Diagnostics for Time Series Analysis
نویسندگان
چکیده
Test statistics are proposed to determine the goodness of t of a time series model. The test statistics are based on a sequence of random variables that are independent and standard normal if the model is correct. The paper shows how to compute eeciently this sequence of random variables using a combination of Markov chain Monte Carlo and importance sampling. The power of the test statistics to detect outliers and level shifts is studied for an autoregressive model. The methodology is illustrated using both simulated and real data.
منابع مشابه
Leave·k·out Diagnostics for Time Series
We propose diagnostics for ARIMA model fitting for time series formed by deleting observations from the data and measuring the change in the estimates of the parameters. The use of leave-one-out diagnostics is a well established tool in regression analysis. We demonstrate the efficacy of observation deletion based diagnostics for ARIMA models, addressing issues special to the time diagnostics b...
متن کاملDynamic linear model diagnostics
In time series analysis using dynamic linear models, retrospective analysis involves the calculation of filtered, or smoothed, distributions for state parameters in the past. We develop and illustrate novel results that are useful in retrospective assessment of the influence of individual observations on such distributions. In particular, new and computationally simple filtering equations are d...
متن کاملInterpolating time series based on fuzzy cluster analysis problem
This study proposes the model for interpolating time series to use them to forecast effectively for future. This model is established based on the improved fuzzy clustering analysis problem, which is implemented by the Matlab procedure. The proposed model is illustrated by a data set and tested for many other datasets, especially for 3003 series in M3-Competition data. Comparing to the exist...
متن کاملForecasting flow discharge through time series analysis using SARIMA model for drought conditions, a case study of Jamishan River
Nowadays, water supply is more limited and providing water is more difficult due to increasing population and demand for water. Thus, due to rainfall shortage and impacts of drought, the need for forecasting monthly and annual rainfall and flow discharge through time series analysis is acutely felt. One of the key assumption in time series is their static condition. However, hydrological time s...
متن کاملResidual analysis using Fourier series transform in Fuzzy time series model
In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...
متن کاملDynamic characterization and predictability analysis of wind speed and wind power time series in Spain wind farm
The renewable energy resources such as wind power have recently attracted more researchers’ attention. It is mainly due to the aggressive energy consumption, high pollution and cost of fossil fuels. In this era, the future fluctuations of these time series should be predicted to increase the reliability of the power network. In this paper, the dynamic characteristics and short-term predictabili...
متن کامل