In many high dimensional problems, the dependence structure among the variables can be quite complex. An appropriate use of the regularization techniques coupled with other classical statistical methods can often improve estimation and prediction accuracy and facilitate model interpretation, by seeking a parsimonious model representation that involves only the subset of revelent variables. We p...

This study presents developing procedures and verification of a new hybrid model, namely wavelet packet-genetic programming (WPGP) for short-term meteorological drought forecast. To this end, the multi-temporal standardized precipitation evapotranspiration index (SPEI) has been used as quantifying parameter at two stations Ankara province, Turkey. The WPGP model comprises main steps. In first s...

Traffic prediction constitutes a hot research topic of network metrology. MultiStep ahead prediction allows to predict more values in the future. Then, the result can be used to act proactively in many prediction applications. In this work, the AutoRegressive Integrated Moving Average (ARIMA) model and the linear minimum mean square error (LMMSE) are used for multiStep predicting. Via experimen...

In this paper, a multivariate fundamental skew probit (MFSP) model is used to model correlated ordinal responses which are constructed from the multivariate fundamental skew normal (MFSN) distribution originate to the greater flexibility of MFSN. To achieve an appropriate VC structure for reaching reliable statistical inferences, many types of variance covariance (VC) structures are considered ...

The article describes the economic essence of stock market infrastructure and main directions its formation, scientific theoretical basis. foreign experience exchanges has been studied, opportunities for their application to Uzbekistan have identified. Analysis institutional, technical functional bases market, situation in Republic Uzbekistan. Factors influencing development were systematized a...

This study examines the labor market effects of influx Syrian refugees in Turkey. Engle-Granger and Johansen co-integration tests, followed by autoregressive distributive lag (ARDL) bounds tests reveal that Turkish unemployment refugee series are co-integrated; pointing out to a long-run relationship. Short-run dynamics have been analyzed from fitted ARDL model error-correction parameter is use...

This novel research looked into the role of public-private partnership investment in energy affecting Pakistan’s long-term environmental sustainability. Employing time series data from 1992 to 2018 and utilizing autoregressive distributive lag model (ARDL) model, we found a equilibrium association ecological footprint with energy, technological innovation, economic growth, trade openness. Our o...

The decrease in the quality of environment is one key problems currently facing human society, especially if environmental capacity to serve needs considered be a factor emergence global warming phonemes. In addition, all actions are deemed responsible for decline degradation. aim paper see how, as formulated by classical STIRPAT model, activity Indonesia driving factors deterioration quality, ...

The study investigated the impact of non-oil revenue on economic growth Nigeria for period 1981 to 2019. Autoregressive Distributed Lags (ARDL) technique was adopted alongside unit root test, which showed that in all cases, variables level form were non-stationary but their first differences found be stationary. This shows (including growth) are co-integrated at order 1. short run diagnostic te...

liberalization of international markets affects level of pollution in developing countries more than in developed countries. therefore the impact of trade liberalization on environmental pollution is a challenge for policy makers. in this paper auto regressive distributed lags (ardl) and error correction model (ecm) methods are employed for a study of the relationship between trade liberalizati...