{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T04:29:12Z","timestamp":1690345752900},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684109","type":"print"},{"value":"9781643684116","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,21]]},"abstract":"<jats:p>With the continuous development of emerging economic forms, the disadvantages of traditional statistical measures are becoming increasingly prominent. The performance measure of the emerging economic statistical index is also an urgent problem to be solved. This paper propose a performance evaluation frame for emerging economic statistic index which takes traditional index as the benchmark. The proposed method uses the spectral analysis method to analyse the periodogram of the time series, determine the appropriate parameters according to the filter, and filter the time series to obtain the trend and periodic terms of the sequence. Use the ANOVA method for trend items to analyse the consistency of trend items, and use the mutual spectral analysis method to analyse the consistency and leading lag of new indicators and benchmark indicators. By using the method of frequency domain analysis and mutual spectral analysis, the components of this frame include the preprocessing, analysis, comparison of innovative statistical index data, and obtain the performance evaluation results of innovation indicators, which provides a solution for the quantitative analysis of innovation index. This paper also give a specific example to present how this framework works to evaluate the performance of an emerging economic statistic index.<\/jats:p>","DOI":"10.3233\/faia230190","type":"book-chapter","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T13:01:09Z","timestamp":1690290069000},"source":"Crossref","is-referenced-by-count":0,"title":["Performance Evaluation Framework for Emerging Statistical Index Based on Mutual Spectral Analysis"],"prefix":"10.3233","author":[{"given":"Meijiao","family":"Wang","sequence":"first","affiliation":[{"name":"Yunnan Police College, Kunming, China"}]},{"given":"Yanjun","family":"Qian","sequence":"additional","affiliation":[{"name":"Survey office of the National Bureau of Statistics in Yunnan, China"}]},{"given":"Libo","family":"He","sequence":"additional","affiliation":[{"name":"Yunnan Police College, Kunming, China"}]},{"given":"Yunyun","family":"Wu","sequence":"additional","affiliation":[{"name":"Yunnan Police College, Kunming, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Modern Management Based on Big Data IV"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230190","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T13:01:17Z","timestamp":1690290077000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,21]]},"ISBN":["9781643684109","9781643684116"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230190","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,21]]}}}