全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2016 

SARIMA模型在流行性腮腺炎发病预测中的应用
Application of SARIMA model in predicting the incidence of mumps

DOI: 10.6040/j.issn.1671-7554.0.2015.1163

Keywords: 预测,时间序列分析,季节性差分自回归移动平均模型,流行性腮腺炎,
Time series analysis
,Seasonal autoregressive integrated moving average model,Prediction,Mumps

Full-Text   Cite this paper   Add to My Lib

Abstract:

References

[1]  Martinez EZ, Silva EA. Predicting the number of cases of dengue infection in Ribeirao Preto, Sao Paulo State, Brazil, using a SARIMA model[J]. Cad Saude Publica, 2011, 27(9):1809-1818.
[2]  马亮亮, 田富鹏. 不同时间序列分析方法在高血压发病率预测中的比较[J]. 中国老年学杂志, 2010, 30(13):1777-1780. MA Liangliang, TIAN Fupeng. Application of time series analysis in the prediction of hypertension incidence[J]. Chinese Journal of Gerontology, 2010, 30(13):1777-1780.
[3]  李秀君, 康殿民, 曹杰, 等. 时间序列模型在肾综合征出血热发病率预测中的应用[J]. 山东大学学报(医学版), 2008, 46(5):547-549. LI Xiujun, KANG Dianmin, CAO Jie, et al. Application of time series analysis in the prediction of hemorrhagic fever of renal syndrome incidence[J]. Journal of Shandong University(Health Science), 2008, 46(5):547-549.
[4]  彭志行, 陶红, 贾成梅, 等. 时间序列分析在麻疹疫情预测预警中的应用研究[J]. 中国卫生统计, 2010, 27(5):459-463. PENG Zhihang, TAO Hong, JIA Chengmei, et al. Application of time series analysis in the prediction of measles incidence[J]. Chinese Journal of Health Statistics, 2010, 27(5):459-463.
[5]  Dayan GH, Quinlisk MP, Parker AA, et al. Recent resurgence of mumps in the United States[J]. N Engl J Med, 2008, 358(15):1580-1589.
[6]  Galazka AM, Robertson SE, Kraigher A. Mumps and mumps vaccine: a global review[J]. Bull World Health Organ, 1999, 77(1):3-14.
[7]  Mumps virus vaccines[J]. Wkly Epidemiol Rec, 2007, 82(7):51-60.
[8]  Hviid A, Rubin S, Muhlemann K. Mumps[J]. Lancet, 2008, 371(9616):932-944.
[9]  Yang Q, Yang Z, Ding H, et al. The relationship between meteorological factors and mumps incidence in Guangzhou, China, 2005-2012[J]. Hum Vaccin Immunother, 2014, 10(8):2421-2432.
[10]  Fu CX, Nie J, Liang JH, et al. Evaluation of live attenuated S79 mumps vaccine effectiveness in mumps outbreaks: a matched case-control study[J]. Chin Med J(Engl), 2009, 122(3):307-310.
[11]  金如锋, 邱宏, 周霞, 等. ARIMA模型和GM(1,1)模型预测全国3种肠道传染病发病率[J]. 复旦学报(医学版), 2008, 35(5):675-680. JIN Rufeng, QIU Hong, ZHOU Xia, et al. Forecasting incidence of three intestinal infectious diseases in China with ARIMA model and GM(1,1)model[J]. Fudan University Journal of Medical Sciences, 2008, 35(5):675-680.
[12]  许阳婷. ARIMA模型在流行性腮腺炎发病率预测中的应用[J]. 华南预防医学, 2015, 41(3):255-259. XU Yangting. Application of time series analysis in the prediction of mumps incidence[J]. South China Journal of Preventive Medicine, 2015, 41(3):255-259.
[13]  Moosazadeh M, Nasehi M, Bahrampour A, et al. Forecasting tuberculosis incidence in Iran using box-jenkins models[J]. Iran Red Crescent Med J, 2014, 16(5): e11779. doi:10.5812/ircmj.11779
[14]  Liu L, Luan RS, Yin F, et al. Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model[J]. Epidemiol Infect, 2016, 144(1):144-151.
[15]  赛晓勇, 张治英, 徐德忠, 等. 不同时间序列分析法在洞庭湖区血吸虫病发病预测中的比较[J]. 中华流行病学杂志, 2004, 25(10):40-43. SAI Xiaoyong, ZHANG Zhiying, XU Dezhong, et al. Different time series analysis method on the prediction of schistosomiasis in Dongting Lake regions[J]. Chinese Journal of Epidemiology, 2004, 25(10):40-43.
[16]  Kane MJ, Price N, Scotch M, et al. Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks[J]. BMC Bioinformatics, 2014, 15(1):276. doi:10.1186/1471-2105-15-276.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133