in this paper, we show that the chapman-kolmogorov formula could be used as a recursive formula for computing the m-step-ahead conditional density of a markov bilinear model. the stationary marginal probability density function of the model may be approximated by the m-step-ahead conditional density for sufficiently large m.

A reliable flood warning system depends on efficient and accurate forecasting technology. A systematic investigation of three common types of artificial neural networks (ANNs) for multi-stepahead (MSA) flood forecasting is presented. The operating mechanisms and principles of the three types of MSA neural networks are explored: multi-input multi-output (MIMO), multi-input single-output (MISO) a...

We develop and show applications of two new test statistics for deciding if one ARIMA model provides significantly better h-step-ahead forecasts than another, as measured by the difference of approximations to their mean square forecast error. The two statistics differ in the variance estimates used for normalization. Both variance estimates are consistent even when the models considered are in...

We study the fitting of time series models via minimization of a multi-step ahead forecast error criterion that is based on the asymptotic average of squared forecast errors. As in Haywood and Tunnicliffe-Wilson (1997) our score function is formulated in the frequency domain, but our time series models are not limited to those with spectra linear in the parameters; our formulation includes all ...

In finance, volatility is defined as a measure of variation of a trading price series over time. As volatility is a latent variable, several measures, named proxies, have been proposed in the literature to represent such quantity. The purpose of our work is twofold. On one hand, we aim to perform a statistical assessment of the relationships among the most used proxies in the volatility literat...

#no abstract#

Wearable tremor suppression devices (WTSD) have been considered as a viable solution to manage parkinsonian tremor. WTSDs showed their ability improve the quality of life individuals suffering from tremor, by helping them perform activities daily living (ADL). Since has shown be nonstationary, nonlinear, and stochastic in nature, performance models used is affected inability adapt nonlinear beh...

Accurate multi-step PM2.5 (particulate matter with diameters ?2.5um) concentration prediction is critical for humankinds’ health and air population management because it could provide strong evidence decision-making. However, very challenging due to its randomness variability. This paper proposed a novel method based on convolutional neural network (CNN) long-short-term memory (LSTM) space-shar...

Rainfall is a primary factor for agricultural production, especially in rainfed region. Its accurate prediction therefore vital planning and managing farmers’ plantations. plays an important role the symmetry of water cycle, many hydrological models use rainfall as one their components. This paper aimed to investigate applicability six machine learning (ML) techniques (i.e., M5 model tree: (M5)...