{"department":[{"_id":"206"}],"user_id":"10075","_id":"4617","language":[{"iso":"eng"}],"extern":"1","publication":"Computational Statistics & Data Analysis","type":"journal_article","status":"public","volume":40,"author":[{"first_name":"Jan","last_name":"Beran","full_name":"Beran, Jan"},{"id":"20760","full_name":"Feng, Yuanhua","last_name":"Feng","first_name":"Yuanhua"}],"date_created":"2018-10-10T11:18:08Z","date_updated":"2022-01-06T07:01:15Z","publisher":"Elsevier BV","doi":"10.1016/s0167-9473(02)00007-5","title":"SEMIFAR models—a semiparametric approach to modelling trends, long-range dependence and nonstationarity","issue":"2","publication_identifier":{"issn":["0167-9473"]},"publication_status":"published","intvolume":"        40","page":"393-419","citation":{"mla":"Beran, Jan, and Yuanhua Feng. “SEMIFAR Models—a Semiparametric Approach to Modelling Trends, Long-Range Dependence and Nonstationarity.” <i>Computational Statistics &#38; Data Analysis</i>, vol. 40, no. 2, Elsevier BV, 2002, pp. 393–419, doi:<a href=\"https://doi.org/10.1016/s0167-9473(02)00007-5\">10.1016/s0167-9473(02)00007-5</a>.","bibtex":"@article{Beran_Feng_2002, title={SEMIFAR models—a semiparametric approach to modelling trends, long-range dependence and nonstationarity}, volume={40}, DOI={<a href=\"https://doi.org/10.1016/s0167-9473(02)00007-5\">10.1016/s0167-9473(02)00007-5</a>}, number={2}, journal={Computational Statistics &#38; Data Analysis}, publisher={Elsevier BV}, author={Beran, Jan and Feng, Yuanhua}, year={2002}, pages={393–419} }","short":"J. Beran, Y. Feng, Computational Statistics &#38; Data Analysis 40 (2002) 393–419.","apa":"Beran, J., &#38; Feng, Y. (2002). SEMIFAR models—a semiparametric approach to modelling trends, long-range dependence and nonstationarity. <i>Computational Statistics &#38; Data Analysis</i>, <i>40</i>(2), 393–419. <a href=\"https://doi.org/10.1016/s0167-9473(02)00007-5\">https://doi.org/10.1016/s0167-9473(02)00007-5</a>","ama":"Beran J, Feng Y. SEMIFAR models—a semiparametric approach to modelling trends, long-range dependence and nonstationarity. <i>Computational Statistics &#38; Data Analysis</i>. 2002;40(2):393-419. doi:<a href=\"https://doi.org/10.1016/s0167-9473(02)00007-5\">10.1016/s0167-9473(02)00007-5</a>","chicago":"Beran, Jan, and Yuanhua Feng. “SEMIFAR Models—a Semiparametric Approach to Modelling Trends, Long-Range Dependence and Nonstationarity.” <i>Computational Statistics &#38; Data Analysis</i> 40, no. 2 (2002): 393–419. <a href=\"https://doi.org/10.1016/s0167-9473(02)00007-5\">https://doi.org/10.1016/s0167-9473(02)00007-5</a>.","ieee":"J. Beran and Y. Feng, “SEMIFAR models—a semiparametric approach to modelling trends, long-range dependence and nonstationarity,” <i>Computational Statistics &#38; Data Analysis</i>, vol. 40, no. 2, pp. 393–419, 2002."},"year":"2002"}