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Prediction Intervals for ARIMA Models [PDF]
Journal of Business & Economic Statistics, 2001 The problem of constructing prediction intervals for linear time series (ARIMA) models is examined. The aim is to find prediction intervals which incorporate an allowance for sampling error associated with parameter estimates. The effect of constraints on parameters arising from stationarity and invertibility conditions is also incorporated.
Snyder, Ralph D. +2 more
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ARIMA models in load modelling with clustering approach [PDF]
2005 IEEE Russia Power Tech, 2005 In distribution system, bus load estimation is complicated because system load is usually monitored at only a few points. As a rule receiving nodes are not equipped with stationary measuring instruments so measurements of loads are performed sporadically. In general, the only information commonly available regarding loads, other than major distribution
Nazarko, Joanicjusz +2 more
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The Identification of Multiple Outliers in ARIMA Models [PDF]
Communications in Statistics - Theory and Methods, 2003 The presence of outliers causes biases in the estimation of ARIMA models. In this work we present a procedure for detecting outliers and obtaining a robust estimator of the parameters in univariate ARIMA time series models. There are three main problems in the existing procedures for detecting outliers in ARIMA time series models.
Sánchez, María Jesús, Peña, Daniel
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Forecasting Crime Using ARIMA Model
CoRR, 2020 Data mining is the process in which we extract the different patterns and useful Information from large dataset. According to London police, crimes are immediately increases from beginning of 2017 in different borough of London. No useful information is available for prevent crime on future basis.
Khawar Islam, Akhter Raza
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The Selection of ARIMA Models With or Without Regressors [PDF]
SSRN Electronic Journal, 2012 We develop a Cp statistic for the selection of regression models with stationary and nonstationary ARIMA error term. We derive the asymptotic theory of the maximum likelihood estimators and show they are consistent and asymptotically Gaussian. We also prove that the distribution of the sum of squares of one step ahead standardized prediction errors ...
Johansen, Søren +2 more
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Comparison of ARIMA and ARIMA/GARCH Models in EVN Traffic Prediction [PDF]
Journal of Research and Development on Information and Communication Technology, 2014 This paper focuses on building statistical models to capture and forecast the traffic of mobile communication network in Vietnam. Following BoxJenkins method, a multiplicative seasonal ARIMA model is constructed to represent the mean component using the past values of traffic, a GARCH model is then incorporated to ...
Tran Quang Thanh, Trinh Quang Khai
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Abstract Background Dengue remains an enduring public health concern across tropical and subtropical regions of China, with a disproportionate burden observed in economically disadvantaged areas. Dengue outbreaks can overwhelm healthcare systems and impede economic development.
Jingyi Guo +5 more
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Efficient In-Database Maintenance of ARIMA Models
, 2011 Forecasting is an important analysis task and there is a need of integrating time series models and estimation methods in database systems. The main issue is the computationally expensive maintenance of model parameters when new data is inserted. In this paper, we examine how an important class of time series models, the AutoRegressive Integrated ...
Frank Rosenthal, Wolfgang Lehner
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ARIMA Modeling of Noise of Piezoelectric Accelerometer
IEEE AccessPiezoelectric accelerometer is well-known for ultra-high sensitivity that is limited by the noise floor. Due to its importance, the modeling of the noise of piezoelectric accelerometers using Autoregressive Integrated Moving Average (ARIMA) is presented herein.
Ghulam Ali, Faisal Mohd-Yasin
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Combining disaggregate forecasts for inflation: The SNB's ARIMA model: the SNB's ARIMA model
, 2013 ISSN:1661 ...
Huwiler, Marco, Kaufmann, Daniel
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