Author: Terry Ross SmithPublisher:
ISBN:
Category : Agricultural prices
Languages : en
Pages : 200
Book Description
A Statistical Model for Characterizing Price Variability with Application to Dairy Investment Analysis
Author: Terry Ross SmithPublisher:
ISBN:
Category : Agricultural prices
Languages : en
Pages : 200
Book Description
American Doctoral Dissertations
Author: Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 784
Book Description
Dissertation Abstracts International
Author: Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 598
Book Description
World Agricultural Economics and Rural Sociology Abstracts
Author: Comprehensive Dissertation Index
Author: Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 984
Book Description
Comprehensive Dissertation Index: Agriculture
Author: Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 1080
Book Description
The Journal of Agricultural Economics Research
Author: An Author and Permuted Title Index to Selected Statistical Journals
Author: Brian L. JoinerPublisher:
ISBN:
Category : Annals of mathematical statistics
Languages : en
Pages : 512
Book Description
All articles, notes, queries, corrigenda, and obituaries appearing in the following journals during the indicated years are indexed: Annals of mathematical statistics, 1961-1969; Biometrics, 1965-1969#3; Biometrics, 1951-1969; Journal of the American Statistical Association, 1956-1969; Journal of the Royal Statistical Society, Series B, 1954-1969,#2; South African statistical journal, 1967-1969,#2; Technometrics, 1959-1969.--p.iv.
NBS Special Publication
Author: Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 574
Book Description
Linear Models in Statistics
Author: Alvin C. RencherPublisher: John Wiley & Sons
ISBN: 0470192607
Category : Mathematics
Languages : en
Pages : 690
Book Description
The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.