Unemployment remains a major cause for both developed and developing nations, due to which they lose their financial economic impact as whole. rate prediction achieved researcher attention from fast few years. The intention of doing our research is examine the coronavirus on unemployment rate. Accurately predicting stimulating job policymakers, plays an imperative role in country's development ...

BACKGROUND The main objective of this study is to apply autoregressive integrated moving average (ARIMA) models to make real-time predictions on the number of beds occupied in Tan Tock Seng Hospital, during the recent SARS outbreak. METHODS This is a retrospective study design. Hospital admission and occupancy data for isolation beds was collected from Tan Tock Seng hospital for the period 14...

In this paper we mirror the framework of generalized (non-)linear models to define the family of generalized age-period-cohort stochastic mortality models which encompasses the vast majority of stochastic mortality projection models proposed to date, including the well-known Lee-Carter and Cairns-Blake-Dowd models. We also introduce the R package StMoMo which exploits the unifying framework of ...

We analyze the effects on prediction intervals of fitting ARIMA models to series with stochastic trends, when the underlying components are heteroscedastic. We show that ARIMA prediction intervals may be inadequate when only the transitory component is heteroscedastic. In this case, prediction intervals based on the unobserved component models tend to the homoscedastic intervals as the predicti...

This paper outlines the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Irish inflation. A framework for ARIMA forecasting is drawn up. It considers two alternative approaches to the issue of identifying ARIMA models the Box Jenkins approach and the objective penalty function methods. The emphasis is on forec...

Network traffic prediction plays a vital role in the optimal resource allocation and management in computer networks. This paper introduces an ARIMA based model for the real time prediction of VBR video traffic. The methodology presented here can successfully addresses the challenges in traffic prediction such as accuracy in prediction, resource management and utilization. ARIMA application on ...

An approach to exponential smoothing that relies on a linear single source of error state space model is outlined. A maximum likelihood method for the estimation of associated smoothing parameters is developed. Commonly used restrictions on the smoothing parameters are rationalised. Issues surrounding model identi…cation and selection are also considered. It is argued that the proposed revised ...

Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA based model. SVM-based forecasting model necessitates the selection of appropriate kernel function and values of free parameters: regularization parameter and ε– insensitive loss function. In this paper, we investigate th...

In this paper an attempt is made to develop hybrid models using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) for predicting the future exchange rate for US dollar. Simulation results of hybrid models were compared with results of ANN based models and ARIMA based models. Results show that the model ANN – ARIMA ANN gives a better performance than the other ...