Excerpt from Missing<br/><br/>Our procedure was developed to model the forest growth and yield functions when there are more than two repeated measure ments per plot, but not all measurements are made on every plot. The program was developed to obtain solutions to this model, but can also be used to solve several well known statistical models including the multi variate linear regression model (anderson and Zellner's (1962) seemingly um related regressions model.
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Paperback. Zustand: New. Print on Demand. This book focuses on how to calculate maximum likelihood estimates of the parameters of a multivariate linear model with correlated errors when some of the dependent variates are not measured on some of the experimental units. The author presents a computer program that obtains these estimates and can also be used to solve several well-known statistical models, including the multivariate linear regression model. Providing definitions and notations used in incomplete multivariate models, the author delves into the subject of maximum likelihood estimates and how they are calculated. Practical examples demonstrate the program, and the author addresses sample problems, issues, warnings, and error messages that may occur. With its clear explanations and illustrative examples, this book is a valuable resource for researchers and practitioners in statistics, econometrics, and related fields, as well as students studying these disciplines. By providing a user-friendly tool for obtaining maximum likelihood estimates in incomplete multivariate linear models, this book makes complex statistical calculations more accessible and efficient. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Bestandsnummer des Verkäufers 9780365808954_0
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