time series modeling approach
Copula-based semiparametric models for multivariate time series
... univariate time series modeling approach of Chen & Fan ...semiparametric time series models, ...between time series. Their technique differs from the usual ...
13
A Hybrid Approach for Modeling Financial Time Series
... forecasting time series in financial ...for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced ...models. Time series ...
9
Selection of Best ARIMA Modeling Approach for Forecasting Time Series Patterns; A Case Study on Colombo Stock Exchange
... [11] R.M Kapila Tharanga Rathnayaka, D.M. Kumudu Nadeeshani Seneviratne and Zhong- jun Wang, “An Investigation of Statistical Behaviors of the Stock Market Fluctuations in the Colombo Stock Market: ARMA & PCA ...
5
Cybersecurity: Time Series Predictive Modeling of Vulnerabilities of Desktop Operating System Using Linear and Non Linear Approach
... The schematic network of Desktop Operating Systems, given by Figure 2 above, displays a layout of the process that our analytic study will follow. In the present study, we have developed analytic vulnerability ...
21
Time series modeling for syndromic surveillance
... We built models of ED utilization using a time-series an- alytic approach. Models were constructed through an iter- ative process and were trained on roughly the first eight years of data (2,775 ...
11
A Modified Approach on Fuzzy Time Series Forecasting
... the time series comprised of imprecise ...of time series the uncertainty of the individual observed values as well as the interpretation of a sequence of uncertain observed values are of ...
11
SARS Time Series Modeling and Spatial Data Analysis
... infection, approach is timely isolation and treatment, and timely treatment of SARS on the scale or level of the hospital has a high demand for hospital information collected and stored, when one region discovered ...
7
On observation-driven time series modeling
... This approach provides a general framework to specify the time-varying parameter in an observation-driven ...update time-varying parameters is also justified by an optimality reasoning (Blasques et ...
133
Quantile autoregressive distributed lag model with an application to house price returns
... in time series models where controlling for lagged regressors and exogenous covariates is ...The approach proposed in this paper is different from that of Engle and Manganelli (2004) because we use ...
48
Handling arch effects in wind speed data using state space approach model
... dynamic time series model that is capable to forecast in short term duration is ...data series was examined ...speed time series with conventional models ...of modeling and ...of ...
44
Advances in Statistical Network Modeling and Nonlinear Time Series Modeling
... nonlinear time series models that have been applied successfully to data from various ...nonlinear time series models that are mostly inspired by high di- mensional statistical ...nonlinear ...
121
Identification and Modeling of Outliers in a Discrete - Time Stochastic Series
... stochastic series may result in model misspecification, biases in parameter estimation and in addition, it is difficult to identify some outliers due to masking ...iterative approach which involves joint ...
7
Modeling and forecasting time series of precious metals: a new approach to multifractal data
... results were for each trial. In seven out of 12 trials, the proximity to the actual value from VARFIMA trials were 10% or less of the difference value of ARFIMA results. In Table 6, the differences between 30th day ...
28
Takagi interpolation problem as time series modeling
... of time: in the discrete-time case as in the original version [17] (see also [13]), in the context of interpolation with rational matrix functions as in the book [4], with the generalized Beurling-Lax ...
10
Factor modeling for high dimensional time series
... terms as one cannot separate X t(-) from £*(•) in (1.1). This difficulty was resolved in Hall & Vial (2006) under a ‘low noise’ setting which assumes that the noise £*(•) goes to zero as the sample size goes to ...
90
Customer Equity-Driven Marketing Mix Decisions at Wachovia Bank
... Modeling Approach Log-Log Cross- Sectional Time Series Model Synergies among Drivers Diminishing Returns of Marketing Reduce Outlier Effects DMA Differences in a Common Model La[r] ...
21
Modeling births at a tertiary health-care facility in Ghana: Box-Jenkins time series approach
... Data obtained were captured in Microsoft Excel 2010 and analysis was performed in R statistical software version 3.0.3. Box-Jenkins (4) approach put forward as autoregressive integrated moving average (ARIMA) ...
7
An Introductory Study on Time Series Modeling and Forecasting
... for time series modeling and ...(ANNs) approach has been suggested as an alternative technique to time series forecasting and it gained immense popularity in last few ...for ...
67
Time series modeling and decomposition
... In another study, Dagum and Bianconcini (2008) derive two density functions and corresponding orthonormal polynomials to obtain two Reproducing Kernel Hilbert Space representations which give excellent results for ...
25
Financial-Economic Time Series Modeling and Prediction Techniques – Review
... Cheng et al, (2010) proposed a hybrid forecasting model using multi-technical indicators to predict stock price trends. There are four procedures described such as select the essential technical indicators, the popular ...
6