| 书目名称 | Latent Variable Modeling and Applications to Causality |
| 编辑 | Maia Berkane |
| 视频video | http://file.papertrans.cn/582/581808/581808.mp4 |
| 丛书名称 | Lecture Notes in Statistics |
| 图书封面 |  |
| 描述 | This volume gathers refereed papers presented at the 1994 UCLA conference on "La tent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability co |
| 出版日期 | Conference proceedings 1997 |
| 关键词 | Estimator; Factor analysis; Fitting; Latent variable model; Likelihood; best fit; correlation; expectation– |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-1842-5 |
| isbn_softcover | 978-0-387-94917-8 |
| isbn_ebook | 978-1-4612-1842-5Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 1997 |
|Archiver|手机版|小黑屋|
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