نتایج جستجو برای: arima فصلی
تعداد نتایج: 7771 فیلتر نتایج به سال:
Auto Regressive Integrated Moving Average (ARIMA) is a broad class of time series models, and it has been achieved using the statistical differencing approach. It is normally being performed using the computational method. Thus, it is useful to choose the suitable model from a possibly large selection of the available ARIMA formulations. The ARIMA approach was then analysed with the presence of...
BACKGROUND We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliabilit...
فضای حالت و هموارسازی نمایی هر دو روش هایی برای پیش بینی و هموارسازی محسوب می شوند با این تفاوت که مدل های فضای حالت بسیلری از مدل ها از جمله arch garch,arima را نیز شامل می شود. در این رساله سعی شده که هموارسازی نمایی با توجه به مولفه های آن شامل روند اثرات فصلی و دوره که می توانن به صورت جمعی یا ضربی ترکیب شونددر قالب یک مدل فضای حالت قرار گیرد. سپس با استفاده از الگوریتم فیلتر کالمن به هموا...
The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed...
رودخانۀ کهمان پرمنفعتترین رودخانۀ شهرستان الشتر از نظر کشاورزی و پرورش ماهی است. بهدلیل اینکه فرایندهای هیدرولوژی تصادفیاند، آمار و احتمال اساس تجزیه و تحلیل پدیدههای یادشده است، بنابراین از سریهای زمانی استفاده میشود. در تحلیل سری زمانی، مرحلۀ اول شامل نمایش نوسان پارامترها در طول زمان است، مرحلۀ دوم ایستاسازی دادهها، مرحلۀ سوم نرمالسازی و مرحلۀ چهارم شناسایی پارامترهای مدل است. درن...
BACKGROUND China is a country that is most seriously affected by hemorrhagic fever with renal syndrome (HFRS) with 90% of HFRS cases reported globally. At present, HFRS is getting worse with increasing cases and natural foci in China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence to make the control of HFRS more effective. In this study, we applied a stochastic...
OBJECTIVE Injury is currently an increasing public health problem in China. Reducing the loss due to injuries has become a main priority of public health policies. Early warning of injury mortality based on surveillance information is essential for reducing or controlling the disease burden of injuries. We conducted this study to find the possibility of applying autoregressive integrated moving...
Canada has implemented legislation covering all firearms since 1977 and presents a model to examine incremental firearms control. The effect of legislation on homicide by firearm and the subcategory, spousal homicide, is controversial and has not been well studied to date. Legislative effects on homicide and spousal homicide were analyzed using data obtained from Statistics Canada from 1974 to ...
Tuberculosis is a major global public health problem, which also affects economic and social development. China has the second largest burden of tuberculosis in the world. The tuberculosis morbidity in Xinjiang is much higher than the national situation; therefore, there is an urgent need for monitoring and predicting tuberculosis morbidity so as to make the control of tuberculosis more effecti...
This study compares two new seasonal adjustment methods designed to handle outliers and structural changes: X-IZARIMA and GAUSUM-STM. X12-ARIMA is a successor to the X-ll-ARIMA seasonal adjustment method, and is being developed at the U.S. Bureau of the Census (Findley et al. (1988)). GAUSUM-STM is a non-Gaussian method using time series structural models, and was developed for this study based...
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