{"title":"用脉冲响应区分时间序列模型——以死亡率和人口经济为例","authors":"T. Bengtsson, G. Broström","doi":"10.1080/01615449709601183","DOIUrl":null,"url":null,"abstract":"Distinguishing time series models by impulse response-A case study of mortality and population economy","PeriodicalId":45535,"journal":{"name":"Historical Methods","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/01615449709601183","citationCount":"9","resultStr":"{\"title\":\"Distinguishing time series models by impulse response-A case study of mortality and population economy\",\"authors\":\"T. Bengtsson, G. Broström\",\"doi\":\"10.1080/01615449709601183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distinguishing time series models by impulse response-A case study of mortality and population economy\",\"PeriodicalId\":45535,\"journal\":{\"name\":\"Historical Methods\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"1997-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/01615449709601183\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Historical Methods\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1080/01615449709601183\",\"RegionNum\":2,\"RegionCategory\":\"历史学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HISTORY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Historical Methods","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/01615449709601183","RegionNum":2,"RegionCategory":"历史学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HISTORY","Score":null,"Total":0}
期刊介绍:
Historical Methodsreaches an international audience of social scientists concerned with historical problems. It explores interdisciplinary approaches to new data sources, new approaches to older questions and material, and practical discussions of computer and statistical methodology, data collection, and sampling procedures. The journal includes the following features: “Evidence Matters” emphasizes how to find, decipher, and analyze evidence whether or not that evidence is meant to be quantified. “Database Developments” announces major new public databases or large alterations in older ones, discusses innovative ways to organize them, and explains new ways of categorizing information.