{"title":"空间相关面板数据的统一非参数推理:xtnpsreg命令","authors":"Jia Li, Z. Liao, Wenyu Zhou","doi":"10.1177/1536867X231162035","DOIUrl":null,"url":null,"abstract":"In this article, we introduce a command, xtnpsreg, that implements a uniform nonparametric inference procedure for possibly unbalanced panel datasets with general forms of spatiotemporal dependence. We demonstrate how to apply this command via several examples, including 1) the nonparametric estimation of the conditional mean function and its marginal response, 2) the construction of uniform confidence bands for these nonparametric functional parameters, 3) specification tests for parametric model restrictions, and 4) the estimation and uniform inference for functional coefficients in semi-nonparametric models.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"23 1","pages":"243 - 264"},"PeriodicalIF":3.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uniform nonparametric inference for spatially dependent panel data: The xtnpsreg command\",\"authors\":\"Jia Li, Z. Liao, Wenyu Zhou\",\"doi\":\"10.1177/1536867X231162035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we introduce a command, xtnpsreg, that implements a uniform nonparametric inference procedure for possibly unbalanced panel datasets with general forms of spatiotemporal dependence. We demonstrate how to apply this command via several examples, including 1) the nonparametric estimation of the conditional mean function and its marginal response, 2) the construction of uniform confidence bands for these nonparametric functional parameters, 3) specification tests for parametric model restrictions, and 4) the estimation and uniform inference for functional coefficients in semi-nonparametric models.\",\"PeriodicalId\":51171,\"journal\":{\"name\":\"Stata Journal\",\"volume\":\"23 1\",\"pages\":\"243 - 264\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stata Journal\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1177/1536867X231162035\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X231162035","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
Uniform nonparametric inference for spatially dependent panel data: The xtnpsreg command
In this article, we introduce a command, xtnpsreg, that implements a uniform nonparametric inference procedure for possibly unbalanced panel datasets with general forms of spatiotemporal dependence. We demonstrate how to apply this command via several examples, including 1) the nonparametric estimation of the conditional mean function and its marginal response, 2) the construction of uniform confidence bands for these nonparametric functional parameters, 3) specification tests for parametric model restrictions, and 4) the estimation and uniform inference for functional coefficients in semi-nonparametric models.
期刊介绍:
The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.