocks, smooth transition models are assumed variance. We adopt fully Bayesian approach inference, prediction and selection discuss problems related esti...

In this study, we employ the GARCH–MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to investigate response stock market volatility BRICS group countries (Brazil, Russia, India, China, and South Africa) oil shocks. We utilise recent datasets Baumeister & Hamilton (2019), where shocks are decomposed into four variants: supply shocks, economic...

Christoffersen, Jacobs, and Ornthanalai (2012) (CJO) propose an interesting and useful class of generalized autoregressive conditional heteroskedasticity (GARCH)-like models with dynamic jump intensity, and find evidence that the models not only fit returns data better than some commonly used benchmarks but also provide substantial improvements in option pricing performance. While such models p...

Condition-based maintenance is currently widely used in the aviation industry with diagnoses obtained from the performance data of the aircraft. Online assessments of the real-time condition and predicted residual life have been of great importance for both mechanics and pilots, especially during flight for the latter. Statistical distribution and feature parameters are believed to be crucial c...